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Renewable integration for remote communities: Comparative allowable cost analyses for hydro, solar and wave energy
Abstract
Many remote communities are reliant on diesel-fueled electricity generation. The extra-ordinary logistical and financial complications in acquiring fuel often result in energy poverty. To alleviate these realities, and simultaneously mitigate noise and emissions, communities are focused on harnessing local renewable resources to achieve aggressive decarbonization and renewable energy penetration.
This study quantifies the diesel and emissions mitigation potential of micro-hydro, solar and wave energy; and defines ‘allowable-cost’ Levelized Cost of Energy (LCOE) targets. Through the application of a bottom-up, time domain energy systems model, Remote Community Optimization Model (RCOM), differing renewable options (including wave, micro-hydro and solar) are compared. The RCOM model formulates the community’s energy system operation as a cost minimization optimization problem and generates an hourly dispatch strategy. Comparing hybrid renewables-based systems to the diesel only case, the maximum allowable LCOE values for each renewable energy system to provide economic benefit to the local community are quantified. Additional sensitivities to resource availability, emissions pricing and fuel costs are explored through scenario-based sensitivity analyses.
Utilizing RCOM for Hot Springs Cove (remote Canadian community), the diesel system results in LCOE of 5.2 M over the 30-yr. project lifetime. However, these savings are less than the upfront construction capital, and the associated LCOE increases to 0.59/kWh; with the added benefit of reducing diesel consumption by 40%, and returning 0.53/kWh, reduced diesel consumption by only 12%, and gave a return of $6844/kW installed.
... By employing advanced techniques, such as data-driven modeling and RL, Gen-AI can iteratively refine design configurations based on criteria like energy conversion efficiency, durability under environmental stressors, and material costs. This is especially valuable in applications where solar system sizing is critical for performance, such as remote or off-grid locations [73]. Moreover, Gen-AI's role in system sizing extends to integrating renewable energy sources with existing power grids, ensuring seamless operation and maximum energy utilization. ...
... Data processing Limited by the capacity of existing tools to handle various data types effectively [73]. ...
... Dynamic approach that considers current energy needs and anticipates future changes. Adaptable to evolving conditions [73]. ...
Driven by growing environmental concerns, such as global warming and the depletion of fossil fuels, the renewable energy industry, particularly solar energy, has risen to global prominence. In this context, generative artificial intelligence (Gen-AI) can play a valuable role in facilitating the development of more efficient, durable, and adaptable solar systems. Gen-AI’s multifaceted proficiency, from predictive maintenance and reducing downtime and costs to vital forecasting for grid management and strategic planning, extends to optimizing site selection for solar farms and smart grid integration, thereby enhancing solar energy flow, grid stability, and sustainable operation. This paper presents a comprehensive exploration of the role of Gen-AI in revolutionizing the solar energy industry. Focusing on various aspects of solar energy systems, including design, optimization, sizing, maintenance, energy forecasting, site selection, and smart grid integration, the study investigates the transformative impact of Gen-AI across these domains. It demonstrates how Gen-AI enhances the efficiency, sustainability, and adaptability of solar systems, driving strategic decision-making and optimizing the integration of solar power within complex energy ecosystems. Furthermore, the paper concludes by discussing the challenges and future prospects of employing Gen-AI in the solar energy domain, providing a comparative analysis of the current and future scenarios, and underscoring the advantages, disadvantages, and challenges of Gen-AI implementation.
... In this respect, community-based energy systems allow a greater energy access than centralized ones, even in areas with no access to the national grid [72]. As an example, solar-driven SECs may represent an interesting alternative in meeting off-grid rural communities' electricity demand with sustainable electricity, thus boosting the decarbonization of energy islands, i.e., areas with poor or inexistent connections to the grid [70], where the electricity generation relies on diesel-fuelled systems [73]. In [74], a SEC is designed to increase energy SS, stability and flexibility of the Italian island of Ischia. ...
... Therefore, the presence of EVs leads to significative economic savings, which can be shared within all members of the SEC, according to their agreements. This cost-saving solution, together with the enhancement of local RESs exploitation [73], demonstrates that SECs may improve local economy. In addition, SECs have the potential of unlocking private investments and financing renewable energy generation units, thus increasing their pervasiveness and social acceptability [79]. ...
... This topic has been analysed in references [13,[36][37][38][39]43,49,61,68,70,74,78,86]. The fourth column refers to local RESs valorisation, and accounts for eight check marks corresponding to references [36,49,69,70,[72][73][74]78]. No more than ten check marks are found in all remaining columns. ...
The Smart Energy Community topic has attracted a lot of interest from policy, research centres, companies and private citizens since 2018, when in Europe the recast of the Renewable Energy Directive, and later in 2019 the Internal Electricity Market Directive, came into force to support the new role of users in energy systems. Following these directives, energy community exper-imentations, real projects and/or simulations and case studies have been developed and investigated in the literature. In this review paper, an investigation of recent literature about Smart Energy Communities in terms of common characteristics, fundamental scopes, and principal indexes used for their evaluation, has been realized by considering 111 scientific references, 78 of which have been published since 2018. The reference papers have been selected through the "Preferred Reporting Items for Systematic reviews and Meta-Analysis" methodology. In developing the review, significant barriers to Smart Energy Communities' diffusion emerged. The main shortcomings concern citizens' uncertainty about these new projects, due to their poor information and technical skills. These issues often hide energy, economic, environmental, and social benefits of Smart Energy Communities. Therefore, this study wants to be an opportunity for bringing to the attention of citizens Smart Energy Communities' positive outcomes, especially from the social point of view, thus boosting their spreading and overcoming still existing criticalities.
... However, the authors did not consider economical feasibility in the study nor system sizing optimization. In [26], the authors used the Remote Community Optimization Model (RCOM) to compare different energy system designs to supply the power demand of a remote community in the Canadian West Coast. Their objective function optimized the dispatch of the hydro and diesel generators. ...
... The COE is a key indicator of the effectiveness and viability of an energy project. The COE of an isolated system in a remote community is typically around USD0.363/kWh, as reported by the authors of studies conducted in Transylvania [14], India [15] and the Canadian West Coast [26] rural communities. The hybrid PVS with generator and storage presented in this study has a COE of USD0.14/kWh. ...
Many rural communities in developing countries rely on diesel-fueled power generation, in which the use of hybrid renewable energy systems (HRES) is an environmentally and economically attractive option. The main objective of this study is to analyze the feasibility to implement a HRES based on photovoltaic technology. The main contribution is to present a reliable and adaptable methodology to optimize an energy system sizing and fuel consumption to meet the power demand in rural areas, regardless of the geographic location or load profile, that can be easily implemented in freely available tools. For this purpose, a typical load scenario provided by an industrial partner is considered. This consumption data was compiled from experimental measurements in different rural communities, which averages a daily consumption of approximately 300 kWh. Three different power systems are analyzed: (i) a diesel generator with battery storage, (ii) a photovoltaic system with storage, and (iii) a photovoltaic system with diesel generator and battery storage. For each case, three storage technologies were considered, namely: lead–acid, Li-ion and absorbent glass mat (AGM), from which the first one was the least expensive. These storage systems were operated within the limits of maximum load and minimum discharge that each technology establishes. The photovoltaic/diesel-generator/AGM battery hybrid power system turned out to be the least expensive and the most feasible, with a net present cost of USD311,632.53 and a cost of energy (COE) of USD0.14/kWh. The presented results demonstrate the advantages and disadvantages of each system, as well as their economic and technical feasibility. A cost reduction was found regarding the COE when comparing the system proposed in this study to other reported studies. Additionally, a sensitivity analysis was performed to report the impact of cost variations on the overall COE. These results prove that it is possible to satisfy the electrical demand of rural communities at a reasonable and accessible cost.
... Most of the remote and off-grid communities still lack energy. Traditionally, the only way to meet their electricity and heating demands is using diesel generation, an analysis of which has been included in several case studies [9][10][11][12][13]. Indeed, diesel has several advantages that make it very attractive: it has a high energetic potential (1 L of diesel corresponds to around 10 kWh), is easily transported, and is low cost to produce (at least before the current war in Ukraine). ...
This paper aims to explore the feasibility of establishing self-sufficient electricity generation systems in off-grid remote communities using renewable energy sources. It provides an overview of current trends and developments in Renewable Energy Communities worldwide, with a focus on remote locations. To assess the technical feasibility, simulations were conducted using PVGIS for irradiation data and a load generator for energy consumption data. Different scenarios combining photovoltaic modules with lithium-ion battery systems were simulated using a dedicated optimization model developed in the PYTHON environment. The simulations aimed to size the entire system for three distinct locations: Congo, Australia, and Canada. The optimal number of PV modules determined for each location was 50 for Congo and 55 for Australia, and the battery system sizes were found to be 225 kWh and 150 kWh, respectively, admitting usual practices for the energy not supplied. The results obtained regarding Canada pointed to a system difficult to justify from an economic standpoint due to challenging weather conditions, namely, the existence of several consecutive days without irradiation.
... Paneller, turist gemilerinin enerji ihtiyacını karşılamak için kullanılır ve bu sayede denizlerde daha temiz bir enerji kaynağı sağlanır. Proje, geniş bir yatırımcı kitlesinin desteklediği ve blockchain sayesinde fonların nasıl kullanıldığını ve enerji üretim süreçlerini şeffaf bir şekilde izlemeye olanak tanıyan bir model sunmuştur (Robertson, Bekker, & Buckham, 2020). • "EcoTourism Blockchain Platformu" EcoTourism Blockchain Platformu, global çapta sürdürülebilir turizm projelerini destekleyen bir blockchain platformudur. ...
Bu çalışma, blockchain tabanlı kitle fonlamasının sürdürülebilir turizm
projelerindeki potansiyelini ve bu yenilikçi finansman yönteminin projelere
sağladığı avantajları incelemektedir. Geleneksel finansman yöntemlerinin
yetersiz kaldığı durumlarda, blockchain teknolojisinin sunduğu şeffaflık,
güvenlik ve merkeziyetsizlik özellikleri, sürdürülebilir turizm projelerinin hayata
geçirilmesine önemli katkılar sunmaktadır.
... Climate change will have a significant influence on the energy management of this group of Indigenous people in Canada. Canada had over 670 megatons of CO 2 emissions and per capita emissions of 17.5 tons of CO 2 in the year 2021 [8,9]. ...
