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Energy Management of CHP-Based Microgrid with Thermal Storage for Reducing Wind Curtailment
Abstract
A large amount of wind energy curtailment is observed during the winter off-peak period in northern China. Because heat demand is high but electric demand is low, combined heat and power (CHP) units have to generate power to supply heat, leaving no load for wind farms to serve. To solve this problem, this paper proposes an energy management method to take advantage of the flexibility in different heating resources in a CHP-based microgrid to relieve wind power curtailment. A novel two-layer coordinated strategy (a schedule layer and a real-time layer) is proposed to control all the components including distributed generation (DG) units, different heating sources, and electrical energy storage (EES). In the schedule layer, a centralized optimization model based on forecasting data is implemented. The real-time layer calculates control signals based on metrical data and received reference values from the upper layer. Flexible control of EES and electric heater scheme (FCEE) is developed to further increase grid integration of wind generation. A 14-bus test system is designed to illustrate the performance of the proposed approach. Results show that the presented method is able to significantly reduce wind curtailment and ensure promising operation efficiency of the studied CHP-based microgrid.
... To accomplish this, mathematical characterisation of the parts of the system are needed for control purposes. In most cases, different elements of the CHP system are designed as a result of simple energy balances, as housing applications do not require high accuracy in terms of chemical and thermal processes [7,93]. The energy management problem consists of ensuring autonomy of the FC-based CHP system, as it is a sustainable alternative to current energy sources, while promoting global efficiency and mitigating fuel cell degradation. ...
... Other energy management methods are based on recursive calculations [92,93]. In [92], a forecasting unit is added to a test-bench to match energy demand in a real CHP system. ...
... This is verified in a real experimental platform, and the operation of each CHP element is monitored. In [93], voltage and power of the CHP system are computed and compared to certain initial values, and local controllers are adjusted after each iteration in order for the system to match the target values. ...
Combined heat and power technologies represent an efficient way to ensure energy efficiency, as they promote usage of both electrical and thermal energy, something not done by most traditional energy sources, especially in residential environments. In this context, high-temperature proton exchange membrane fuel cells allow the implementation of combined heat and power systems. Additionally, in this environment, fuel cells are more efficient and less polluting than their traditional counterparts. We present a literature review of energy management in residential systems based on this type of fuel cell. In addition, we classify and detail the current state of fuel cell technologies, paying special attention to their characteristics, mathematical modelling and control, as well as combined heat and power systems and energy management strategies.
... Due to the natural intermittent property, wind power can not be dispatched on demand. When the available wind power excess the operation capability of the integrated power grid, wind curtailment has to be performed to keep power balance in the system, which leads to an critical issue of massive wind generation curtailment during the winter off-peak period in Northern China [1]. To ensure the utilization of wind power, the Government of China has also issued a set of policies to guide market design and technology development [2]. ...
... Therefore, additional flexibility resources need to be introduced in heating supply to allow CHP units to further reduce their power output for relieving wind generation curtailment. Installing electrical boilers (EB) is one of the potential solutions that can utilize wind generation to meet the heat load demand [1]. Electrical energy storage has also been widely applied to increase the flexibility in island microgrid operation [14]. ...
The uncertainty and intermittency of the available wind resource in nature would potentially cause wind generation curtailment when the flexibility of the integrated power grid is limited, especially in small-scale microgrids for islands. In this paper, an optimal configuration method is proposed to use thermal energy storage (TES) to relieve wind generation curtailment in an island microgrid. The thermal network is modeled along with the electrical network to utilize its regulation capability, while TES is introduced as an additional flexibility resource. The detailed cost models of combined heat and power (CHP) units and TES are presented to realize the objective of minimizing the overall operating cost. The performance of TES in improving wind power utilization is firstly validated by using an electrical boiler (EB) as a benchmark and further analyzed under different scenarios considering the growths of wind power capacity, electrical load, and heat load. The effectiveness of the proposed method is validated using real-world data obtained from the practical island microgrid.
... With the energy system transformation, the proportion of renewable energy is gradually increasing. Traditional electric energy storage technology does not have an advantage in large-scale energy storage due to its high price and cost (Cheng et al., 2018). Seasonal pumped storage, large-capacity compressed air energy storage, large-scale thermal storage and P2X technologies have attracted a great deal of attention from researchers (Guo et al., 2020;Qiu et al., 2020;Hunt et al., 2020). ...
