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-Load shifting and peak shaving under time-of-use rates

-Load shifting and peak shaving under time-of-use rates

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Microgrids are an increasingly common component of the evolving electricity grids with the potential to improve local reliability, reduce costs, and increase penetration rates for distributed renewable generation. The additional complexity of microgrids often leads to increased investment costs, creating a barrier for widespread adoption. These cos...

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... economic impact of this value stream can be particularly high in scenarios where utility TOU rates consist of both volumetric and power charges. Such tariffs are typically very strong incentives to enable both load leveling and peak shaving, as illustrated in Figure 1. In this case, an optimized load profile would theoretically be capped by a dynamic maximum demand level that follows the different time-ofuse periods established in the utility tariff. ...

Citations

... This approach in describing the analysis will additionally be utilised for the remaining two layers of the TL-BMC, environmental ( Figure 3) and social ( Figure 4). Most projects focusing on built environment materials have value propositions that span from delivering one-dimensional value to creating benefit from many streams, improving the projects' long-term economic resilience [7,8]. Furthermore, the majority of the generated monetary value provides more than one revenue source to balance costs [9]. ...
Conference Paper
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Addressing the growing need for sustainability, novel concrete solutions become increasingly popular for mitigating the negative environmental impacts found in cement production, such as high CO2 emissions output and raw materials overuse, providing conventional concrete products alternatives. The industry is lacking a common analytical framework for business models to clearly define sustainable concrete value streams present across economic, environmental, and social layers. Our research utilises the Triple-Layer Business Model Canvas (TL-BMC) to analyse a piloted sustainable concrete product (CIRCLE), describes its multi-layered value, and effectively provides the common framework for sustainable concrete business model adaptation. We conclude that the Triple-Layered Business Model Canvas (TL-BMC) is the most appropriate framework that enables the identification and establishment of successful business models focused on sustainable concrete.
... Isolated microgrids are small power networks that produce and manage their own electricity needs. Grid connectivity improves system dependability and allows electricity trading with other grids [11,12]. Hydrogen technology is currently preferred in microgrids to store electric power. ...
Article
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Microgrid optimization is one of the most promising solutions to power system issues and new city electrification. This paper presents a strategy for optimal power scheduling of a residential microgrid depending on renewable generating sources and hydrogen power. Five scenarios of the microgrid are introduced to show the effect of using biomass energy and a seawater electrolyzer on microgrid cost and CO2 emissions. Time of use demand response is applied to reshape the electric load demand and decrease the dependence on grid power. The obtained results from the multi-objective optimization verify that biomass has a significant role in minimizing the cost and CO2 emissions; the cost is decreased by 37.9% when comparing scenarios with and without biomass. Besides, the FC integration with seawater electrolyzer and tanks reduces the microgrid emissions by around 40%.
... Other added values of SMGs in terms of city governance cannot be expressed quantitatively. For example, the electric system resiliency cannot be accurately estimated [100]. ...
Article
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Smart MicroGrids (SMGs) can be seen as a promising option when it comes to addressing the urgent need for sustainable transition in electric systems from the current fossil fuel-based centralised system to a low-carbon, renewable-based decentralised system. Unlike previous studies that were restricted to a limited number of actors and only took a mono-disciplinary research approach, this current review adopts a multidisciplinary, socio-technical approach and addresses the factors that have been hindering the development of SMGs and considers how these barriers interact. This study contributes to the body of literature on the development of SMGs by mapping and discerning technical, regulatory, market, social and institutional barriers for different types of actors, including technology providers, consumers, Distributed Generation (DG) providers and system operators, based on information derived from laboratory reports, demonstration pilots, and academic journals. In addition, attention is paid to how these barriers interact based on real-life experimentation. A holistic picture of barriers and their interaction is presented as well as recommendations for future research.