The steep decline in the price of wind and solar photovoltaics provides a possibility to decarbonize electricity deeply and affordably. This study uses the HOMER Pro energy modeling tool to model an optimized grid-connected renewable energy system for a community in southern Alberta, Canada. The study’s goal is to identify the best renewable energy technology combinations that can provide electricity at the lowest levelized cost of energy (LCOE) and has lower greenhouse gas emissions as compared to the electricity produced by traditional fossil fuel. Gleichen is a small town in southern Alberta that is close to numerous commercial wind and solar projects given the region’s high quality renewable resources. “Tri-brid” systems consisting of wind turbines, solar photovoltaics, and battery energy storage systems (BESS) are considered and compared based on electricity prices, net present cost, and greenhouse gas emissions savings. This tri-brid system is connected to the grid to sell excess generated electricity or buy electricity when there is less or no availability of solar and wind energy. The tri-brid energy system has an estimated LCOE of 0.0705 CAD/kWh, which is competitive with the price of electricity generated by natural gas and coal, which is 0.127 CAD/kWh.
... The field of wave energy conversion is currently living at a tipping point [1]: on the one hand, the extremely high potential of production of renewable energy exploiting ocean waves is broadly recognized, not only by the academia [2], but also by policy-makers [3] and funding agencies [4], thanks to its complementarity with other renewable energy sources [5] and widespread availability [6]; on the other hand, ambitions are yet to be met, as the industry is still struggling to reduce the livelised cost of energy (LCoE) to become competitive with other renewable energy sources [7]. Techno-economic optimizations based on representative continuously improving estimations of LCoE [8] are the main routes followed to achieve economic viability. ...
... Wave energy has the highest energy density among other marine renewable energy sources [2]. Several studies explored the possibility of utilizing wave energy in various locations around the world, such as Gulf of Oman [3,4], the Persian Gulf [4,5], the Atlantic coast of Europe [6][7], Atlantic Ocean [8] and many other locations. There are several advantages of utilizing wave energy such as, having limited environmental impact, the energy is available throughout the day, and having high-energy fluxes. ...
Al Hallaniyat Island is located in the southern part of Oman. The island has a low number of population and is currently fed by a number of diesel generators with a capacity of 1568 kW. Decreasing the emission of greenhouse gases is one of the main goals for the country’s vision of 2040 as well as Oman’s commitment to net-zero emissions by 2050, in line with the Paris Agreement of limiting global warming to 1.5°C. The purpose of this paper is to study the feasibility of replacing diesel generators with 100% renewable energy sources. The proposed energy source for the Island will be a hybrid system consisting of the wave energy converter, PV, wind and battery storage system. Real load data was used in the model with measured wind speed and solar radiation. The Hybrid Optimization Model for Electric Renewables software is used in this study. Several systems were proposed but the most economical one is PV-Wind-Wave-Battery system that resulted in levelized cost of energy of US 5,010,594. Having PV-Wave-Battery will result in levelized cost of energy of US/kWh 0.42.
... It should be reminded here that the levelized cost of electricity (LCOE) represents the present value of the price of the electricity produced, considering the economic life of the plant and the costs incurred in the construction, operation, and maintenance [23][24]. [27] 2018 Cameroon 100 kWh/day 18 PV/DG/MH/BS 0.443 Kamran et al. [28] 2019 Pakistan 1536 kWh/day 79 MH/Grid 0.011 Robertson et al [29] 2020 Canada The micro-hydro based RES-GS were studied mostly for communities with multiple houses. To our knowledge, for individual buildings only the cost-effectiveness of the PHS in high-rise buildings was investigated. ...
This work aims to identify a cost-effective solution for improving the energy performance of a grid-connected prosumer, possibly equipped with electric vehicle chargers. The solution is based on a small-scale energy system based on renewable energy sources (RES). The system is equipped with an Archimedes Screw Turbine (AST) and photovoltaic panels. Energy storage in batteries is also considered. A simple yet efficient method for sizing the AST is proposed. A cost-benefit analysis of the small-scale energy system is performed for six case studies covering different combinations of energy consumers. Three economic scenarios are considered for each case study. The results suggest that the AST-based solution leads to reasonable costs for the prosumer and less impact of energy price fluctuations. Also, if EV chargers are used, their consumption can be covered directly by RES.
... The Siksika Nation, a group of three Indigenous nations in Canada, relies on diesel generators to generate electricity, which has major negative effects on the environment, including global warming, greenhouse gas emissions, air pollution, and water pollution. Climate change will have a significant influence on energy management of this group of Indigenous people of Canada [7,8]. Canada had over 670 megatons of CO2 emissions while per capita emission is 17.5 tons of CO2 year 2021 [9]. ...
The steep decline in the price of wind and solar photovoltaics provides a possibility to decarbonize electricity deeply and affordably. This study uses HOMER Pro energy modeling tool to model an optimized grid-connected renewable energy system for a community in southern Alberta, Canada. The study's goal is to identify the best renewable energy technology combinations that can provide electricity at the lowest levelized cost of energy (LCOE) and has lesser greenhouse gas emission as compared to the electricity produced by traditional fossil fuel. Gleichen, is a small town in southern Alberta and is near to numerous commercial wind and solar projects given the region’s high quality renewable resources. “Tri-brid” systems consisting of wind turbines, solar photovoltaics, and battery energy storage systems (BESS) are considered and compared based on electricity prices, net present cost, and greenhouse gas emissions savings. This tri-brid system is connected to the grid to sell excess electricity generated or buying electricity when there is less or no availability of solar and wind. The tri-brid energy system has an estimated LCOE of 0.0705 CAD/kWh which is competitive with the price of electricity generated by natural gas and coal which is 0.127 CAD/kWh.
... Over the past few years, various technologies have been utilized for the research and development of marine resources as a result of technological advancements, including the use of artificial intelligence models to predict sea conditions, such as marine weather [1][2][3], and to study phenomena such as turbulence [4,5]; A marine system for the acquisition of marine energy and other resources [6,7]; Automated navigational systems for the navigation of ships [8][9][10], and so on. It is important to note, however, that these technologies cannot be developed or optimized without a change, marine resource development, and early warnings of marine disasters is the ocean, which is the largest ecosystem on earth. ...
... Ocean Wave Power Plant (WEC) can be divided into 6 types, namely (1) Point absorber, (2)Oscillating Water Column, (3) Pressure Differential Submerger, (4) Oscillating Wave Surge Converter, (5) Attenuator & Terminator, and (6) Removable Device [1] [2]. [3] - [6]. ...
Ocean Wave Power Plants (WEC) are divided into 6 types, namely (1) Point Absorber, (2) Oscillating Water Column, (3) Pressure Differential Submerger, (4) Oscillating Wave Surge Converter, (5) Attenuator & Terminator, and ( 6) Removable Devices. The AquabuOY type is a type of Point Absorber type wave power generator. This type uses a long pump connected to a Pelton turbine and was developed by Finavera (Aquaenergy) Company of Canada. The AquabuOY system has a weakness in that the turbine rotation depends on the wave period that occurs. The slower the wave period occurs, the weaker the resulting turbine rotation, therefore it needs to be improved by adding a reservoir unit to obtain pressure. stability and puffiness of the unit so that the rotation produced in the turbine is much greater. With this addition, the generator will spin more quickly and stably. In addition, the addition of wind energy installed at the top of the unit means that the generator to be built will produce more energy, is more flexible, can be placed in shallow, medium or deep seas, does not require complicated foundations, is relatively cheap, is not affected by extreme weather. and can be used in all sea conditions just by attaching it to a ballast. This study examines the effect of pump diameter and outlet pipe diameter on the electrical power generated at a hybrid power plant. pump diameter variations of 8 inches, 10 inches, 12 inches and 14 inches. Variation of outlet pipe diameter 1 inch, 2 inch, 3 inch and 4 inch. In this paper, we will present a simulation of the calculation of electrical energy from wave power with variations in pontoon volume, pump diameter, and outlet pipe diameter to obtain the most optimal system size. while wind energy power generation is presented in a different pape. Calculation simulation results to get the most optimal pump diameter and outlet pipe diameter in the hybrid power plant system built.
... Reference is also made to [4], where Renewable Energy Alternatives for Remote Communities in Northern Ontario, Canada, are considered. In reference [5] , a cost analysis is carried out for remote communities when hydro, solar and wave energy are available. To identify renewable energy alternatives where hydropower or wood is not available (like on Flatøy) or where the construction costs of wave energy plants will be too onerous, is a large challenge, therefore, the case of providing the barren Flatøy with renewable energy represents the ultimate challenge. ...
The need for transitioning towards renwable energy and sustainable storage solutions is particularly challenging for remote communities in the Arctic, located far away from the electricity grid. This paper explores the potential for use of renewable energy on the remote island of Flatey, Iceland, which currently relies on two diesel aggregates for power. The primary goal is to assess the feasibility of transitioning from fossil fuels to renewable energy sources, such as solar or wind power, to meet the island’s variable energy demand while reducing its environmental impact. With a year-around population of 5 and with a considerably increased energy consumption during vacation times, due to more population, Flatey’s annual energy consumption is ~ 209.000 kWh, peaking in July at ~ 25.000 kWh. This fluctuation requires an adaptable and resilient energy infrastructure. The paper examines the viability of Flatey as a self-sufficient renewable energy provider. The study considers the island’s energy requirements, consumption patterns, and geographical constraints, while also evaluating technical, economic, and social factors that may influence renewable energy adaption. This paper, thereafter, investigates the feasibility of achieving energy self-sufficiency on the small island of Flatey. Different energy storage options is considered, focusing on battery storage, underground solar power/energy storage, and hydrogen storage.
... Hybrid renewable energy systems show advantages in reducing cost, improving power stability, and increasing power product. For remote communities, a comparative allowable cost analysis in [19] shows that the integration of solar and wave energies to a diesel-fueled grid can reduce both the levelized cost of energy (LCoE) and the diesel consumption; on the contrary, the integration of hydro energy to the diesel-fueled grid increases the LCoE. For solar-wind hybrid energy systems, their energy resource availability, optimal sizing, modelling, control and reliability issues are discussed in [20], with conclusions to address the significance of resource availability and sizing optimisation. ...