Keywords: Urban multi-energy flow system Inter seasonal heat storage Electric hydrogen production Joint optimization of planning and operation a b s t r a c t With the urbanization construction and the advancement of the carbon peaking and carbon neutrality goals, urban energy systems are characterized by coupling multi-energy networks and a high proportion of renewable energy. Urban energy systems need to improve the quality of energy use, as well as to achieve energy conservation and emission reduction. Inter-seasonal heat technology has satisfactory engineering application prospects in promoting renewable energy consumption and the energy supply of urban multi-energy systems. Considering inter-seasonal heat storage and electric hydrogen production, a joint optimization method of planning and operation is proposed for the urban multi-energy flow system. First, the operation framework of inter-seasonal heat storage and electric hydrogen production system is established, which clarifies the energy flow of the urban multi-energy system. Secondly, aiming at the goals of minimizing the equipment's annual investment cost and the multi-energy system annual operation cost, combined with the time series period division method, a planning operation model has been established considering multi-objectives. Through case study, it is shown that the proposed model can promote the renewable energy consumption and reduce the operation cost of the whole system.
... In [6], scheduling electric vehicle charging to minimize carbon emissions and wind curtailment is proposed. In [7], energy management of CHPbased microgrid with thermal storage for reducing wind curtailment is proposed. In [8], analysis of energy storage systems to exploit wind energy curtailment in Crete is carried out. ...
... These efforts have considered a range of approaches that can be roughly classified as deterministic methods or scenario-based stochastic programming. Specifically, some authors (Cheng et al. 2018;Hu et al. 2013;Ghasemi and Enayatzare 2018;Hosseinnezhad et al. 2016) incorporated uncertainty via a deterministic optimization framework with a single expected forecast for the uncertain inputs. Subsequently, deterministic rolling-horizon approaches have been implemented to take advantage of updated information as the model moves through the operation time frame, still in a deterministic formulation (Zhang et al. 2016;Kalavani et al. 2019;Qureshi et al. 2014;Borsche et al. 2014;Palma-Behnke et al. 2013). ...
As the level of renewable and distributed energy resources (DER) increases in power systems, there is a coincident effort to ensure ongoing reliability. Microgrids are likely to play a central role in this development globally. However, a counterpoint is the high cost of microgrid operations, and there exists a need to develop efficient tools to operate microgrids optimally and economically. In this paper, the potential of demand response (DR) to reduce microgrid operation cost while supporting renewable integration is investigated. Three types of DR, namely thermostatically controlled load (TCL), deferrable load (DL), and elastic load (EL), are explored in the context of various system conditions. Because systems with significant renewables and DER are subject to high levels of uncertainty, the investigation is conducted under a stochastic rolling-horizon optimization framework that leverages the update of renewable generation forecast and the energy market real-time prices (RTP). A case study illustrates that certain system conditions, such as price peaks and moderate temperatures, facilitate best demand response performance. Conversely, inaccurate price forecast information can lead to ineffectual operation of microgrids and result in higher cost. The insights provided by the study of various types of DR are helpful for microgrid design with consumers’ preferences taken into consideration.
... A few study based on superconducting magnetic energy storage for enhancing MG operation and controls are reported in [33][34][35]. Thermal energy storage for MG applications are presented in [36][37][38]. Using hydrogen to support energy back up for microgrid operation are investigated in [39][40][41][42]. ...
Energy storage has an effective role on establishing isolated microgrids (MGs) that contain intermittent renewable energy sources. Energy storages depending upon their technologies can ensure stable and reliable operation, control, and resiliency of the MGs. Therefore, it is indispensable to study MGs operation using appropriate, cost effective and sustainable energy storages along with necessary control. In this paper, sizing, operation and control of a suitable energy storage method for a case study MG system is presented. Due to the excellent geographical location of the case study MG system, a pumped hydro storage is selected; and the sizing of this storage unit is provided using mathematical models that is based on the system physical dimension. In addition, governor-excitation control based on power-frequency droop is designed for the pumped hydro storage unit. The controller performance is tested under various load changes in the MG and the results are presented to show the effectiveness of the designed controller. The performance of the MG frequency and the voltage at the MG bus under load disturbances indicate that the proposed pumped hydro storage is capable to maintain stable operation of the study MG system. Sizing outcomes and performance analysis of the designed controller have been carried out using MATLAB/Simulink software package.
... Dai et al. (2017) have studied the modeling of active thermal storage (ATS) and passive thermal storage (PTS) in a combined heat and power (CHP) plant. Also, in Cheng et al. (2018) energy management of CHP-based microgrid has been performed by thermal storage in order to reduce wind curtailment. Zou et al. (2019) have solved the CHPED problem by an improved genetic algorithm and a new constraint handling strategy. ...