... Smart Home (SH) is a residential electrical installation that applies the smart grid concept. The energy performance of a SH appliance can be monitored intrusively-Intrusive Load Monitoring (ILM) (Stadler et al., 2016;Dong et al., 2013)-or non-intrusively-Non-Intrusive Load Monitoring (NILM) (Xu & Milanović 2015), (Benzi et al., 2011). In the first, sensors are installed in each SH appliance, while NILM requires only a central monitoring device, thus allowing a lower infrastructure cost when compared to ILM. ...
Article
The identification of electrical/electronic loads is one of the Smart Grids (SGs) relevant problems. An accuracy of 100\(\%\) can be achieved in SGs with non-similar loads. However, to the best of the authors knowledge, this level of accuracy was not described in the literature, considering SGs with similar loads. Therefore, the development of an intelligent classification system of similar electrical/electronic loads is described in this paper, aiming at the achievement of 100% accuracy with minimum parameters of the neural classifiers. An experimental platform containing an arrangement with four high similar loads was implemented. In such arrangement, all possible combinations are realized, that is, from all loads turned on until all turned off, resulting in non-similar and very similar loads, as found in real scenarios. The electrical signals demanded by the connected load arrangements are acquired and submitted to two different neural networks. The first neural network is an Extreme Learning Machine (ELM) classifier, where a Particle Swarm Optimization (PSO) technique is applied to select the best ELM model, whereas the second network is a Convolutional Neural Network (CNN) classifier. The ELM-PSO system is based on pre-processed data because it uses information based on the spectrum amplitude of the demand signals (features), whereas the CNN system is based on the use of the raw data, thus requiring a greater processing capacity when compared to the ELM-PSO. The simulation results show that the proposed CNN based system provides success rates considerably higher than the proposed ELM-PSO system, i.e., \(100\%\) of accuracy with 381, 512 network parameters against \(85\%\) with 14, 989 parameters of the ELM-PSO-based system.
... Power quality, ancillary services, optimization and stability are some examples of these. In the economic sphere, the power flow, exported or imported, sold, bought or negotiated, will be determined by energy market prices, demand response with incentives, event-based programs, economic benefits, increased resiliency, among others [121]. In the social side, the power flow can be engaged in supporting participants of the microgrid or individuals in the distribution system that are in critical conditions, prioritizing its control to aide people or establishment in more vulnerable situations, such as hospitals in disaster circumstances, or with families with less resources. ...
Article
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Microgrids are relatively smaller but complete power systems. They incorporate the most innovative technologies in the energy sector, including distributed generation sources and power converters with modern control strategies. In the future smart grids, they will be an essential element in their architecture. Their potential to offer many economic, social and environmental services through advanced electrical techniques has led to a growing interest in the theme. Although the islanding condition is a very important feature of microgrids, only with the implementation of grid connection and seamless transition they will demonstrate their full capacity. However, there are still many questions surrounding these operation modes and this paper tries to answer part of them. To do that, several aspects in the field are approached. The history and late development of microgrids are revisited. The main concepts are presented. The islanded mode is revised, since it is intrinsically linked to the other working states of the microgrid. The requirements for the interconnection of microgrids to an external grid are discussed. The operation elements are also analyzed. A crucial part of the grid-connected microgrids and their seamless transfer conditions, the control methods found in the literature are extensively reviewed. The paper is concentrated in the analysis of control methods for AC microgrids and AC power systems, therefore, it does not enter in detail or investigates profoundly the topologies applied in the power electronics structures nor DC microgrids and DC power systems.
... In order to systematically and clearly summarize the characteristics of various modeling tools, Fig. 11 provides a comprehensive summary of the main benefits, limitations and applications of 10 typical modeling tools [172,240,242,243]. It includes: ①National Level: RETScreen, MRAKAL, LEAP, EnergyPLAN; ②Regional Level: DER-CAM, NEMS and CloudPSS; ③Users Level: HOMER, TRNSYS and iHOGA. ...