Due to climate issues and energy crisis, the development and usage of marine renewable energies are on the rise. However, ocean wind, solar and wave energies are intermittent, and there are few studies investigated the correlation and complementarity of these ocean renewable energy resources. This study investigates the energy density, variability, correlation, and complementarity of these three marine renewable energy sources in the South China Sea and its surrounding areas, based on the ERA5 database in 2022. The study points out that wind and wave energies are enriched in the northern and central South China Sea, and solar energy is evenly distributed. Numerical results also reveal that the temporal distribution of solar energy in the South China Sea is most stable, followed by wind energy and wave energy. In this study, solar energy shows complementary feature with wind and wave energies, while wind and wave energies are correlated. The results are expected to provide a basic guideline for the design of hybrid ocean renewable energy platforms.
... The global energy outlook is undergoing a monumental shift, driven by the pressing imperatives of mitigating climate change and fostering sustainable development [1]. As societies recognize the urgent need to decarbonize their energy sectors, the transition from fossil fuels to renewable energy sources has taken center stage. ...
This study delves into power system flexibility, with a keen focus on the integration of variable renewable electricity generation into power grids. Two scenarios were analyzed. The base scenario revealed an aging grid, insufficient generation capacity, frequent outages, and little renewable energy generation (1.9%), along with a significant (71.23%) loss of load. In contrast, the investment scenario presented solutions including raising VRE capacity to 44%, adding 1000 MW capacity transmission lines, installing 200 MW capacity grid-scale battery storage, and technological enhancements. These interventions effectively eliminated loss of load, reinforcing energy resilience. Investments in CCGPP and grid-scale batteries proved instrumental in mitigating the variability of renewable energy. Improved transmission promised efficient power exchange and regional collaboration. The elimination of annualized energy spills and the removal of ramping constraints marked significant strides in enhancing power system flexibility. This research underscores the pivotal role of grid flexibility in accommodating VRE sources. By implementing the proposed optimal solutions, Afghanistan can lead the way toward a cleaner, more resilient, and more interconnected energy future. These findings offer a replicable framework for addressing similar challenges in integrating renewable energy sources globally and supporting the transition to sustainable and reliable energy.
... A typical approach for these studies is to conduct sensitivity analysis or rely on diverse static inputs like component costs, efficiencies, energy storage throughput, and discount rates. With this approach, the primary input parameters are the time series data of RE (solar/wind) and load demand, as it has been well-recognized that the intrinsic variability of these series substantially challenges the reliability and robustness of RES, in particular, for off-grid power systems [19][20][21][22]. Researchers often limit themselves (due to data availability or practicality) to using one-year time series to design and optimize the RE-based microgrids that might considerably underestimate or oversize the demand-supply gaps and thus the energy storage requirements [23][24][25][26] or the primary RE generation components [27,28]. ...
It remains a significant technical and economic challenge to fully power large-scale grids with intermittent renewable energy (RE). Meanwhile, due to the rapid decrease in the cost of RE power generation technologies in recent years, the number of real-world implementations and studies dedicated to the optimal capacity sizing of renewable off-grid systems has increased. However, a common approach in the literature is to rely on typical single-year meteorological and demand data. A negative effect of this assumption is that it does not consider the RE inter-annual variability, which might cause blackouts or oversizing the system and large curtailments. This study employs 43 years of hourly solar, wind, and demand data, coupled with different microgrid configurations, to evaluate the impact of diverse simulation periods on the total system cost, optimal RE mix, and system reliability. Our findings indicate that extended simulation periods considerably increased renewable energy systems (RES) reliability and that the resulting configurations can be up to 94% more robust than those obtained using a single year of data. Additionally, the optimal energy storage requirements increased when considering longer simulation periods, indicating that short simulation periods could underestimate energy storage capacities in off-grid systems. The overestimations or underestimations resulting from optimizations based on single-year data directly affect the long-term sustainability, reliability, and cost-effectiveness of the RES.
... As the global warming threat continues to increase, the energy mix needs to be more dominated by renewable energies (MacKay, 2009;Robertson et al., 2020); hence investing in all types of renewables is urgent (Kenny et al., 2010). In this context, and despite its potential ( Energy Converter (WEC) is a device that harvests energy from the ocean waves and converts it into electricity for consumption (Shadman et al., 2019), amongst many other applications (Clemente et al., 2021). ...
< This thesis comes with comments related to the last updates on my research > Abstract: With an augmentation in energy needs from population-growth and digitalisation, and increasing global warming and climate change, the global energy mix needs to rely less on fossil resources and more on renewable energy sources. This thesis is dedicated to wave renewables which form part of marine renewable energies. A Wave Energy Converter (WEC) is a mechanical device used to harvest the energy from ocean waves. Due to the large variety of designs, properly assessing where each WEC works best and increasing its appeal to the market is challenging. Indeed, many approaches for WEC-location pairing have been developed but their integration is missing alongside misuse of optimisation methods and neglecting crucial aspects for WEC (and farm) assessments such as the wave direction (and period) and potential response to the actual energy demand, amongst others. Furthermore, too often studies reduce their area for assessing wave energy installation to high energy power/energy locations, whereas some studies have shown that WECs may work best in lower resource conditions, which need to be assessed further. This thesis develops an integrated method divided into a collection of six chapters assessing main aspects of the wave renewable energy WEC-location pairing by: 1. Developing the CapEx method for adjusted cost estimations of the technologies under different configurations (design, size, and dimensions) and locations’ characteristics, 2. Analysing optimisation methods for enhanced technology energy production and capacity factor assessment, 3. Investigating the annual energy production relationship with the farm costs based on the expansion of the CapEx method for various designs of technology, 4. Conducting a region and wave resource assessment for renewable energy farm installation based on indices and metrics analyses alongside geographical limitations of potential areas, 5. Developing a framework for pairing fixed-designed WECs and locations based on the capacity factor, the energy production and response to the energy demand, alongside area restrictions’ impacts, for mapping optimal WEC-location pairs, 6. Classifying the WEC wave power and efficiency to compensate for the current classifications that are not fully correlated with the actual WEC energy production potential, to help the pre-assessment of WEC-location pairing over larger areas. This method is less time-consuming and potentially represent all possible WEC power production potential compared to the five previous chapters that are based on more detailed levels of pairing. The wave direction is mostly neglected in the literature although almost 50% of the WECs are wave direction-dependent and wave direction may greatly impact the wave farm energy production. Consequently, this is investigated in the chapters associated with points 2 to 5. In particular, the chapters associated with 2 and 3 involve the Wavepiston technology that is siginificantly dependent on the wave direction to provide optimal energy production. Chapter 4 assesses the wave direction of the resource by including parameters based on circular statistics. Chapter 5 provides a solution to include wave direction in the energy production matrices provided by the WEC developers. Finally, two integrations of the six developed pieces of method are provided, into a synthetic and a detailed ensemble method-framework. It enables selecting suitable WEC(s) for wave farm installation in a given site or area, or finding potential farm installation hotspots for a given WEC. This framework is built on wave distribution climates for given places or areas, locations’ characteristics (energy demand, urban, fauna, and flora restrictions to name a few), WEC and associated farm characteristics (water depth, moorings, grid connection type, etc.) and economics. This study highlighted the need for several “checks” and possible adjustments (wave spectrum, wave direction-dependency, scaling possibilities, linearity, and presence of generator-related limitations) and to frame each WEC study to help clarify their contribution. Although costs are challenging to obtain for large databases of WECs and configurations, the CapEx method unlocks the possibilities to compute economical indicators to enhance WEC-location mapping for wave farm analyses. Optimisations over the generator are encouraged in any case, but WEC configuration optimisations should be conducted carefully. In contrast, the new classes should be used for a higher reach by representing the majority of WECs. Furthermore, the method to pre-select locations based on high wave power (and unidirectional wave climate) is proven misleading and should no longer be considered; but instead, a fairer wave resource approach is provided. It should always be compared with the WEC-location pairs’ cartography (carefully discussing area restrictions) to conclude on wave farm installation and design.
... 23 Calculating a global LCOE for over 140 countries, the authors find that the LCOE of solar PV systems in high-latitude countries may, in fact, be lower than in equatorial countries because of varying financing costs, and therefore subsidizing solar PV systems in these countries may be a promising strategy. A similar finding of economic benefit in high-latitude countries was reported for Canada by Robertson et al. 32 The LCOE methodology is not limited to calculations of the historical costs but it can also be applied to project the costing in the future. Herná ndez-Moro and Martinez-Duart 18 used data from Germany, Spain, California, and Northern Africa to predict the development of solar PV and CSP up to 2050. ...
Solar photovoltaic (PV) electricity represents one of the most promising sources of clean and affordable en-ergy; however, the share of solar power in electricity production remains low, primarily because of the highinstallation costs. By conducting a large-scale analysis of electricity pricing, we show that solar PV systemsare quickly becoming one of the most competitive sources of electricity. Collecting a contemporary UK data-set of 2010–2021, we analyze the historical levelized cost of electricity for several PV system sizes, projectuntil 2035, and conduct a sensitivity analysis. The cost of PV electricity is currently at about 149 ₤/MWhfor the smallest-scale and 51 ₤/MWh for large-scale PV systems, already lower than the wholesale price ofelectricity, with PV systems predicted to get cheaper by 40–50% until 2035. The government should focuson supporting solar PV system developers with benefits such as simpler land purchases for PV farms or pref-erential loans with low interest rates.
... It is predicted to play a more significant role in the energy mix in the coming years (Du et al., 2014). Solar energy installation reduces diesel consumption by 12% and yields $6844/kW (Robertson et al., 2020). It determined that the return on solar energy use is $177.41 ...
This study examines the long-term relationships between solar energy, globalization, coal energy consumption, economic growth, and CO2 emissions. We included data from 26 countries for which data are available for 2000-2019. To consider the cross-sectional dependence and slope homogeneity, which are prominent in the panel data analysis, we preferred the mean group of co-related effects (CCEMG) method. According to OLS, FMOLS, and CCEMG estimations, solar energy consumption negatively affects CO2 emissions. A 1 % increase in solar energy consumption causes a 0.0106671% reduction in CO2 emissions. There is bidirectional causality between solar energy consumption and CO2 emissions in the long run. Globalization does not have a significant effect on CO2 emissions. However, coal energy consumption and economic growth appear to cause an increase in CO2 emissions. Because of the diversity and consistency of the methods we used to measure the relationships between variables in our article, the dominant power of solar energy in reducing carbon emissions has been proven once again. Encouraging the use of solar energy by countries and supporting investments in this field has emerged as benefiting from solar energy based only on the geographical advantage they have, regardless of globalization. For this reason, it is essential for environmental sustainability that governments give tax advantages and energy investment incentives to companies that prefer solar energy in their production processes. As a result, reduced carbon emissions will also bring about a greener environment.