Economic dispatch is the optimal scheduling for generating units with technical constraints. Combined heat and power economic dispatch (CHPED) refers to minimization of the total energy cost for generating electricity and heat supply to load demand. This planning model integrates heat and power energy to balance energy supply and demand, mitigate climate change and improve energy efficiency of sustainable cities and green buildings. In this paper for the first time, self-regulating particle swarm optimization (SRPSO) algorithm is utilized for solving the CHPED problem by considering valve point effects and prohibited zones on fuel cost function of pure generation units and electrical power losses in transmission systems. The main advantage of SRPSO algorithm to PSO algorithm is the inertia weight flexibility with respect to search conditions. In this algorithm, unlike PSO algorithm that inertia weight reduces in each iteration, this value increases or reduces proportional to particles’ positions, which will lead particles to achieve optimal value with higher speed. The capability and effectiveness of the proposed algorithm are evaluated on a large-scale energy system using MATLAB environment. The results obtained by SRPSO algorithm are outperformed by other optimization methods from the economic, sustainable energy and time consumption point of view.
... Вопросы децентрализованного энергообеспечения рассматриваются при выборе архитектуры энергоснабжения. Все больше исследовательского интереса уделяется технологиям «микросетей» и «умных сетей» [9]. В этих технологиях широко используют возобновляемые источники энергии: биоэнергетика [10][11][12], ветроэнергетика [13; 14], солнечная энергетика [15][16][17]. ...
Introduction. Recently the issue of decentralised (autonomous) power supply of certain rural consumers has been increasingly considered. Various small power generators using local and renewable energy sources can be applied for this purpose. So a consumer must choose the best-suited energy-generating source.
Materials and Methods.The findings of energy audits, which were conducted by the Institute from 2003 to the present day, were used to evaluate energy consumers and determine operation modes of equipment and load schedules. Complex index of the negative impact of heat and electricity generation on the environment was determined using the Spesivtsev ‒ Drozdov method of logical-linguistic modelling based on expert assessments.
Results. Energy sources can be divided into traditional (diesel generators and gas generator plants) or renewable ones (wind turbines, solar collectors, mini hydro systems). Energy source is chosen either with the help of the economic criterion, being the cost of one k·Wh of energy or the criterion of environmental compatibility, or total specific emission of pollutants from energy generation at local generating sources (g/k·Wh). Here, not only the quantity of emissions, but also the harmful effect on the environment is considered.
Discussion and Conclusion. For the choice of energy supply sources, the coefficient of energy-ecological compatibility is proposed, being the product of the cost of one k·Wh of energy generated and specific emission of pollutants. The optimal value of this factor is the smallest, which accounts for both economic and environmental feasibility of energy generating sources.
In this paper, a consistent framework to optimize the energy consumption in microgrids (MGs) with the presence of Distributed Energy Resources (DERs) such as Wind Turbines, Photo-Voltaic arrays, Combined Heat and Power, Fuel Cell, Boiler and Batteries is presented, in which battery owners can use them both in battery to grid and grid to battery (G2V). Since the time of use electricity tariff is higher than charging rate pricing, the batteries are due to discharge their energy to the loads and otherwise, the DERs such will supply the batteries and the rest of demands. The load uncertainties and renewable energy probability of production modeled with different probability densities through Beta, Weibull distribution functions with suitable coefficients and information gap decision theory, are going to be modeled and solved using the Improved Shuffled Frog Leaping Algorithm (ISFLA). In this way, the best sets of distributed energy resources in MGs are chosen. The results comparison of the proposed method with the existing methods has verified the superiority of ISFLA method to solve this optimization problem in IEEE 33 and 69 bus test systems.
This research effort formulates and solves a biobjective dynamic combined heat and power economic-emission dispatch (DCHPED) of generation in a microgrid (MG). The MG encompasses fossil-fuel power and heat units, renewable resources, price-operated electrical and thermal energy storage elements, bidirectional-exchange of electrical power with the external grid, and fixed nonfferrable and deferrable loads. The two objective functions involve the total operation cost and the total gas emission produced by the fossil fuel units participating in the MG dynamic dispatch. Costs of emission tax and price-based energy storage and exchanges with the external grid are ingredients of the total operating costs. The Bernstein-search differential evolution (BSDE) algorithm is utilized to deal with the problem to obtain the day-ahead optimal schedules of available resources. The nonlinear nonconvex MG DCHPED optimization problem that has a large number of decision variables involves equality and inequality constraints, production costs, emission levels, taxes of released gases, ramp-rate limits of power-producing units, effects of valve-points in generating units, active power transmission losses, and feasible operation regions of coegenerating (CHP) units. The paper investigates the positive impacts of utilizing price-based electrical and thermal storage elements, deferrability of loads, and price-based power exchanges on the day-ahead MG operation cost. The paper also describes an approach to achieve the best compromise solution (BCS) of the MG DCHPED employing the fuzzy satisfying method (FSM). In addition, it shows that gas emissions and emission taxes in the MG can be both controlled by exchanging power with the external grid.
