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Kazem Zare - One of the best experts on this subject based on the ideXlab platform.
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Robust operation of microgrid energy system under uncertainties and Demand Response Program
Institute of Advanced Engineering and Science, 2020Co-Authors: Sahar Seyyedeh Barhagh, Kazem Zare, Amin Mohammadpour Shotorbani, Behnam Mohammadi-ivatloo, Ali FarzamniaAbstract:<span>Microgrid energy systems are one of suitable solutions to the available problems in power systems such as energy losses, and resiliency issues. Local generation by these energy systems can reduce the role of the upstream network, which is a challenge in risky conditions. Also, uncertain behavior of electricity consumers and generating units can make the optimization problems sophisticated. So, uncertainty modeling seems to be necessary. In this paper, in order to model the uncertainty of generation of photovoltaic systems, a scenario-based model is used, while the robust optimization method is used to study the uncertainty of load. Moreover, the stochastic scheduling is performed to model the uncertain nature of renewable generation units. Time-of–use rates of Demand Response Program (DRP) is also utilized to improve the system economic performance in different operating conditions. Studied problem is modeled using a mixed-integer linear Programming (MILP). The general algebraic modeling system (GAMS) package is used to solve the proposed problem. A sample microgrid is studied and the results with DRP and without DRP are compared. It is shown that same robustness is achieved with a lower increase in the operation cost using DRP.</span>
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Optimal Sitting and Sizing of Energy Storage Systems in a Smart Distribution Network Considering Network Constraints and Demand Response Program
2019Co-Authors: Alireza Akbari-dibavar, Sayyad Nojavan, Kazem ZareAbstract:Demand Response Program (DRP) and energy storage systems (ESSs) are two main tools for load management in smart grids. They can make distribution networks more reliable without costly upgrades for substation constructing or lines reinforcement. This work proposes an optimization framework of optimal sitting and sizing of ESSs in a smart distribution network in the presence of DRP and considering renewable energy sources (RESs) effects and network constraints. The proposed objective function includes two terms: 1) minimization of total investment costs of ESSs; 2) minimization of active losses cost and the power purchased from upstream grid and diesel generators. DRP can reduce operation costs by shifting an amount of loads from hours with high Demand to hours with lower Demand and so can reduce network losses and help in peak load shaving process. In order to solve the proposed optimization model, a mixed-integer non-linear Programming (MINLP) model is constructed and solved using DICOPT solver by GAMS optimization software. A modified 33-bus distribution network is considered and the results of three different cases are compared. Finally it can be noted that total cost of network in case 2, with optimal ESS allocation is reduced by 4.9% with compare to the base case, while this reduction is about 20% in case 3 with considering DRPs beside ESS allocation.
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optimal performance of microgrid in the presence of Demand Response exchange a stochastic multi objective model
Computers & Electrical Engineering, 2019Co-Authors: Tohid Khalili, Sayyad Nojavan, Kazem ZareAbstract:Abstract This paper investigates optimal scheduling of the microgrids, including renewable energy sources and conventional generators. Due to the stochastic nature of the wind speed and the sun irradiation, generated power of the wind turbines and photovoltaic are highly uncertain and in the proposed model the uncertainty of the load, price, and renewable energy sources generation are considered by utilizing the normal distribution function. Incentive-based Demand Response Program is implemented in the operating process. The optimal economic status is achieved by maximizing the microgrid's Demand Response Program profit and minimizing the generators cost, and the trading cost. This multi-objective model is solved by the weighted sum technique in order to produce the optimal Pareto solutions and the trade-off solution is selected by applying the fuzzy satisfying method. It is performed on two different microgrids and sensitivity analysis is executed. Results demonstrate that Demand Response Program reduces unused energy in both scenarios.
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optimal stochastic scheduling of cryogenic energy storage with wind power in the presence of a Demand Response Program
Renewable Energy, 2019Co-Authors: Farshad Kalavani, Behnam Mohammadiivatloo, Kazem ZareAbstract:This paper provides a stochastic method to conduct the optimal scheduling of the combination of wind power and new-type large-scale energy storage with considering the Demand Response Program in the electricity market. The integration of ASU and CES make the opportunity to store energy in the form of liquid in the off-peak periods and recovering the electricity in the peak periods. The uncertainty of electricity price, load Demand and wind speed considered as the stochastic model uncertain parameters. The optimal operation of wind turbine, CES, and conventional generation units, considering the stochastic models for price, Demand, and wind speed, was formulated as a mixed-integer non-linear Programming (MINLP) problem. The constraints of CES operation, liquid and gas product Demands, and ASU production were considered in ASU-CES modeling. The startup cost, minimum on/off time constraints, ramp rate, and capacity limits were considered in the formulation of conventional power generation. The Demand Response (DR) Program was adopted to increase the total expected profit and decrease the total operational cost. The results revealed that the application of CES to attest system containing ASU increases the total profit of power generation units and decreases the total cost of generating power to serve load Demands.