... Renewable energy use means creating employment for economies (Bulavskaya and Reynès, 2018), providing environmental protection, and sustainable development (Akal, 2015;Chen et al., 2019;), reducing the cost of carbon reduction by developing more economical and more efficient technologies (Popp, 2012), having a significant impact on regional development (Miguez et al., 2006), offering great opportunities in the future (Robertson et al., 2020) and giving hopeless hope for energy soon (Chang et al., 2003). It also offers many opportunities such as contributing to economic growth (Alola & Yildirim, 2019). ...
The difference of this study from other studies is to investigate the relationship between renewable energy use and economic growth for energy importing countries that increased their renewable energy use by 556.91% (hydro 377.65% and solar etc. 1052.32%), their total GDP by 466.19% and their total energy imports by 388.96% in 2018 compared to 1990. While doing this, it analyzes real GDP, real gross capital, labor force, and renewable energy use for 16 energy importing countries in emerging economies, which have a special place among developing countries, with annual data for the period 1990-2018. Firstly, unit roots tests were used to determine the degree of stationarity of the series. Then, the cointegration relationship was tested with a heterogeneous panel cointegration test and a cointegration relationship was found. The coefficients of all variables were positive and statistically significant. In addition, according to the findings obtained from the error correction models, it has been obtained that there is unidirectional causality from economic growth to renewable energy use in both the short and long run. Therefore, the results show that the interdependent relationship between economic growth and renewable energy use supports the conservation hypothesis.
... Because their resource availability is not tied to local conditions, marine energy resources are highly predictable and persistent when compared to other renewables such as wind and PV [1]- [3]. Rather, the availability of wave energy resources, for example, is tied to the timing and location of storm activities across the entire ocean basin under investigation, with the Pacific Ocean being the focus of the current study. ...
Marine energy resources could promote clean energy and resilience of coastal and island microgrids, and thus, these applications are a key future market for marine energy development. To demonstrate these benefits, this paper illustrates how inclusion of wave resources into energy resilience solutions can improve overall grid efficiency and sustainability, as well as maintain electricity supply during grid outages. The paper describes a case study evaluation of the potential to add wave energy to the Moloka'i grid as Hawaii strives to meet a 100% clean energy target. The Microgrid Component Optimization for Resilience tool is used to simulate operation in off-grid conditions and size different combinations of wave, solar photovoltaic (PV), wind, storage, and fuel resources required to meet resilience objectives. This research investigates how including wave resources in a microgrid contributes to reducing or eliminating biofuel generation, producing a zero-greenhouse gas emission profile in the latter case, and avoiding the over-sizing of PV and battery systems to accommodate periods of unavailability or high demand. Insight from this paper supports the value proposition of wave resources for future markets and informs the relationship between marine generators and microgrids or isolated grids.
... Some recommendations are given in the latter part of the review to accelerate WE production in Australia. that noise and greenhouse gas emission, some countries have started using RE sources in the off-shore areas ( Robertson et al., 2020 ). The exploitation of the RE sources was firstly started in a few countries, including Japan, Norway, and the UK, by conducting Government-sponsored programs aiming for the advancement in technology ( Hayward and Osman, 2011b ). ...
The facts are that increasing energy demand, depletion of fossil fuel, and greenhouse gas emissions have increased the world's interest in renewable energy. Out of all RE options, Wave Energy (WE) is the least harnessed one despite the availability of WE Resource (WERs) in many countries and with the potential to cover a significant proportion of the world's energy needs. Australia, mainly in the southern part of the country, has plenty of this resource. Although recently, the Australian Government has started to focus on WERs as a Renewable Energy Source (RES) to cope with the energy crisis, research suggests that the country's progress in the WE generation to meet the energy demand is well below the potential generation capacity. However, insufficient research and studies address the issues and technologies in detail. This study examines the viability of further developing WE as a renewable energy source in Australia by evaluating the current constraints and challenges to achieving a satisfactory level of WE generation in the country. As a result, this study emphasizes the trustworthiness of WE in terms of several criteria. The availability of WERs within Australia and the status of producing WE are reviewed in this study. It also highlighted certain Australian technologies and devices that are now being tested or deployed in real-time. Moreover, this review is expanded by comparing the key developers in the WE sector to Australia to uncover some of the contributing elements in other countries that may have contributed to the growth of the WE generation in other nations. Finally, some of the barriers identified are lack of high-resolution data and social & environmental challenges. Some recommendations are given in the latter part of the review to accelerate WE production in Australia.
... As one of the main renewable energy resources, wave energy is expected to play an increasingly important role in the energy mix in the future [1,2]. In order to reduce the cost of wave power, a lot of research efforts have been spent on the modeling, simulations, and predictions of ocean waves. ...
Phase-resolved wave prediction is of vital importance for the real-time control of wave energy converters. In this paper, a novel wave prediction method is proposed, which, to the authors’ knowledge, achieves the real-time nonlinear wave prediction with quantified uncertainty (including both aleatory and model uncertainties) for the first time. Moreover, the proposed method achieves the prediction of the predictable zone without assuming linear sea states, while all previous works on predictable zone determination were based on linear wave theory (which produces overly conservative estimations). The proposed method is developed based on the Bayesian machine learning approach, which can take advantage of machine learning model’s ability in tackling complex nonlinear problems, while taking various forms of uncertainties into account via the Bayesian framework. A set of wave tank experiments are carried out for evaluation of the method. The results show that the wave elevations at the location of interest are predicted accurately based on the measurements at sensor location, and the prediction uncertainty and its variations across the time horizon are well captured. The comparison with other wave prediction methods shows that the proposed method outperforms them in terms of both prediction accuracy and the length of the predictable zone. Particularly, for short-term wave forecasting, the prediction error by the proposed method is as much as 55.4% and 11.7% lower than the linear wave theory and deterministic machine learning approaches, and the predictable zone is expanded by the proposed method by as much as 74.6%.
... As the global warming threat continues to increase, the energy mix needs to be more dominated by renewable energies (MacKay, 2009;Robertson et al., 2020); hence investing in all types of renewables is urgent (Kenny et al., 2010). In this context, and despite its potential (Gunn and Stock-Williams, 2012), wave renewable energy has received relatively little attention, including in the assessment of the transfer to a complete renewable energy mix by 2050 (Zappa et al., 2019) and even when focusing on blue energy solutions (Quero García et al., 2020). ...
< Public version is the Chapter 3 of my Australian PhD - upon enquiry I may share the published-article version > Abstract: In the struggle against increasing global warming, wave renewable energy could help progress to the increasingly necessary renewable-based energy-mix. Wave energy has many applications, one of which involves its capture and conversion into usable energy. To date, there has been no agreement in the scientific community with respect to a single wave energy converter design, and given the numerous concepts involved, many approaches have been developed to investigate the performance of these different devices. This work summarises these approaches in addition to completing and extending them regarding wave spectrum, wave direction, generator capacity limitations, and use of the Froude similarity law for wave energy converter scaling. Ultimately, this study aims to improve the selection process of the most appropriate converter configuration for a given resource (i.e. wave distribution climate). The main results showed that neglecting the wave direction can lead to a 10 % energy production overestimation when the method is applied to the Wavepiston device. Furthermore, for Weptos and Wavepiston wave energy converters, different standard wave spectra were found to estimate the energy production with less than 8 % difference, below the 16.5 % estimated in previous studies. Additionally, the Reverse Froude Law method is introduced to help assess the applicability of the Froude similarity law for converter configuration scaling. Finally, a threshold in the decrease of generator capacity is determined such that, despite limiting the device power production potential, annual energy production remained almost as high as without generator limitations for an approximately 40 % capacity factor increase.
... Most wave renewables are under research and development [6,7]. This is partially because the Levelised Cost of Energy (LCoE) [8], key metric to compare renewables [9], is difficult to estimate for waves. Indeed, there are many directions for its optimisation [8,10], and when estimated, wave energy's LCoE is often higher than other renewables [11]. ...
< Public version is the Chapter 4 of my Australian PhD - upon enquiry I may share the published-article version > Abstract: Renewable energies are mostly compared using the Levelised Cost of Energy (LCoE). Two major components of LCoE are of interest in this study, the others being still experimental: the Annual Energy Production (AEP) and the Capital Expenditure (CapEx). Since many Wave Energy Converters (WECs), including Wavepiston, are wave direction-dependent, this research investigates the wave direction impact on the relationship between the site-configurations (site characteristics and wave climates), WEC-configurations and power, alongside AEP and CapEx. Wave climate and WEC power are expressed in 3-dimension by adding the wave direction to the common 2-dimensional space of wave height and period. Wavepiston's WEF costs are calculated using the CapEx method. Assessing the relationship between the diverse sources of AEP/CapEx variations, enabled the development of the Cost-AEP Threshold Criterion (CAEPTC) to determine the threshold where an increase in AEP becomes negligible compared to CapEx increase. CAEPTC is perhaps a better alternative to LCoE for enhanced WEC/site-configuration pairing. Based on this Criterion and the limited dataset (a challenge to most wave companies), it was apparent that the best WEC/site-configuration pairs came from configurations with the highest yearly energy production, which is not necessarily the most expensive, and for sites with lower wave energy.
... LCOE can be obtained using Eq. (23) [34,35]: ...
The application of hybrid renewable energy systems (HRES) has been gaining ground in the recent years due to low-carbon policies of nations and increasing energy demand. However, marine energy sources such as waves have remained untapped notwithstanding their significant potential. This research examines the feasibility of a hybrid wave-photovoltaic (PV) system in three ports of Iran namely Bandare Anzali, Bandare Torkaman and Noshahr on the shores of Caspian Sea using MATLAB/Simulink. Oscillating water column (OWC) converters are deployed to harvest the wave energy. The findings indicated that the maximum energy production occurs in May, while the minimum is in November for all the locations under study. The annual energy generation reaches 11607.4 kWh, 13419.2 kWh and 11885.6 kWh in Anzali, Torkaman and Noshahr, respectively. The levelised cost of electricity (LCOE) for Anzali, Torkaman and Noshahr was found to be 5.59 /kWh and 5.46 $/kWh, respectively, which shows that Torkaman is the best place for the installation of the hybrid system. Considering the economic conditions in Iran, the system is not economically viable. It is, however, anticipated that with the elimination of energy subsidies in the near future, these systems can be feasible.