With the development of energy markets and the introduction of renewable energy certificates (RECs), a regional integrated energy system (RIES) may participate in an energy wholesale market flexibly. In this paper, a bilevel optimization problem is formulated to determine the optimal management strategies of an RIES, including trading in the markets of electricity, natural gas, and RECs. In the bilevel model, an energy supplier (ES) purchases energy from energy wholesale markets and sets retail prices of energy products at the upper level to maximize its profit. At the lower level, various user aggregators (UAs) determine individual energy consumption strategies. The clearing prices of electricity, natural gas, and REC markets are determined asynchronously at the lower level. This nonlinear problem is then transformed into a mixed-integer linear programming problem using the incremental method and strong duality theory, which enables the problem to be solved efficiently. Finally, case studies are carried out to demonstrate the feasibility and effectiveness of the proposed method and the impacts of the RECs.
Operational bottlenecks are commonly observed in power systems and lead to severe system security issues, which may be caused by the fluctuating and uncertain nature of renewable energy. This paper presents an approach to define, identify and eliminate such bottlenecks in the scope of system balance for renewable energy integrated bulk power systems, so as to quantify the requirement of energy storage. A mixed-integer linear programming (MILP) formulation for system operational bottleneck identification is proposed given renewable generation profile, in order to obtain operational restriction indices to assess the adequacy of power adjustment margin and power ramp rate. Cosine similarity based density-based spatial clustering of applications with noise (DBSCAN) method is used to cluster a large number of scenarios by operational restriction indices, then scenarios with bottlenecks are attributed to corresponding clusters. Finally, various bottleneck elimination options, including energy storage with different technologies, are compared for each cluster. Case studies of an eight-bus test system and a practical Chinese power system are presented to verify the proposed approach, the numerical results indicate energy storage is the most effective option to eliminate bottlenecks identified in power downward adjustment margin and ramp rate dominated clusters aforementioned.
This paper deals with the multi-objective economic-emission dispatch problem of combined heat and power (CHP) generation in a large microgrid (MG). The MG comprises many types of fossil fuel generating units, wind power units, and solar power units. The objective functions involve unit operating costs, emission level, emission tax, and cost of power purchase from the main external grid. Interdependencies of heat and power outputs of CHP units and valve-point effects of thermal units impose non-convexities, nonlinearities and complications in the dispatch modeling and optimization. The intermittent stochastic nature of wind and solar power and considering transmission losses increase the complexity of the problem. In addition to compromise programming, this paper uses some recent metaheuristic methods to solve the MG combined heat-power economic-emission dispatch (MG CHPED) problem. The results will show that cost and emissions in MG are totally conflicting functions, and different global optimization solvers may result in different near-global solutions. Single and multi-objective solutions obtained for the MG CHPED require the MG operator to use a decision-making tool, which is the fuzzy satisfying method in this paper, to select the best compromise solution among the achieved sets of solutions.
The current status of wind power and the energy infrastructure in Denmark is reviewed in this paper. The reasons for why Denmark is a world leader in wind power are outlined. The Danish government is aiming to achieve 100% renewable energy generation by 2050. A major challenge is balancing load and generation. In addition, the current and future solutions of enhancing wind power penetration through optimal use of cross-energy sector flexibility, so-called indirect electric energy storage options, are investigated. A conclusion is drawn with a summary of experiences and lessons learned in Denmark related to wind power development.
This paper presents a two-stage stochastic programming model for provision of flexible demand response (DR) based on thermal energy storage in the form of hot water storage and/or storage in building material. Aggregated residential electro-thermal technologies (ETTs), such as electric heat pumps and (micro-) combined heat and power, are modeled in a unified nontechnology specific way. Day-ahead optimization is carried out considering uncertainty in outdoor temperature, electricity and hot water consumption, dwelling occupancy, and imbalance prices. Building flexibility is exploited through specification of a deadband around the set temperature or a price of thermal discomfort applied to deviations from the set temperature. A new expected thermal discomfort (ETD) metric is defined to quantify user discomfort. The efficacy of exploiting the flexibility of various residential ETT following the two approaches is analyzed. The utilization of the ETD metric to facilitate quantification of the expected total (energy and thermal discomfort) cost is also demonstrated. Such quantification may be useful in the determination of DR contracts set up by energy service companies. Case studies for a U.K. residential users’ aggregation exemplify the model proposed and quantify possible cost reductions that are achievable under different flexibility scenarios.