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Multi-Objective Optimization Framework for Electricity and Natural Gas Energy Hubs Under Hydrogen Storage System and Demand Response Program
Operation Planning and Analysis of Energy Storage Systems in Smart Energy Hubs, 2018Co-Authors: Majid Majidi, Sayyad Nojavan, Kazem ZareAbstract:Energy hub is a new concept in the field of energy systems. Using multiple energy carriers as their inputs, these systems are capable of supplying various kinds of energy Demands which seems to be interesting for system operators in the future. Different renewable and non-renewable generation units can be incorporated in gas and electricity energy hub systems to provide sufficient energy for supplying different types of loads. Primary fuel consumed by the units inside hub system is usually natural gas which is procured from gas network. In addition to distributed generation units in the hub system, upper network is also available to provide a reliable power to the electrical load. As expressed above, different energy carriers are involved in the hub energy systems. So, utilization of energy storage system seems to be vital. One of the energy storage systems that can be integrated in the future hub energy systems is hydrogen energy storage system (HSS). In this chapter, performance of hub energy system has been investigated from economic and environmental viewpoints in the presence of hydrogen energy storage system and Demand Response Program (DRP). Four case studies have been evaluated in a sample hub energy system and the results are analyzed for comparison.
Sayyad Nojavan - One of the best experts on this subject based on the ideXlab platform.
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financial risk based scheduling of micro grids accompanied by surveying the influence of the Demand Response Program
IEEE IAS Industrial and Commercial Power Systems Technical Conference, 2021Co-Authors: Tohid Khalili, Sayyad Nojavan, Hamed Ganjeh Ganjehlou, Ali Bidram, Somayeh AsadiAbstract:This paper presents an optimization approach based on mixed-integer Programming (MIP) to maximize the profit of the Microgrid (MG) while minimizing the risk in profit (RIP) in the presence of Demand Response Program (DRP). RIP is defined as the risk of gaining less profit from the desired profit values. The uncertainties associated with the RESs and loads are modeled using normal, Beta, and Weibull distribution functions. The simulation studies are performed in GAMS and MATLAB for 5 random days of a year. Although DRP increases the total profit of the MG, it can also increase the risk. The simulation results show that RIP is reduced when downside risk constraint (DRC) is considered along with DRP implementation. Considering DRC significantly reduces the percentage of the risk while slightly decreasinz the profit.
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probabilistic scheduling of power to gas storage system in renewable energy hub integrated with Demand Response Program
Journal of energy storage, 2020Co-Authors: Zhi Yuan, Sayyad Nojavan, Asad Alizadeh, Kittisak JermsittiparsertAbstract:Abstract Reliable energy supply is a significant challenge for the power system operators. The increase of emerging resources, as well as multi-carrier consumers in energy systems, lead to the integration of multi-carrier energy systems. The energy hub (EH) is one of the central infrastructures which smooths the combination and interdependency of various energy carriers to increase the efficiency and reliability. A novel technology, such as power-to-gas (P2G) storage, is a great option for achieving a renewable resources-based integrated energy system with high efficiency. The P2G storage is regarded as a viable energy storage approach to cover ever-increasing renewable energy resources variability in power system operations. The contribution of this paper is to present an optimal stochastic scheduling problem of EH integrated with P2G storage, combined heat and power (CHP) unit, wind power, boiler, electrical storage, and thermal storage to meet electrical, heat, and gas Demands considering Demand Response Program (DRP). The load shifting based DRP is applied on the electrical loads to reduce the operation cost of the EH. Also, the P2G storage system is used as a new resource that makes a connection between electrical and natural gas networks by converting the power to hydrogen and after that to natural gas through two processes including electrolysis and mechanization, respectively. A scenario-based stochastic approach is applied to handle the uncertainties related to the electrical loads, wind power, and electricity price. The objective of the proposed problem is to minimize the total operation cost of EH, which is modeled as a mixed-integer linear Programming (MILP) problem model. The numerical results are implemented for different cases which demonstrate the effectiveness of the integration of the P2G based multi-carrier energy storage and DRPs on the operation cost of EH. The achieved results confirm the proposed approach by demonstrating the considerable reduction in operating cost of the EHS by approximately 7%.