Article
With a rapid growth of Integrated Energy System (IES) in various scenarios, researches on IES have attracted extensive attention in the last few decades. Inspired by the ever-increasing studies about the IES, which focus on various energy scenarios but lack a systematic summarization, this paper aims to undertake a comprehensive review of the IES models, operation optimization methods, and model tools. Firstly, CiteSpace is used to visually analyze the cooperation and co-occurrence network of related articles in recent two decades, among which 1998 papers from WOS are selected for analyzing. Note that 243 papers highly related to IES are further investigated to systematically analyze and integrate the relevant work. On this basis, different definitions of IES around the world and 12 related research hotspots are summarized. Then, the IES modeling methods are creatively classified from eight aspects. Furthermore, from the perspective of operation optimization methods, three mainly optimal problems, including Economic Dispatch, Unit Commitment and Optimal Power Flow, are comprehensively analyzed. Besides, 22 energy model tools are discussed from the levels of National, Regional, and Users. Finally, seven advantages and three challenges are summarized, four key points are concluded, and six perspectives/recommendations are proposed for future research. In general, this paper is intended to offer an insightful guidance to prompt related researchers/engineers to broaden the horizons of their researches.
... The MGs are a promising technology for efficient and pollution-free power generation. They can be connected to the primary electricity grid or disconnected to operate in the ''island mode' Stadler et al., 2016). ...
Article
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Microgrid (MG) represents a promising opportunity for integrating renewable energy systems with the electric power grid. However, numerous complexities need to be addressed in the process. The electrical grid is complex, vulnerable, and centralized. Thus, the integration is challenging owing to the stochastic nature of renewable energy generation, which affects the possibility of reliable forecasting. The wastage due to poor estimation of clean energy generation discourages new investments in this area. However, recent advancements in big data technologies enable processing a large amount of data captured from multiple sources in real-time. It opens the possibility of improving the operational optimization of MGs and the performance of forecasting models. The overall MG problem is formulated using a two-stage stochastic mixed-integer linear programming problem with recourse. Amazon Web Services (AWS) IoT analytics platform inputs data in real-time and runs a sophisticated wind generation forecast analysis. The stochastic model is solved using the Sample Average Approximation (SAA) algorithm. The innovative methodology leads to significant improvements in the total average operating cost by integrating AWS IoT Analytics compared to traditional methods that use historical data. Computations are performed for different power-grid settings, including a power-outage, and different power generators units capacities with total operation average cost savings of 7.6% and 5.9%, respectively. Sensitivity analysis showed that the SSA algorithm could solve all the instances by providing high-quality solutions. The AWS IoT strategy outperformed at 7.7 % and 3.6% for optimality gap and CPU time, respectively. We examined an actual case in Peru for an agricultural application to assess the performance of a stochastic optimization model with a real-time IoT wind generation forecast strategy. The results revealed the following capabilities of our novel framework: (1) it can realize higher cost savings from the MG operating systems; (2) improve real-time renewable energy forecasting; (3) facilitate robust decision-making under conditions of uncertainty.
... They announce a savings of 41 to 74% for a combined storage/PV system. More generally, Ref. [30] presents a review of the literature on the economic benefits of microgrids. They conclude that there is potentially a substantial economic gain, while insisting that the monetization strategy must be adapted to the specificities of the deployment site. ...
Article
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Hydrogen has been identified as a very promising vector for energy storage, especially for heavy mobility applications. For this reason, France is making significant investments in this field, and use cases need to be evaluated as they are sprouting. In this paper, the relevance of H2 in two storage applications is studied: a domestic renewable electricity production system connected to the grid and a collective hydrogen production for the daily bus refill. The investigation consists of the sizing of the system and then the evaluation of its performance according to several criteria depending on case. Optimizations are made using Bayesian and gradient-based methods. Several variations around a central case are explored for both cases to give insights on the impact of the different parameters (location, pricing, objective, etc.) on the performance of the system.Our results show that domestic power-to-power applications (case 1) do not seem to be competitive with electrochemical storage. Meanwhile, without any subsidies or incentives, such configuration does not allow prosumers to save money (+16% spendings compared to non-equipped dwelling). It remains interesting when self-sufficiency is the main objective (up to 68% of energy is not exchanged). The power-to-gas application (case 2, central case), with a direct use of hydrogen for mobility, seems to be more relevant according to our case study, we could reach a production cost of green H2 around 5 €/kg, similar to the 3–10 $/kg found in literature, for 182 houses involved. In both cases, H2 follows a yearly cycle, charging in summer and discharging in winter (long term storage) due to low conversion efficiency.