Smart grid is advancing power grids significantly, with higher power generation efficiency, lower energy consumption cost, and better user experience. Microgrid utilizes distributed renewable energy generation to reduce the burden on utility grids. This paper proposes an energy ecosystem; a cost-effective smart microgrid based on intelligent hierarchical agents with dynamic demand response (DR) and distributed energy resource (DER) management. With a dynamic update mechanism, DR automatically adapts to users' preference and varying external information. The DER management coordinates operations of micro combined heat and power systems ($boldsymbol {mu }$ CHPs), and vanadium redox battery (VRB) according to DR decisions. A two-level shared cost-led $boldsymbol {mu }$ CHPs management strategy is proposed to reduce energy consumption cost further. VRB discharging is managed to be environment-adaptive. Simulations and numerical results show the proposed system is very effective in reducing the energy consumption cost while satisfying user's preference.
With the largest installed capacity in the world, wind power in China is experiencing a curtailment during operation. The large portion of the generation capacity from inflexible combined heat and power (CHP) is the major barrier for integrating this variable power source. This paper explores opportunities for increasing the flexibility of CHP units using electrical boilers and heat storage tanks for better integration of wind power. A linear model is proposed for the centralized dispatch for integrated energy systems considering both heat and power, with detailed modeling of the charging processes of the heat storage tanks. The model balances heat and power demands in multiple areas and time periods with various energy sources, in-cluding CHP, wind power, electrical boilers, and heat storage. The impact of introducing electrical boilers and heat storage systems is examined using a simple test system with characteristics similar to those of the power systems in Northern China. Our results show that both electrical boilers and heat storage tanks can improve the flexibility of CHP units: introducing electrical boilers is more effective at reducing wind curtailment, whereas heat storage tanks save more energy in the energy system as a whole, which reflect a different heating efficiency of the two solutions. Index Terms—Combined heat and power (CHP), energy system integration, heat storage, wind power.
One of the important points in optimal operation of a micro-CHP based microgrids (e.g., a residential building) is to coordinate its thermal and electrical loads. Therefore, in this study, thermal load is analyzed more precisely in terms of the required hot water and desired building temperature. The microgrid is assumed to be equipped with smart meters and controllable electrical loads. The information provided by smart meters is utilized in implementing smart control of micro-CHP, storages, and demand response programs. This study is aimed at presenting an optimal scheduling model for a microgrid considering technical and economical constraints based on temperature dependent thermal load modeling. A sensitivity analysis is conducted to identify and rank the impact of several uncertainties such as variations in temperature, electrical and thermal demand.
A smart building energy system usually contains multiple energy sources such as power grids, autonomous generators, renewable resources, storage devices, and schedulable loads. Storage devices such as batteries, ice/heat storage units, and water tanks play an important role in reducing energy cost in building energy systems since they can help sufficiently utilize renewable energy resources and time-of-use electricity prices. It is important to plan, schedule, and coordinate all the storage devices together with schedulable loads in a building facilitated by microgrid technology. To consider the above problem with uncertainties in solar radiation and demand profiles, a stochastic optimization problem is formulated and solved by the scenario tree method. The best combination and the optimal capacities of storage devices for specific building energy systems are then determined. Furthermore, the optimal operating strategy of building energy systems can be obtained. The performance analysis on the storage devices is conducted and the numerical results show that thermal storage devices (e.g., ice storage units, water tanks) are good for saving energy costs but batteries may not be economical due to their high investment cost and short lifetime. It is also observed that the aforementioned uncertainties have an impact on selecting which type and capacity of storage device should be used.
Wind turbine technology has significantly improved over the last 20 years, allowing for the rapid growth of the wind penetration that we are now witnessing. Large-scale wind power penetration impacts the electricity supply industry (ESI) in many aspects and leads to fundamental changes in electric power systems. Also, it raises a number of technical challenges for the transmission system operator, distribution system operator, and wind turbine generator manufacturers. This paper aims to present in a thorough and coherent way the picture redrawn for electric power systems under large wind power penetration. Topics related to technical challenges emerged and relevant technical solutions required are analyzed. Finally, general conclusions are extracted about the current and future ESI status and general directions are recommended.