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reliability based optimal allocation of distributed generations in transmission systems under Demand Response Program
Electric Power Systems Research, 2019Co-Authors: Hadi Chahkandi Nejad, Sayyad Nojavan, Noradin Ghadimi, Saeed Tavakoli, Saman Korjani, Hamed PashaeididaniAbstract:Abstract Rising dependency on reliable electric power has resulted in emerging technologies in power system such as Distributed Generation (DG). Recent developments in Information and Communication Technologies (ICTs), Advanced Metering Infrastructures (AMIs) and Wide Area Measurement Systems (WAMS) will guarantee high penetration of DR Programs in near future. In this paper, optimal allocation of DG units in the transmission systems with the aim of improving reliability of power system is carried out through introducing a placement index. The placement index takes both reliability and economic issues into the account. The impacts of DR Programs on optimal allocation of DG units are also considered. Power system operation in the presence of DR Programs and DG units are implemented through a unit commitment problem and several operational parameters are scrutinized so as to underline the efficiency of the proposed method, considering the complexity of the problem in this paper, population based intelligent search methods have been utilized extensively. The effectiveness of proposed allocation method is illustrated on IEEE RTS-79.
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Optimal Sitting and Sizing of Energy Storage Systems in a Smart Distribution Network Considering Network Constraints and Demand Response Program
2019Co-Authors: Alireza Akbari-dibavar, Sayyad Nojavan, Kazem ZareAbstract:Demand Response Program (DRP) and energy storage systems (ESSs) are two main tools for load management in smart grids. They can make distribution networks more reliable without costly upgrades for substation constructing or lines reinforcement. This work proposes an optimization framework of optimal sitting and sizing of ESSs in a smart distribution network in the presence of DRP and considering renewable energy sources (RESs) effects and network constraints. The proposed objective function includes two terms: 1) minimization of total investment costs of ESSs; 2) minimization of active losses cost and the power purchased from upstream grid and diesel generators. DRP can reduce operation costs by shifting an amount of loads from hours with high Demand to hours with lower Demand and so can reduce network losses and help in peak load shaving process. In order to solve the proposed optimization model, a mixed-integer non-linear Programming (MINLP) model is constructed and solved using DICOPT solver by GAMS optimization software. A modified 33-bus distribution network is considered and the results of three different cases are compared. Finally it can be noted that total cost of network in case 2, with optimal ESS allocation is reduced by 4.9% with compare to the base case, while this reduction is about 20% in case 3 with considering DRPs beside ESS allocation.
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optimal performance of microgrid in the presence of Demand Response exchange a stochastic multi objective model
Computers & Electrical Engineering, 2019Co-Authors: Tohid Khalili, Sayyad Nojavan, Kazem ZareAbstract:Abstract This paper investigates optimal scheduling of the microgrids, including renewable energy sources and conventional generators. Due to the stochastic nature of the wind speed and the sun irradiation, generated power of the wind turbines and photovoltaic are highly uncertain and in the proposed model the uncertainty of the load, price, and renewable energy sources generation are considered by utilizing the normal distribution function. Incentive-based Demand Response Program is implemented in the operating process. The optimal economic status is achieved by maximizing the microgrid's Demand Response Program profit and minimizing the generators cost, and the trading cost. This multi-objective model is solved by the weighted sum technique in order to produce the optimal Pareto solutions and the trade-off solution is selected by applying the fuzzy satisfying method. It is performed on two different microgrids and sensitivity analysis is executed. Results demonstrate that Demand Response Program reduces unused energy in both scenarios.
Noradin Ghadimi - One of the best experts on this subject based on the ideXlab platform.
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reliability based optimal allocation of distributed generations in transmission systems under Demand Response Program
Electric Power Systems Research, 2019Co-Authors: Hadi Chahkandi Nejad, Sayyad Nojavan, Noradin Ghadimi, Saeed Tavakoli, Saman Korjani, Hamed PashaeididaniAbstract:Abstract Rising dependency on reliable electric power has resulted in emerging technologies in power system such as Distributed Generation (DG). Recent developments in Information and Communication Technologies (ICTs), Advanced Metering Infrastructures (AMIs) and Wide Area Measurement Systems (WAMS) will guarantee high penetration of DR Programs in near future. In this paper, optimal allocation of DG units in the transmission systems with the aim of improving reliability of power system is carried out through introducing a placement index. The placement index takes both reliability and economic issues into the account. The impacts of DR Programs on optimal allocation of DG units are also considered. Power system operation in the presence of DR Programs and DG units are implemented through a unit commitment problem and several operational parameters are scrutinized so as to underline the efficiency of the proposed method, considering the complexity of the problem in this paper, population based intelligent search methods have been utilized extensively. The effectiveness of proposed allocation method is illustrated on IEEE RTS-79.