... This problem has been previously solved by electrical engineers who allocated a Value of Lost Load (VoLL) to power blackouts which are at an increased risk due to privatization and the expansion of renewable capacity [42]. Further applications include micro and nanogrids that provide localized utilities during grid-outages [43]. Originally, this solution was applied to critical infrastructure such as hospitals, military bases, water treatment plants, and computer server farms requiring redundancies and where an operator is willing to pay a premium to avoid power disruptions [44]. ...
... A literature review in 2015 points to a considerable increase in VoLL varying between $5-280 per kWh [42]. Regardless of the end-user, VoLL is always understood to be higher than the price of the undelivered energy [43]. ...
Article
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Climate change brings several challenges to BPS practitioners beyond GHG emission mitigation. Adaptation to grid-outage events, caused by both acute and chronic stresses, requires consideration of how building services can be provided to occupants in a time of need. At the moment, we lack both the tools and processes to quantify key metrics such as thermal resiliency in tandem with annual performance indicators. This paper proposes a multi-objective approach using thermal resiliency, annual net-energy, and life-cycle cost to better quantify building performance during grid-outages. The approach can handle a variety of events, using shortened simulation periods, and consider cost-implications of outages by applying the value of the lost load to annual operational costs. The methodology is demonstrated using a case-study and a historical grid-outage from an ice-storm event. Resiliency indicators are improved by two times and the payback of upgrade packages is decreased to 14 years for a single outage event.
... From the control features point of view, it is highly effective but the complexity to achieve is also high. [10,2] Challenges, and research needs 2010, 2015 [11,12] AC versus DC: Resources [19,20] DC: Hierarchical control 2015, 2020 [21] Building microgrids: Hierarchical control 2019 [45,24] Protection schemes 2014 -2016, 2018, 2020 [25] Adaptive protection based on communication 2021 [26,27] DC: Protection 2018, 2019 [28] Modeling uncertainties 2017 [29][30] EMS 2015, 2018 -2020 [31] DC: Architectures, Applications, and Standardization 2016 [32,33] Power sharing 2016, 2017 [34] Islanded: EMS and planning 2019 [35] Operation, applications, modeling, and control 2021 [36] Generation, demand forecasting 2018 [37,38] Experimental microgrids and example cases 2010, 2011 [39] DC: Planning, operation and control 2021 [40,41] DC: Control, power sharing and stabilization techniques 2016, 2019 [42] Stability improvement 2017 [43] Reactive power compensation 2018 [44] Value streams 2016 [89,6] Implementation of AI and ANN in control 2017, 2020 [45][46][47] Hybrid/Energy storage/Flywheel application 2017, 2019 [48] Technologies, key drivers, and outstanding issues 2018 [49] Transactive Energy Market 2020 [50] Guidelines for practical implementations and operation 2020 This paper Implementation of AI techniques in control (single and networked microgrids) others as slaves. There must be a communication channel established for coordinated control of master and slave controllers itself which could be a possible hurdle for local controllers. ...
Article
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Microgrids are gaining popularity by facilitating distributed energy resources (DERs) and forming essential consumer/prosumer centric integrated energy systems. Integration, coordination and control of multiple DERs and managing the energy transition in this environment is a strenuous task. Classical control techniques are not enough to support dynamic microgrid environments. Implementation of Artificial Intelligence (AI) techniques seems to be a promising solution to enhance the control and operation of microgrids in future smart grid networks. Therefore, this paper briefly reviews the control architectures, existing conventional controlling techniques, their drawbacks, the need for intelligent controllers and then extensively reviews the possibility of AI implementation in different control structures with a special focus on the hierarchical control layers. This paper also investigates the AI-based control strategies in networked/interconnected/multi-microgrids environments. It concludes with the summary and future scopes of AI implementation in hierarchical control layers and structures including single and networked microgrids environments.