The deployment of small ( < 1-2 MW ) clusters of generators, heat and electrical storage, efficiency investments, and combined heat and power (CHP) applications (particularly involving heat-activated cooling) in commercial buildings promises significant benefits but poses many technical and financial challenges, both in system choice and its operation; if successful, such systems may be precursors to widespread microgrid deployment. The presented optimization approach to choosing such systems and their operating schedules uses Berkeley Lab's Distributed Energy Resources Customer Adoption Model (DER-CAM), extended to incorporate electrical and thermal storage options. DER-CAM chooses annual energy bill minimizing systems in a fully technology-neutral manner. An illustrative example for a hypothetical San Francisco hotel is reported. The chosen system includes one large reciprocating engine and an absorption chiller providing an estimated 11% cost savings and 8% carbon emission reductions under idealized circumstances.
There is a potential for utilizing a combination of combined heat and power (CHP) plants together with large scale heat pumps in district heating systems to balance intermittent renewable power production. The thought is to use a combination of both power production and consumption to balance both surplus and deficit in the electric power market. Much research has presented different modeling and simulations of such systems. This particular study present lessons and empirics from operating such a system. The DH system in Stockholm is large with over 12 TWh of heat demand annually. Since the 1970s the system has been operated with both CHPs and heat pumps. About 660 MW of heat pumps and 300 MW of electric boilers are currently operational in this system. Both the district heating and district cooling systems are equipped with storage. Besides constituting an empirical example, the paper contributes with input to future modeling of this kind of system.
We present a primal-dual interior-point algorithm with a lter line-search method for non- linear programming. Local and global convergence properties of this method were analyzed in previous work. Here we provide a comprehensive description of the algorithm, including the fea- sibility restoration phase for the lter method, second-order corrections, and inertia correction of the KKT matrix. Heuristics are also considered that allow faster performance. This method has been implemented in the IPOPT code, which we demonstrate in a detailed numerical study based on 954 problems from the CUTEr test set. An evaluation is made of several line-search options, and a comparison is provided with two state-of-the-art interior-point codes for nonlin- ear programming.
Energy is fundamental to modern society. Increase in the price of oil as well as environmental concerns have spurred the use of alternative renewable energy sources. In the Faroe Islands, the readily available wind energy is an obvious source for space heating. Seasonal correlation exists between wind energy and required space heating and mismatches can be reduced by using simple water tanks as heat storages. A traditional Danish induction generator wind turbine has been erected on the island of Nólsoy to produce energy for space heating. The system is designed as a stand-alone microgrid, which needs its own control of frequency and voltage. A microcontroller is used to control frequency by matching load (heaters) to generated power and to produce the correct reactive power and voltage by switched capacitors. One challenge is the start-up procedure at high wind speeds when nominal speed tends to be reached before voltage builds up by the self-excitation process. This paper reports the initial test and adaptation of the control system.
This paper discusses the charging of plug-in hybrid electric vehicles (PHEVs) in an existing office building microgrid equipped with a photovoltaic (PV) system and a combined heat and power (CHP) unit. Different charging strategies and charging power ratings for workplace charging are examined for their grid impact and their impact on the self-consumption of the locally generated electricity. The grid impact can be significantly reduced by using strategies that require limited future knowledge of the EV mobility behavior and limited communication infrastructure. These strategies allow a high number of EVs to be charged at an office building, even with a limited number of charging spots, due to the large standstill times.
Increasing power system flexibility by responsive demand is a central issue for the incorporation of higher levels of variable wind generation in future power systems. The electrification of the heat sector, except from energy efficiency gains, may offer a vast potential of new forms of flexible demand, by time-shifting of heat production in buildings. The assessment of this potential can, however, be performed only when the limitations imposed by the primary operation of the equipment (space heating) are realistically taken into account. In this paper, a methodology is presented for the quantification of the flexibility offered by the thermal storage of building stock equipped with heat pumps, to power systems with significant penetration of wind power. A model is proposed for the incorporation of the building stock thermal behavior as equivalent energy storage in electricity market models. At the same time, the model allows the coupling to a detailed dynamic thermal model of buildings for the assessment of the respective operational restrictions. The case study presents the results of a project for the evaluation of the flexibility offered by portfolios of high heat pump deployment in conjunction with high wind penetration scenarios for the future German electricity system.