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risk assessment of photovoltaic wind battery grid based large industrial consumer using information gap decision theory
Solar Energy, 2018Co-Authors: Hamid Asadi Bagal, Yashar Nouri Soltanabad, Milad Dadjuo, Karzan Wakil, Noradin GhadimiAbstract:Abstract In this paper, the energy procurement problem for a large electricity consumer is solved under various resources. In this problem, the uncertainty of pool market price is a big challenge to achieve optimal result. In this paper, the information gap decision theory has been proposed to handle the pool market price uncertainty. The results of information gap decision theory are presented in three different strategies for the large consumer. These three strategies include risk-averse, risk-neutral and risk-taker strategies which examine the large consumer risk at various prices in pool market. In addition, the results in all strategies point out the importance of Demand Response Program in reducing the large consumer’s costs. In the risk-neutral strategy, the large consumer cost with and without Demand Response Program is $36,945 and $40,253 respectively. Therefore, the positive impact of Demand Response Program has reduced large consumer cost about 8.2%. Large consumer resistance is 72.5% higher than the without use of Demand Response Program mode in the risk-averse strategy. Finally, large consumer cost is 8% less than the without use of Demand Response Program mode in the risk-taker strategy.
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retracted risk assessment of photovoltaic wind battery grid based large industrial consumer using information gap decision theory
Solar Energy, 2018Co-Authors: Hamid Asadi Bagal, Yashar Nouri Soltanabad, Milad Dadjuo, Karzan Wakil, Noradin GhadimiAbstract:Abstract In this paper, the energy procurement problem for a large electricity consumer is solved under various resources. In this problem, the uncertainty of pool market price is a big challenge to achieve optimal result. In this paper, the information gap decision theory has been proposed to handle the pool market price uncertainty. The results of information gap decision theory are presented in three different strategies for the large consumer. These three strategies include risk-averse, risk-neutral and risk-taker strategies which examine the large consumer risk at various prices in pool market. In addition, the results in all strategies point out the importance of Demand Response Program in reducing the large consumer’s costs. In the risk-neutral strategy, the large consumer cost with and without Demand Response Program is $36,945 and $40,253 respectively. Therefore, the positive impact of Demand Response Program has reduced large consumer cost about 8.2%. Large consumer resistance is 72.5% higher than the without use of Demand Response Program mode in the risk-averse strategy. Finally, large consumer cost is 8% less than the without use of Demand Response Program mode in the risk-taker strategy.
Majid Majidi - One of the best experts on this subject based on the ideXlab platform.
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Multi-Objective Optimization Framework for Electricity and Natural Gas Energy Hubs Under Hydrogen Storage System and Demand Response Program
Operation Planning and Analysis of Energy Storage Systems in Smart Energy Hubs, 2018Co-Authors: Majid Majidi, Sayyad Nojavan, Kazem ZareAbstract:Energy hub is a new concept in the field of energy systems. Using multiple energy carriers as their inputs, these systems are capable of supplying various kinds of energy Demands which seems to be interesting for system operators in the future. Different renewable and non-renewable generation units can be incorporated in gas and electricity energy hub systems to provide sufficient energy for supplying different types of loads. Primary fuel consumed by the units inside hub system is usually natural gas which is procured from gas network. In addition to distributed generation units in the hub system, upper network is also available to provide a reliable power to the electrical load. As expressed above, different energy carriers are involved in the hub energy systems. So, utilization of energy storage system seems to be vital. One of the energy storage systems that can be integrated in the future hub energy systems is hydrogen energy storage system (HSS). In this chapter, performance of hub energy system has been investigated from economic and environmental viewpoints in the presence of hydrogen energy storage system and Demand Response Program (DRP). Four case studies have been evaluated in a sample hub energy system and the results are analyzed for comparison.