... It is predicted to play a more significant role in the energy mix in the coming years (Du et al. 2014). Solar energy installation reduces diesel consumption by 12% and yields $6844/kW (Robertson et al. 2020). It determined that the return on solar energy use is $177.41 ...
The impact of renewable energy on environmental sustainability has become much more critical in the era of globalization. Therefore, this study examines the long-run relationships between solar energy consumption, coal energy consumption, financial globalization, economic growth, and CO 2 emissions for 26 countries from 2000-2019. We preferred the common correlated effects mean group (CCEMG) method, which considers the cross-section dependence and slope homogeneity observed in the panel. According to CCEMG estimates, solar energy consumption has a negative and significant effect on the level of carbon emissions. Accordingly, a 1% increase in solar energy causes a 0.0106671% reduction in CO 2 emissions. On the other hand, a 1% increase in fossil energy consumption causes a rise of 0.2403829% in CO 2 emissions. Furthermore, the empirical results of the causality test showed a bidirectional causality between solar energy consumption and CO 2 emissions. As a result, this study reveals the importance of solar energy in reducing CO 2 emissions.
This study critically
examines the LCOE metric used for checking the feasibility of electricity generation technologies for 20 to
40 years. Levelized electricity cost of power generation technologies will decrease if we move to 100%
renewable energy adoption. Following the introduction, we discussed assumptions made for estimation,
parameters involved in the metric, and the cost components ignored by this metric. Most studies
considered producer cost for comparing the electricity generation technologies ignoring the additional
consumer and external costs with societal implications, which is inadequate for decision and policy-
making.
Wave energy resources have high, yet largely untapped potential as candidate generation technology. In this paper, we perform a data-driven analysis to characterize the impact of wave energy integration on bulk-scale power systems and market operations. Through data-driven sensitivity studies centered on an optimization-based production cost modeling formulation, our work characterizes the inflection point beyond which wave integration starts impacting power system operations, considering present day transmission infrastructure. Furthermore, our analysis also considers the joint effects of wave energy integration and system-wide transmission expansion. Finally, potential resilience scenarios such as wildfire-driven transmission contingencies and heat wave events are investigated, whereby the contributions of grid-integrated wave energy in alleviating the effects of the resilience events are analyzed. As our demonstration test bed, we consider a reduced-order network topology for the U.S. Western Interconnection with wave energy generation integrated at carefully selected sites across the coastal areas of Washington, Oregon, and northern California. Our results indicate that over a representative year of operations, wave energy integration systematically reduces locational marginal prices (LMPs) of energy and price volatility, especially during periods of high wave resource availability (winter months for the U.S. west coast). Average, maximum, and minimum of hourly LMPs over a typical year of operation was reduced by 2.95, 51.28, and 1.13 $/MWh respectively (over a baseline scenario with no wave energy integration), when the selected network model had a total of 5000 MW wave power installed capacity during the representative year of study. The effects of wave energy integration can remain localized with existing transmission infrastructure (identified to be most pronounced in the Pacific Northwest region in the example we studied). However, with concurrent transmission expansion, the impacts of wave energy integration are likely to have a higher geographical spread. Our results also indicate that wave energy may be able to assist power system operations during resilience events such as major transmission contingencies and heat wave events, although such benefits might be dependent on factors such as proximity of affected area to wave resources, availability of adequate resource potential and adequate transmission capacity.
This work aimed to test the feasibility, both experimentally and numerically, of a novel concept for a robust Wave Energy Converter (WEC) operating in the near-shore region. The converter uses a series of non-return valves, constrained by a tapered pipe, where the incoming wave builds up pressure in each compartment and finally drives a turbine onshore with the pressurised water. The device is aimed at remote communities, to gain energy security and reduce dependence on imports. The device facilitates local engagement, and it is intended that local people are trained to perform most maintenance tasks using low cost, readily available, parts. This work assessed the feasibility of the WEC through physical testing, the results of which were compared to initial numerical models. The device was shown to capture energy and, through a case study of Ushant Island off the coast of France, was shown to have the potential to become part of the future energy mix for remote communities.
Yükselen Ekonomiler için en önemli enerji kaynağı ya yenilenebilir enerji ya da enerjinin tasarruflu, verimli ve etkin kullanılmasıdır. Bu çalışma da 23 Yükselen Ekonomi için 1990-2018 döneminde enerji etkinliğini açıklayıcı talep yanlı faktörler araştırılmıştır. Model tahmini için Ortak İlişkili Etkiler Ortalama Grup (CCEMG) ile Genişletilmiş Ortalama Grup (AMG) panel tahmincileri kullanılmıştır. Bulgular genel olarak endüstriyel ve hizmetler üretimi, ithalat, doğrudan yabancı sermaye yatırımı, sabit sermaye yatırımı, dış açıklık oranı, ihracat ve ithalat artışları enerji etkinliğini olumlu etkilerken nüfus, karbondioksit emisyonu, petrol ve kömür fiyat artışları ise olumsuz etkilemektedir. Yükselen Ekonomiler ‘de rekabetçi üretim ve dış ticaret artışlarının enerji etkinliğini artırdığı bulunmuştur.
Çeşitli ihtiyaçlardan dolayı enerjiye olan talep sürekli artış içerisindedir. Özellikle Sanayi Devrimi ile birlikte bu artış hızının yükseldiği görülmektedir. Küreselleşme süreci ile birlikte bilgi-iletişim sektörünün gelişmesi ve teknolojik yenilikler enerjinin değerini geçmişe göre kıyaslanamayacak ölçüde artırmıştır. Enerji ihtiyacında meydana gelen bu artışlar enerji ithalatçısı ülkelerde ciddi sorunlar meydana getirebilmektedir. Bu çalışmada enerji ithalatçısı gelişmekte olan ekonomilerde yenilenemez enerji, yenilenebilir enerji, sanayileşme, enerji fiyatı ve kentleşmenin enerji yoğunluğu üzerindeki kısa ve uzun dönemli etkileri araştırılmaktadır. 1990-2018 döneminde 13 enerji ithalatçısı gelişmekte olan piyasa ekonomisinden oluşan bir panel veri seti oluşturularak, PMG, MG ve DFE yöntemleri ile ampirik tahminler yapılmaktadır. Diğer yandan hem iktisadi hem de ampirik sonuçların karşılaştırılabilmesi ve tutarlılık açısından DOLS ve FMOLS yömtemlerindende yararlanılmıştır. Ampirik sonuçlar uzun dönemde yenilenemez enerji kullanımı, yenilenebilir enerji kullanımı, sanayileşme, enerji fiyatı ve kentleşmenin enerji ithalatçısı gelişmekte olan ekonomilerde enerji yoğunluğunu önemli ölçüde etkilediğini ortaya koymuştur. Uzun ve kısa dönemde değişkenlerin dinamikleri açısından farklı bulgulara rastlanmıştır. Bu durum enerji ithalatçısı gelişmekte olan ekonomilerde değişen yenilenebilir enerji kullanımı, enerji fiyatı ve enerji alanında değişik teknolojik altyapıya bağlı kentleşme ile açıklanmaktadır. Uzun dönemde ilgili ülke grubunda enerji yoğunluğunu en çok artıran yenilenemez enerji kullanımı iken en çok azaltan etkenin ise sanayileşme olduğu bulgusuna ulaşılmıştır. Diğer yandan yenilenebilir enerji kullanımı, enerji fiyatı ve kentleşmenin enerji yoğunluğunu azalttığı sonucuna ulaşılmıştır.
Canada produces most of its electricity using renewables. However, in remote communities that are not connected to Southern Canada's main grid, the quasi-totality of microgrids rely on fossil fuels to ensure electricity supply. How much would it cost to decarbonize all of these microgrids? This paper uses a cost-based approach paired with a binary integer optimization model to find the least costly decarbonization solution for each off-grid settlement from now until 2050. By using wind speed and solar irradiance data together with future generation and storage cost estimates, our model determines whether solar or wind is more appropriate for a settlement and at which period it is best to undergo a transition from fossil fuel generation to renewables. Our results show that the cost of decarbonizing Canada's remote microgrids is not prohibitive and which technology and implementation period are cheapest for each settlement. We find that in 2020 wind turbines would be the cheapest option for most settlements, whereas in 2050 solar panels would be the cheapest option for most settlements. Settlements that currently use diesel of heavy fuel to produce electricity should consider undergoing decarbonization as soon as possible, while those that use natural gas could wait until production and storage technologies become cheaper. Larger settlements and fly-in communities could also be prioritized.
Using wave energy to supply the electrical demand of the coastal population is an exciting idea. In recent years, many wave energy converters (WEC) have been invented, researched, and used in different parts of the world. These WECs can be used alone or in a hybrid system with other renewable resources. Also, they can be used stand-alone or grid-connected to generate electricity. Iran has access to the sea from the north and south. Using wave energy to provide power can be a good solution for energy production. This study investigates the application of a point absorber WEC named CETO to supply electricity for a 300 population on the Coasts of the Caspian Sea, Persian Gulf, and Oman sea. Waves scatter diagram for three locations calculated based on the data collected by the Iranian National Center of Ocean Data. According to these diagrams, the average wave height and period on the Konarak coast in the Oman Sea were 69 cm and 5.4 s, respectively, and Konarak had the best wave condition between the desired location in terms of wave energy potential. Also, the Cost of Energy (COE) and Net Present Cost (NPC) for three areas calculated, and the lowest amount of COE and NPC occurred in Konarak. The COE range at Konarak was between 0.523 and 0.991 $/kWh for different WEC numbers. The best performance in terms of power generation and emissions reduction also occurred in Konarak; and the output power of each CETO unit was 23.01 kW, and emissions and related penalties reduced by about 24 %. Also, the effect of load change and grid extension cost on financial results sensitively analyzed, and the results presented. The obtained financial results compared with the results of some similar WECs and it was found that the obtained results differed very little from the results of other research, and were within their range.