Smart grids are often analyzed using a top-down approach, i.e., starting from communication and control technologies evolution, to then focus on their effects on active and passive users, in terms of new services, higher efficiency and quality of supply. However, with their bottom-up approach, virtual power plants (VPP) are very promising instruments for promoting an effective integration of distributed generation (DG) and energy storage devices as well as valid means for enabling consumers to respond to load management signals, when operated under the supervision of a scheduling coordinator. These aggregation factors can be very profitable for the distributed energy resources (DERs) economy and for the energy network itself. This paper presents a new algorithm to optimize the day-ahead thermal and electrical scheduling of a large scale VPP (LSVPP) which contains: a) many small-scale producers and consumers (“prosumers”) distributed over a large territory and b) energy storage and cogeneration processes. The algorithm also takes into account the actual location of each DER in the public network and their specific capability. Thermal and electrical generator models, load and storage devices are very detailed and flexible, as are the rates and incentives framework. Several novelties, with respect to the previous literature, are proposed. Case study results are also described and discussed.
There are two operation modes of microgrids: grid-connected mode and stand-alone mode. Normally, a microgrid will be connected to the main grid for the majority of time, i.e., operates in the grid-connected mode. In the stand-alone mode, a microgrid is isolated from the main grid; the highest priority for microgrids is to keep a reliable power supply to customers instead of economic benefits. So, the objectives and energy management strategies are different in two modes. In this paper, a novel double-layer coordinated control approach for microgrid energy management is proposed, which consists of two layers: the schedule layer and the dispatch layer. The schedule layer obtains an economic operation scheme based on forecasting data, while the dispatch layer provides power of controllable units based on real-time data. Errors between the forecasting and real-time data are resolved through coordination control of the two layers by reserving adequate active power in the schedule layer, then allocating that reserve in the dispatch layer to deal with the indeterminacy of uncontrollable units. A typical-structure microgrid is studied as an example, and simulation results are presented to demonstrate the performance of the proposed double-layer coordination control method in both grid-connected mode and stand-alone mode.
This paper presents the influence of different regulation strategies on wind energy integration into the existing energy system of Jiangsu. The ability of wind integration is defined in terms of the ability to avoid excess electricity production, to conserve primary energy consumption and to reduce CO2 emissions in the system. Firstly, a reference model of Jiangsu's energy system is built using the energy system analysis tool EnergyPLAN based on the year 2009. The model results are then compared to actual values from 2009 to validate their accuracy. Based on the reference model, different regulations of Jiangsu's energy system are compared and analyzed in the range of a wind input from 0% to 42% of the total electricity demand. It is concluded that operating power plants in a flexible way facilitates the promotion of more intermittent wind integration.
Conventional industrial microgrids (IMGs) consist of factories with distributed energy resources (DERs) and electric loads that rely on combined heat and power (CHP) systems while the developing IMGs are expected to also include renewable DERs and plug-in electric vehicles (PEVs) with different vehicle ratings and charging characteristics. This paper presents an electricity and heat generation scheduling method coordinated with PEV charging in an IMG considering photovoltaic (PV) generation systems coupled with PV storages. The proposed method is based on dynamic optimal power flow (DOPF) over a 24-hour period and includes security-constrained optimal power flow (SCOPF), IMG's factories constraints, PV storage constraints and PEVs dynamic charging constraints. It will utilize the generators waste heat to fulfill thermal requirements while considering the status of renewable DERs to decrease the overall cost of IMGs. To demonstrate the effectiveness of the proposed method, detailed simulation results are presented and analyzed for an 18-bus IMG consisting of 12 factories and 6 types of PEVs without/with PV generation systems operating in grid-connected and stand-alone modes. The main contribution is including PEVs with dynamic constraints that have changed the nature of scheduling formulation from a simple hourly OPF to a dynamic OPF.
At the planning of combined heat and power (CHP)-based micro-grid, its distributed energy resources (DER) capacity is to be selected and deployed in such a way that it becomes economically self-sufficient to cater all the loads of the system without utility's participation. Economic deployment of DERs is meant to select optimal locations, optimal sizes, and optimal technologies. Optimal locations and sizes, which are independent of CHP-based DERs types, are selected, here, by loss sensitivity index (LSI) and by loss minimization using particle swarm optimization (PSO) method, respectively. In a micro-grid, both fuel costs and ${\rm NO}_{\rm x}$ emissions are, mainly, dependent on types of DERs used. So the main focus of the present paper is to incorporate originality in ideas to evaluate how different optimal output sets of DER-mix, operating within their respective capacity limits, could share an electrical tracking demand, economically, among micro-turbines and diesel generators of various sizes, satisfying different heat demands, on the basis of multi-objective optimization compromising between fuel cost and emission in a 4-DER 14-bus radial micro-grid. Optimization is done using differential evolution (DE) technique under real power demand equality constraint, heat balance inequality constraint, and DER capacity limits constraint. DE results are compared with PSO.