Ocean energy plays essential roles in reducing carbon footprint and transforming towards carbon neutrality, with cleaner power production, whereas the vertical cascade ocean energy systems with spatiotemporal power supply characteristics might lead to fluctuated power frequency, disruptive disturbance and grid shock. Hybrid renewable energy dispatch, coordinated demand-side management, and electrical energy storages for grid ancillary services provision with different response time-durations are effective solutions to integrate ocean energy with stable and grid-friendly operation. This study is to review advanced ocean energy converters with thermodynamic, hydrodynamic, aerodynamic, and mechanical principles. Power supply characteristics from multi-diversified ocean energy resources are analysed, with intermittency, fluctuation, and spatiotemporal uneven distribution. Hybrid ocean energy storages with synergies are reviewed to overcome the intermittency and provide grid ancillary services, including pumped hydroelectric energy storage, ocean compressed air energy storage, and ocean hydrogen-based storage in different response time durations. Applications of diversified ocean energy systems for coastal residential communities are reviewed, with energy management and controls, collaboration on multi-carrier energy networks. Furthermore, application of artificial intelligence is reviewed for sustainable and smart ocean energy systems. Results indicated that, effective strategies for stable and grid-friendly operations mainly include complementary hybrid renewable system integrations, synergies on hybrid thermal/electrical storages, and collaboration on multi-carrier energy networks. Furthermore, depending on the geographical location, flexible on-shore and off-shore installation of transformers can provide large-scale ocean energy system integrations for long-distance transmission, with low transmission losses, low resistive losses, and simple system configuration. Research results can provide a heuristic overview on ocean energy integration in smart energy systems, providing alternatives for solar and wind energy resources and paving path for the carbon-neutrality transition.
Assessing wave energy is of great importance to estimate the wave energy potential and site selection of wave energy converters. This paper aims to present the distributions of wave energy and long-term wave trend along the Chinese coastline. By using the high-accuracy wave data in ERA5 reanalysis for the 42-year period in 1979–2020, the spatiotemporal distributions of wave variations estimated by Theil-Sen Estimations and mean wave energy resources assessed by the implicit calculation equation are presented. Generally, annually mean wave heights increase in Yellow sea, East China Sea and South China Sea and decrease in Bohai sea. The wave energy assessment shows the great energy potential with annually mean wave energy density of major 6–12 kW/m. There is near Taiwan island and the northern parts of South China Sea that of higher energy density. The seasonal analysis reveals that winter and fall are more energetic with higher values around 20 kW/m. The wave power production in the selected locations was evaluated and provided based on the distribution of various wave states showing the East China Sea and South China Sea are the most suitable sea area for wave energy development.
< Public version is the Chapter 7 of my Australian PhD careful here important updates were made afterwards for the published-article revisions, so please prefer to enquire that article so I may share its fully updated published-article version >
Abstract: With a world needing to progress to a more renewable-based energy mix, wave renewable is indispensable to achieve this goal. Studies showed that it is necessary to cartography wave energy converter and location pairs as varying wave climates require different devices. However, there is not one but many designs of the converters. Hence, pre-matching converter classes with wave climates would enable such computational-demanding global cartography. Then, devices would be matched to these classes to find where they suit most. Power production potentials display features to be naturally pre-classified: (1) presence of a plateau of same maximal value, and (2) associated capture width and possible linear reduction to a 1-dimensional curve; and different power-representations are considered. Then, the principal component analyses are employed to determine the new power production potential classification. This method enables to cluster into a simple 3-dimensional space distributions of data characterised by many dimensions. After calculating the Euclidian distance between the projected data to determine the clusters, different technics are assessed to obtain the representative classes. Results highlighted the non-correlation between previous classifications and the power production potential. The 46 considered power production potentials formed 16 classes. Finally, guidelines are provided to use this new classification.
In multi-source-based energy systems, the ultimate target of optimal operation of the generation units is to create an efficient power system with cleaner production. In this paper, a novel coordinated operation strategy optimizing the commitment of hydro, thermal and wind generation units is proposed. The strategy consists of two hierarchical optimization goals. In the primary goal, utilization of wind and hydro energy units is optimized, and the objective functions involve maximizing hydro energy utilization and minimizing wind curtailment. In the secondary goal, coal costs and carbon emissions are minimized after meeting the utilization goal. The overall execution of the strategy is governed by three power production decisions including peak-load shaving, valley-load filling and generation. The first two decisions suppress the fluctuation in wind power while the generation decision makes full use of the hydro units to replace the working thermal units. The presented operation strategy is applied to an improved IEEE 118-node power system. The optimization ensures the highest utilization of wind energy while coping with the day-ahead wind power forecasting error. Moreover, a particle swarm optimization method is applied to optimize the coal costs and carbon emissions. The presented results demonstrate the capability of the proposed strategy to configure the operation of the multi-source-based energy system with high efficiency and low emissions. Finally, several recommendations to amend the existing management of multi-source-based energy systems are presented.
This paper presents a thorough review of 75 modelling tools currently used for analysing energy and electricity systems. Increased activity within model development in recent years has led to several new models and modelling capabilities, partly motivated by the need to better represent the integration of variable renewables. The purpose of this paper is to give an updated overview of currently available modelling tools, their capabilities and to serve as an aid for modellers in their process of identifying and choosing an appropriate model. A broad spectrum of modelling tools, ranging from small-scale power system analysis tools to global long-term energy models, has been assessed. Key information regarding the general logic, spatiotemporal resolution as well as the technological and economic features of the models is presented in three comprehensive tables. This information has been validated and updated by model developers or affiliated contact persons, and is state-of-the-art as of the submission date. With the available suite of modelling tools, most challenges of today's electricity system can be assessed. For a future with an increasing share of variable renewables and increasing electrification of the energy system, there are some challenges such as how to represent short-term variability in long-term studies, incorporate the effect of climate change and ensure openness and transparency in modelling studies.
Wave energy resources are intermittent and variable over both spatial and temporal scales. This is of concern when considering the supply of power to the electricity grid. This paper investigates whether deploying arrays of devices across multiple spatially separated sites can reduce intermittency of supply and step changes in generated power, thereby smoothing the contribution of wave energy to power supply. The primary focus is on the southwest UK; SWAN wave model hindcast data are analysed to assess the correlation of the resource across multiple sites and the variability of power levels with wave directionality. Power matrices are used to calculate step changes in the generated power with increasing numbers of sites. This is extended to national and European scales using ECMWF hindcast data to analyse the impacts of generating power at multiple sites over wider areas. Results show that at all scales the step change in generated power and the percentage of time with zero generation decreases with increasing numbers of sites before plateauing. This has positive implications for performance of electricity grids with high levels of renewable penetration.
Wave-energy converters of the point-absorbing type (i.e., having small extension compared with the wavelength) are promising for achieving cost reductions and design improvements because of a high power-to-volume ratio and better possibilities for mass production of components and devices as compared with larger converter units. However, their frequency response tends to be narrow banded, which means that the performance in real seas (irregular waves) will be poor unless their motion is actively controlled. Only then the invested equipment can be fully exploited, bringing down the overall energy cost. In this work various control methods for point-absorbing devices are reviewed, and a representative selection of methods is investigated by numerical simulation in irregular waves, based on an idealized example of a heaving semisubmerged sphere. Methods include velocity-proportional control, approximate complex conjugated control, approximate optimal velocity tracking, phase control by latching and clutching, and model-predictive control, all assuming a wave pressure measurement as the only external input to the controller. The methods are applied for a single-degree-of-freedom heaving buoy. Suggestions are given on how to implement the controllers, including how to tune control parameters and handle amplitude constraints. Based on simulation results, comparisons are made on absorbed power, reactive power flow, peak-to-average power ratios, and implementation complexity. Identified strengths and weaknesses of each method are highlighted and explored. It is found that overall improvements in average absorbed power of about 100-330% are achieved for the investigated controllers as compared with a control strategy with velocity-proportional machinery force. One interesting finding is the low peak-to-average ratios resulting from clutching control for wave periods about 1.5 times the resonance period and above.
The main objective of this paper is to establish an economic modelling of wave energy through a Geographical Information System (GIS). Furthermore, this method has been tested for the particular case of the Portuguese coast. It determines the best sea areas to install wave energy converters in this region, using spatial analysis of the Levelized Cost of Energy (LCOE). Several economic parameters, as capital or O&M costs, have been considered. In addition, a sensitivity analysis has been performed by varying the discount rate in three different scenarios. Several types of physical restrictions have been taken into account: bathymetry, submarine electrical cables, seabed geology, environmental conditions, protected areas in terms of heritage, navigation areas, seismic fault lines, etc. Spatial operations have been carried out to complete the procedure, using Model Builder of GIS software. Results indicate the most suitable areas in economic terms in Portugal to install wave energy devices.
This paper presents results from an investigation of global wave energy
resources derived from analysis of wave climate predictions generated
by the WAVEWATCH-III (NWW3) wind-wave model (Tolman, 2002)
spanning the 10 year period from 1997 to 2006. The methodology that
was followed to obtain these new results is described in detail. The
spatial and temporal variations of the global wave energy resource are
presented and described. Several parameters to describe and quantify
the temporal variation of wave energy resources are presented and
discussed. The new results are also validated through comparisons with
energy estimates from buoy data and previous studies.
The year 2008 saw the emergence of the first generation of commercial ocean energy devices, with the first units being installed in the UK and Portugal. This means that there are currently four ways of obtaining energy from sea areas, namely from wind, tides, waves and thermal differences between deep and shallow sea water. This paper focuses on current developments in offshore wind and ocean energy, high-lighting the efforts currently underway in a variety of countries, principally some of the projects typically less talked about such as those in the Asian-Pacific countries. Finally, the growth potential of these industries will be assessed, using as a basis the historical trends in the offshore wind industry and extrapolating it to compute future growth potentials. Using this as a basis, the percentage of the world's electricity that could be produced from ocean based devices is estimated to be around 7% by 2050, and this would employ a significant amount of people by this time, possibly around 1 million, mostly in the maintenance of existing installations. The paper will also evaluate the likely cost of production per kW of ocean energy technologies using a variety of learning factors.
Ocean waves are a huge, largely untapped energy resource, and the potential for extracting energy from waves is considerable. Research in this area is driven by the need to meet renewable energy targets, but is relatively immature compared to other renewable energy technologies. This review introduces the general status of wave energy and evaluates the device types that represent current wave energy converter (WEC) technology, particularly focusing on work being undertaken within the United Kingdom. The possible power take-off systems are identified, followed by a consideration of some of the control strategies to enhance the efficiency of point absorber-type WECs. There is a lack of convergence on the best method of extracting energy from the waves and, although previous innovation has generally focused on the concept and design of the primary interface, questions arise concerning how best to optimize the powertrain. This article concludes with some suggestions of future developments.
Many hope that ocean waves will be a source for clean, safe, reliable and affordable energy, yet wave energy conversion facilities may affect marine ecosystems through a variety of mechanisms, including competition with other human uses. We developed a decision-support tool to assist siting wave energy facilities, which allows the user to balance the need for profitability of the facilities with the need to minimize conflicts with other ocean uses. Our wave energy model quantifies harvestable wave energy and evaluates the net present value (NPV) of a wave energy facility based on a capital investment analysis. The model has a flexible framework and can be easily applied to wave energy projects at local, regional, and global scales. We applied the model and compatibility analysis on the west coast of Vancouver Island, British Columbia, Canada to provide information for ongoing marine spatial planning, including potential wave energy projects. In particular, we conducted a spatial overlap analysis with a variety of existing uses and ecological characteristics, and a quantitative compatibility analysis with commercial fisheries data. We found that wave power and harvestable wave energy gradually increase offshore as wave conditions intensify. However, areas with high economic potential for wave energy facilities were closer to cable landing points because of the cost of bringing energy ashore and thus in nearshore areas that support a number of different human uses. We show that the maximum combined economic benefit from wave energy and other uses is likely to be realized if wave energy facilities are sited in areas that maximize wave energy NPV and minimize conflict with existing ocean uses. Our tools will help decision-makers explore alternative locations for wave energy facilities by mapping expected wave energy NPV and helping to identify sites that provide maximal returns yet avoid spatial competition with existing ocean uses.
Energy is a vital input for social and economic development of any nation. With increasing agricultural and industrial activities in the country, the demand for energy is also increasing. Formulation of an energy model will help in the proper allocation of widely available renewable energy sources such as solar, wind, bioenergy and small hydropower in meeting the future energy demand in India. During the last decade several new concepts of energy planning and management such as decentralized planning, energy conservation through improved technologies, waste recycling, integrated energy planning, introduction of renewable energy sources and energy forecasting have emerged. In this paper an attempt has been made to understand and review the various emerging issues related to the energy modeling. The different types of models such as energy planning models, energy supply–demand models, forecasting models, renewable energy models, emission reduction models, optimization models have been reviewed and presented. Also, models based on neural network and fuzzy theory have been reviewed and discussed. The review paper on energy modeling will help the energy planners, researchers and policy makers widely.
This paper includes a review of the different computer tools that can be used to analyse the integration of renewable energy. Initially 68 tools were considered, but 37 were included in the final analysis which was carried out in collaboration with the tool developers or recommended points of contact. The results in this paper provide the information necessary to identify a suitable energy tool for analysing the integration of renewable energy into various energy-systems under different objectives. It is evident from this paper that there is no energy tool that addresses all issues related to integrating renewable energy, but instead the ‘ideal’ energy tool is highly dependent on the specific objectives that must be fulfilled. The typical applications for the 37 tools reviewed (from analysing single-building systems to national energy-systems), combined with numerous other factors such as the energy-sectors considered, technologies accounted for, time parameters used, tool availability, and previous studies, will alter the perception of the ‘ideal’ energy tool. In conclusion, this paper provides the information necessary to direct the decision-maker towards a suitable energy tool for an analysis that must be completed.
Sea wave energy is being increasingly regarded in many countries as a major and promising resource. The paper deals with the development of wave energy utilization since the 1970s. Several topics are addressed: the characterization of the wave energy resource; theoretical background, with especial relevance to hydrodynamics of wave energy absorption and control; how a large range of devices kept being proposed and studied, and how such devices can be organized into classes; the conception, design, model-testing, construction and deployment into real sea of prototypes; and the development of specific equipment (air and water turbines, high-pressure hydraulics, linear electrical generators) and mooring systems.
Energy resource classification systems are useful assessment tools that support energy planning and project development, e.g., siting and feasibility studies. They typically establish standard classes of power, a measure of the opportunity for energy resource capture. In this study, we develop wave energy resource classification systems for the US based on wave power (J, kW/m) and its distribution with peak period (Tp,s). These metrics are calculated for 70,386 sites from partitioned bulk wave parameters generated from a validated 30-year WaveWatch III model hindcast. As the operating resonant period bandwidth of a wave energy converter (WEC) technology is an important design characteristic, the dominant period band containing the largest energy content is identified among three peak period band classes. These classification systems, comprised of four power classes and three peak period band classes, are based on the total wave power or the partitioned wave power in the dominant peak period band. They discriminate distinct trends in wave energy resource among five regions within the US, and provide useful information for energy planners, project developers, and technology designers. They also establish a framework for investigating the feasibility of a compatible wave climate (design load) conditions and WEC technology classification system to reduce design and manufacturing costs.
A novel stochastic model has been developed which allows for the prediction of Wave Energy Converters (WECs) array power time series, based solely on knowledge of an individual WEC power time series. The model is applicable for arrays of independent WECs.
The power from an array of WECs was simulated by deploying 50 individual WECs in a numerical testbed and aggregating the individual power productions. 51 differing WEC array scenarios were completed using four different WEC architectures, differing separation distances, wave directional spreading constants and device degrees of freedom. These allowed investigation into the normalized standard deviation and the frequency content relationships between the power from an individual WEC and an array of WECs. These properties were used to determine if the power from WECs within the arrays was independent.
WECs are found to be independent if the separation distance is greater than 212 m. If small differences in the frequency content of the power is allowable, separation distances of 98 m with directional spreading constants (s) of 15 are allowable. WEC architecture and movement degrees of freedom were shown not to affect independence.
Energy resources are an irreplaceable life resource in the current world, with the use and management of these an important indicator of development. In parallel to the developing world economy, the increase in the use of energy resources is increasingly consuming existing fossil sources and also increasing the amount of greenhouse gas released into the atmosphere. As a result of resulting material and environmental concerns, renewable energy resources have begun to be used as alternative energy resources. These resources have advantages such as sustainability and environmental friendliness, in addition to having disadvantages such as higher investment costs and also system reliability is insufficient to provide for continuous demand for energy. To resolve these disadvantages, hybrid systems have been developed involving the use of more than one type of renewable energy resource and/or use with traditional energy resources and/or integration with storage systems. The use of these systems requires finding the solution to optimization problems including one or more objectives such as sizing the system to minimize energy costs, system management to balance the uncertainty of energy produced or reduction of greenhouse gas emissions. This article was prepared with the aim of investigating optimization techniques developed from past to present to solve this problem and especially to determine the efficacy of multi-objective optimization approaches.
This paper presents a study of large-scale wave energy integration in which transmission constraints are considered. The Vancouver Island electrical grid is considered and is modelled using PLEXOS® Integrated Energy Model software. The model incorporates the current transmission grid, the existing fleet of main generation stations and ten potential wave farm sites with a total generation capacity of 500 MW. The objectives are to investigate: 1) the potential contribution of wave power toward energy self-sufficiency, 2) the effects of transmission constraints on the viability of alternative wave farm sites, 3) the impacts of wave integration on the load profile. Findings suggest that wave energy integration can significantly reduce the energy dependency on neighbouring jurisdictions but the current grid infrastructure is not adequate to fully support 500 MW of wave power. In this regard, it is shown that potential wave power integration can significantly benefit from transmission expansion for particular pathways. Further, results show that wave integration leads to reductions in the share of energy supplied from other sources and that this reduction follows an annual pattern. This periodic trend is particularly important for a hydro-dominated (energy-limited) grid where water level in reservoirs is managed on monthly and yearly bases.
Global wave energy inventories have shown that the west coast of Canada possesses one of the most energetic wave climates in the world, with average annual wave energy transports of 40-50 kW/m occurring at the continental shelf. With this energetic climate, there is an opportunity to generate significant quantities of electricity from this renewable source through the use of wave energy conversion (WEC) technologies. To help evaluate the feasibility of deploying wave energy conversion technologies along the west coast of Vancouver Island, a detailed Simulating WAves Nearshore (SWAN) model was developed to assess the wave resource. The SWAN model hindcasted wave conditions along the west coast over the 2005-2012 period, at a 3 h time resolution. Detailed sensitivity studies within this report illustrate that the Fleet Numerical Meteorology and Oceanography Centre's (FNMOC) WaveWatch 3 results exhibited superior model performance when used as wave input boundary conditions. The corresponding Coupled Ocean Atmosphere Mesoscale Prediction System (COAMPS) wind fields were used as non-stationary wind forcing functions within the computational domain. Yearly and monthly mean variations of spectral and parametric wave characteristics for two reference locations were plotted to indicate both the spatial and temporal variability of the wave climate. The mean annual wave energy transport for Amphitrite Bank was calculated to be 34.5 kW/m, while the shallower second location featured 27.8 kW/m just 500 m from shore. Wave energy resources of this magnitude are not common globally and, as a consequence, signify that the west coast of Vancouver Island may be an excellent candidate location for future wave energy development.
In the present paper a hindcast system is applied to the analysis of the Atlantic European coast as a whole with specific nestings for sites of interest in each country. The areas included in this study were: Ireland west coast, UK South Western coast, France west coast, northern Spain and Canary Islands and Portugal's continental coast. Two contemporary spectral models were used: WaveWatch III for wave generation, covering almost the entire North Atlantic basin, which outputs are then used as boundary conditions for SWAN which simulates wave transformation in coastal areas. Wind fields were taken from the ERA Interim data base. Results are validated against buoy data. These validations allowed a reformulation, when needed, of the model's configurations in order to better tune its outcomes to the real data. Using the energy transport vectors given by SWAN, the wave power is afterwards calculated and an energy resource assessment is done for a period of several years.
Hybrid energy systems are being utilized for supplying electrical energy in urban, rural and remote areas to overcome the intermittence of solar and wind resources. A hybrid renewable energy system incorporates two or more electricity generation options based on renewable energy or fossil fuel unit. The techno-economic analysis of the hybrid system is essential for the efficient utilization of renewable energy resources. Due to multiple generation systems, hybrid system analysis, is quite complex and requires to be analyzed thoroughly. This requires software tools for the design, analysis, optimization, and economic viability of the systems. In this paper, 19 softwares with their main features and current status are presented. The softwares studied are HOMER, Hybrid2, RETScreen, iHOGA, INSEL, TRNSYS, iGRHYSO, HYBRIDS, RAPSIM, SOMES, SOLSTOR, HySim, HybSim, IPSYS, HySys, Dymola/Modelica, ARES, SOLSIM, and HYBRID DESIGNER. The research work related to hybrid systems carried out using these softwares at different locations worldwide is also reviewed. The main objective of the paper is to provide the current status of these softwares to provide basic insight for a researcher to identify and utilize suitable tool for research and development studies of hybrid systems. The capabilities of different softwares are also highlighted. The limitations, availability and areas of further research have also been identified.