Today, in most countries, electricity is produced either on hydropower or on large steam turbines on the basis of fossil fuels or nuclear power. Electricity from distributed generation constitutes only small amounts. Until now, the task of balancing supply and demand and the task of securing frequency and voltage on the grid has been left solely to large production units. Meanwhile, the implementation of cleaner technologies, such as renewable energy, combined heat and power production and energy conservation, is necessary for future sustainable energy systems. Consequently, such distributed production units sooner or later need to contribute to the task of securing a balance between electricity production and consumer demands. This paper presents technical designs of potential future flexible energy systems, which will be able both to balance production and demand and to secure voltage and frequency requirements on the grid.
Optimal deployment, with respect to locations, capacity sizes, and types of distributed energy resources (DERs), which are the main components in a microgrid system, are chosen for study in this paper. For the selection of optimal locations of DERs, the loss sensitivity index of each bus is taken into account. Whereas optimal size and its separation among microturbines, diesel generators and combustion turbines at each bus location are performed on the basis of the maximum benefit-to-cost ratio of the microgrid owner, obtained by using the particle swarm optimization technique and with respect to their reliable catering and quality of power as well as heat (i.e., combined-heat-and-power (CHP) operation) for customers. This paper conducts four separate case studies-two on 6-bus systems (radial and meshed) and resting on 14-bus systems (the IEEE system and radial system)-to show how much these systems are economically feasible for investment planning when cost and CHP benefits of various types of DERs are taken into account. Load profiles, tariffs, as well as the constructional cost of the microgrid itself are addressed in the six-bus meshed network and its central DER location in a district-heating paradigm is also done separately.
The paper presents the ability of different energy systems and regulation strategies to integrate wind power. The ability is expressed by the following three factors: the degree of electricity excess production caused by fluctuations in wind and Combined Heat and Power (CHP) heat demands, the ability to utilise wind power to reduce CO2 emission in the system, and the ability to benefit from exchange of electricity on the market. Energy systems and regulation strategies are analysed in the range of a wind power input from 0 to 100% of the electricity demand. Based on the Danish energy system, in which 50% of the electricity demand is produced in CHP, a number of future energy systems with CO2 reduction potentials are analysed, i.e. systems with more CHP, systems using electricity for transportation (battery or hydrogen vehicles) and systems with fuel-cell technologies. For the present and such potential future energy systems different regulation strategies have been analysed, i.e. the inclusion of small CHP plants into the regulation task of electricity balancing and ancillary grid stability services and investments in electric heating, heat pumps and heat storage capacity. The results of the analyses make it possible to compare short-term and long-term potentials of different strategies of large-scale integration of wind power.
Significant benefits are connected with an increase in the flexibility of the Danish energy system. On the one hand, it is possible to benefit from trading electricity with neighbouring countries, and on the other, Denmark will be able to make better use of wind power and other types of renewable energy in the future. This paper presents the analysis of different ways of increasing flexibility in the Danish energy system by the use of local regulation mechanisms. This strategy is compared with the opposite extreme, i.e. trying to solve all balancing problems via electricity trade on the international market. The conclusion is that it is feasible for the Danish society to include the CHP plants in the balancing of fluctuating wind power. There are major advantages in equipping small CHP plants as well as the large CHP plants with heat pumps. By doing so, it will be possible to increase the share of wind power from the present 20 to 40% without causing significant problems of imbalance between electricity consumption and production. Investment in increased flexibility is in itself profitable. Furthermore, the feasibility of wind power is improved.
Microgrids are low-voltage (LV) distribution networks comprising various distributed generators (DGs), storage devices, and controllable loads that can operate either interconnected or isolated from the main distribution grid as a controlled entity. This paper describes the operation of a central controller for microgrids. The controller aims to optimize the operation of the microgrid during interconnected operation, i.e., maximize its value by optimizing the production of the local DGs and power exchanges with the main distribution grid. Two market policies are assumed including demand-side bidding options for controllable loads. The developed optimization algorithms are applied on a typical LV study case network operating under various market policies and assuming realistic spot market prices and DG bids reflecting realistic operational costs. The effects on the microgrid and the distribution network operation are presented and discussed.
China Wind Power Review and Outlook
Chinese Renewable Energy Ind. Assoc.(2014). "2014 China Wind Power Review and Outlook".
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