In many remote areas, expensive fossil fuels such as diesel are used to meet local electricity demand. However, their environmental impact is significant. Consequently, some of these areas have started to use hybrid systems that combine renewable energy sources and fossil fuel generation, such as wind-diesel systems, although wind is not feasible in some remote locations and fossil fuels remain the only resource in these areas. Fortunately, offshore renewable energy sources are available in many remote areas close to the ocean. In order to understand the feasibility of using offshore renewables in remote oceanic areas, we recently conducted a systematic study by developing an integrated model. This model includes a supply module, demand module, environmental impact module, and integrating module. Using this model, we mainly study the reduction in emissions resulting from offshore renewable energy penetration in local energy systems. In this article, we present this integrated model and an example study of tidal energy in the Southern Alaska community of Elfin Cove, which relies on diesel fuel for all of its electricity requirements. With 56 kW of tidal power penetrating the energy system, we found that almost 12,000 gallons of diesel fuel are displaced per year. This results in an annual emissions reduction of almost 244,000 lb CO2 and about 1400 lb CO, as well as considerable reductions of PM-10, NOx, and SOx. The newly developed integrated model is expected to be used to analyze other aspects of tidal energy (and offshore renewable energy in general) in remote areas. For example, since the electricity demand in some remote areas varies significantly throughout the year, we recommend that tidal power should be used with a storage system.
Justifying continued development and large-scale deployment of Wave Energy Converters (WECs) requires quantification of the potential resource. Currently, estimates are available for individual countries or, at low accuracy, for global resource. Additionally, existing estimates do not provide insight into potential future markets, i.e. the location of the resource.Here, NOAA WaveWatch III data are analysed for a 6-year period to calculate wave energy potential. The global market is then quantified by calculating the energy flux across a line 30 nautical miles offshore. Results are presented by country, continent, hemisphere and for the globe.Confidence values are also presented in the form of 95% confidence intervals. These limits provide insight into the uncertainty associated with the length of dataset used and the variability of the resource. This enables direct comparison with other resource assessment studies, whether using numerical model or measured data. An extensive survey of previous global and regional resource estimates is also conducted, in order to compare both results and methods.Supplementing this, extractable resource is estimated by considering the deployment of an illustrative WEC (Pelamis P2). The global wave power resource is 2.11 ± 0.05 TW, of which 4.6% is extractable with the chosen WEC configuration.
In this work, we present a methodology for the assessment of the economic value of ocean wave energy schemes. Such an assessment is a necessary tool for supporting investment decisions in the development of wave farms and in the development of wave energy converter (WEC) technology. To overcome the lack of operational experience, the methodology presented includes detailed operational simulations which relate the operational costs and the availability of the plant for power production to the characteristics of the device, the location, and the maintenance strategy chosen. The methodology consists of firstly, a productivity and costs assessment which embodies the operational simulations and secondly, a financial calculator which employs discounted cash-flow techniques to produce selected economic indicators. A case study, consisting of one hundred WECs units deployed off the West Coast of Ireland, is presented to exemplify the use of the methodology. The paper also explores how the key inputs to the assessment affect the economic performance of the case study project via a sensitivity analysis.
Wave energy will certainly have a significant role to play in the deployment of renewable energy generation capacities. As with wind and solar, probabilistic forecasts of wave power over horizons of a few hours to a few days are required for power system operation as well as trading in electricity markets. A methodology for the probabilistic forecasting of the wave energy flux is introduced, based on a log-Normal assumption for the shape of predictive densities. It uses meteorological forecasts (from the European Centre for Medium-range Weather Forecasts - ECMWF) and local wave measurements as input. The parameters of the models involved are adaptively and recursively estimated. The methodology is evaluated for 13 locations around North-America over a period of 15 months. The issued probabilistic forecasts substantially outperform the various benchmarks considered, with improvements between 6% and 70% in terms of Continuous Rank Probability Score (CRPS), depending upon the test case and the lead time. It is finally shown that the log-Normal assumption can be seen as acceptable, even though it may be refined in the future. (c) 2011 Elsevier Ltd. All rights reserved.
Highly Integrated Community Energy Systems (ICES) greatly but not solely dependent on combined heat and power (CHP) sources are a viable approach for dealing effectively with the new set of global threats which Mankind is facing, such as Climate Change, Global Warming and Extreme Poverty. ICES are capable of delivering sustainable electricity, heat and cold to small communities and of working as grid-connected or islanded microgrids, adding technical, economical, environmental and social benefits to populations. The impacts of introducing ICES in current distribution networks can be analyzed at different scales due to the wide range of influence exerted not only at the local but also at regional and global levels. For these reasons, there is increased need for appropriate modeling of ICES for the vital purposes of planning and analysis of these systems. An overview on the available bottom-up tools for the optimization planning and analysis of ICES is done in this paper. The survey shows that DER-CAM can be considered an appropriate tool for the purpose of ICES design modeling due to the robust and flexible three-level optimization algorithm, hourly time step and other scale considerations but particularly due to the several successful applications with modeling microgrid systems. Additionally there is research experience on expanding the objective function for environmental concerns and also with EV battery storage interactions. Finally, GAMS DER-CAM's base language, is a widely known package for allowing changes to be made in model specifications simply and safely. In that sense, there is potential in exploring such tool for the design of ICES. Furthermore, it is found that MARKAL/TIMES, also a GAMS/CPLEX based tool, has scale flexibility which enables it for analyzing the long-term deployment of ICES in time. There is opportunity in this field for further work exploring the sustainability-sound modeling for optimal design of ICES and deployment scenario options evaluation, through long-term time horizons consideration.
The aim of this study is to estimate the mean annual power absorption of a selection of eight Wave Energy Converters (WECs) with different working principles. Based on these estimates a set of power performance measures that can be related to costs are derived. These are the absorbed energy per characteristic mass [kWh/kg], per characteristic surface area [MWh/m(2)], and per root mean square of Power Take Off (PTO) force [kWh/N]. The methodology relies on numerical modelling. For each device, a numerical Wave-to-Wire (W2W) model is built based on the equations of motion. Physical effects are modelled according to the state-of-the-art within hydrodynamic modelling practise. Then, the W2W models are used to calculate the power matrices of each device and the mean annual power absorption at five different representative wave sites along the European Coast, at which the mean level of wave power resource ranges between 15 and 88 kW per metre of wave front. Uncertainties are discussed and estimated for each device. Computed power matrices and results for the mean annual power absorption are assembled in a summary sheet per device. Comparisons of the selected devices show that, despite very different working principles and dimensions, power performance measures vary much less than the mean annual power absorption. With the chosen units, these measures are all shown to be of the order of 1.
In this article different scenarios are analysed with the objective of increasing the penetration of renewable energies in the energy system of S. Vicente Island in Cape Verde. An integrated approach is used to analyse the electricity and water supply systems. The H2RES model, a tool designed to simulate the integration of renewable sources and hydrogen in the energy systems of islands or other isolated locations, is applied. There is no other source of fresh water available to supply the population of S. Vicente, apart from desalinated seawater. The electricity supply system of this Island is based on fossil fuel and wind. S. Vicente has important wind resources that are not fully used because of its intermittent nature. The topography of this Island is relatively uniform, with the exception of Mont Verde, a 774Â m high mountain located in its centre, which could be suitable for pumped hydro storage. The present analysis incorporates the possibility of using pumped hydro as a storage technique to increase the penetration of renewable energy sources, using desalinated seawater. The results show that is possible to have more than 30% of yearly penetration of renewable energy sources in the electricity supply system, together with more than 50% of the water supplied to the population produced from wind electricity.
This paper shows how the complementarity format can be used in computable general equilibrium (CGE) modeling for a hybrid description of economy-wide production possibilities where energy sectors are represented by bottom-up activity analysis and the other production sectors are characterized by top-down regular functional forms typically belonging to the constant-elasticity-of-substitution (CES) family. The hybrid approach increases the credibility of CGE models in energy policy analysis because the possible substitution patterns in energy conversion can be based on `true' technology rather than restrictive functional forms.
This paper analyses the field performance of different off-grid generation technologies applied to the electrification of rural villages. Autonomous diesel generators are the most extended technology. It is a well known application, although it has also some disadvantages: fuel transportation and consumption costs, maintenance needs or environmental problems. In places where accessibility is difficult and costly, the use of local energy resources (basically renewable) constitutes a significant advantage. Due to the intermittent character of those resources, renewable generation systems are sometimes associated to diesel gen-sets in order to increase the reliability of supply of small and medium-size communities. A comparative analysis between diesel, hydro-diesel and photovoltaic-diesel technologies is presented in this article. It is based on data collected from systems installed in the rural area of the province of Jujuy, northwest of Argentina. The study covers from year 2001 to 2008, with a research universe of 16 locations supplied by thermal diesel generation (1 with a large-diesel system and other 15 with smaller ones), 5 locations with hydro-diesel and 7 with photovoltaic-diesel systems. The energy demand evolution of rural villages is also studied because of its influence on the system operation and sustainability.
Detailed temporal consideration has been a major challenge for energy systems models with typical time horizons of years and decades. This presents particular issues in investigating electricity generation, capacity and storage, whilst retaining broader trade-offs sectors, technology pathways and timing of investments. This paper reports on a methodology for temporal disaggregation in the widely applied energy service driven, technology rich, cost optimizing, linear programming MARKAL energy system model. A flexible time slicing feature is developed to enhance representation of diurnal and seasonal electricity demand curves through disaggregation of resource availability and energy service demands. In a first application of a temporal UK MARKAL model, a range of runs investigate the role of electricity storage at supply and demand sides. The results display considerably enhanced insights, notably on the role and preference of demand-side electricity storage over supply-side storage. On average, the system chooses about 7–10% of electricity demand as storage. On the supply side, hydrogen-based electricity storage is greatly preferred but stored-hydrogen is used in the transport sector rather than for power system balancing mechanism.
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