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a cost emission framework for hub energy system under Demand Response Program
Energy, 2017Co-Authors: Majid Majidi, Sayyad Nojavan, Kazem ZareAbstract:Abstract Based on the kind of fuel consumed by generation unit, each generation system has different generation costs and emits various types of greenhouse gases like CO 2 , SO 2 and NO 2 to the atmosphere. So, nowadays in the power system scheduling, emission issue has been turned to be an important factor. In this paper, in addition to economic performance, emission problem of energy hub system has been also investigated. Therefore, a multi-objective optimization model has been proposed for cost-environmental operation of energy hub system in the presence of Demand Response Program (DRP). Weighted sum approach has been employed to solve the proposed multi-objective model and fuzzy satisfying technique has been implemented to select the best compromise solution. Implementation of load management Programs presented by DRP shifts some percentage of load from peak periods to off-peak periods to flatten load curve which leads to reduction of total cost and emission of energy hub system. A mixed-integer linear Programming has been used to model the cost-environmental performance problem of energy hub system and then, GAMS optimization software has been utilized to solve it. A sample energy hub system has been studied and the obtained results have been compared to validate the effectiveness of proposed techniques.
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optimal stochastic short term thermal and electrical operation of fuel cell photovoltaic battery grid hybrid energy system in the presence of Demand Response Program
Energy Conversion and Management, 2017Co-Authors: Majid Majidi, Sayyad Nojavan, Kazem ZareAbstract:Abstract In this paper, cost-efficient operation problem of photovoltaic/battery/fuel cell hybrid energy system has been evaluated in the presence of Demand Response Program. Each load curve has off-peak, mid and peak time periods in which the energy prices are different. Demand Response Program transfers some amount of load from peak periods to other periods to flatten the load curve and minimize total cost. So, the main goal is to meet the energy Demand and propose a cost-efficient approach to minimize system’s total cost including system’s electrical cost and thermal cost and the revenue from exporting power to the upstream grid. A battery has been utilized as an electrical energy storage system and a heat storage tank is used as a thermal energy storage system to save energy in off-peak and mid-peak hours and then supply load in peak hours which leads to reduction of cost. The proposed cost-efficient operation problem of photovoltaic/battery/fuel cell hybrid energy system is modeled by a mixed-integer linear Program and solved by General algebraic modeling system optimization software under CPLEX solver. Two case studies are investigated to show the effects of Demand Response Program on reduction of total cost.
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risk based optimal performance of a pv fuel cell battery grid hybrid energy system using information gap decision theory in the presence of Demand Response Program
International Journal of Hydrogen Energy, 2017Co-Authors: Sayyad Nojavan, Majid Majidi, Kazem ZareAbstract:Abstract One of the big challenges that system operators have always dealt with is uncertainty of different parameters in the power systems. In this paper, optimal performance of an on-grid PV/fuel cell/battery hybrid system has been evaluated in the presence of Demand Response Program with considering electrical load uncertainty. Information gap decision theory (IGDT) has been proposed to model the uncertainty of electrical load. Utilizing different strategies obtained through the robustness and opportunity functions, operator will have several options to control the uncertainty. By shifting some percentage of load from peak periods to other periods, DRP flattens load curve and minimizes total cost of hybrid system. A sample system is simulated and the results are compared to validate the proposed techniques.
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a cost emission model for fuel cell pv battery hybrid energy system in the presence of Demand Response Program e constraint method and fuzzy satisfying approach
Energy Conversion and Management, 2017Co-Authors: Sayyad Nojavan, Afshin Najafighalelou, Majid Majidi, Mehrdad Ghahramani, Kazem ZareAbstract:Abstract Optimal operation of hybrid energy systems is a big challenge in power systems. Nowadays, in addition to the optimum performance of energy systems, their pollution issue has been a hot topic between researchers. In this paper, a multi-objective model is proposed for economic and environmental operation of a battery/fuel cell/photovoltaic (PV) hybrid energy system in the presence of Demand Response Program (DRP). In the proposed paper, the first objective function is minimization of total cost of hybrid energy system. The second objective function is minimization of total CO 2 emission which is in conflict with the first objective function. So, a multi-objective optimization model is presented to model the hybrid system’s optimal and environmental performance problem with considering DRP. The proposed multi-objective model is solved by e-constraint method and then fuzzy satisfying technique is employed to select the best possible solution. Also, positive effects of DRP on the economic and environmental performance of hybrid system are analyzed. A mixed-integer linear Program is used to simulate the proposed model and the obtained results are compared with weighted sum approach to show the effectiveness of proposed method.
Hamid Asadi Bagal - One of the best experts on this subject based on the ideXlab platform.
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risk assessment of photovoltaic wind battery grid based large industrial consumer using information gap decision theory
Solar Energy, 2018Co-Authors: Hamid Asadi Bagal, Yashar Nouri Soltanabad, Milad Dadjuo, Karzan Wakil, Noradin GhadimiAbstract:Abstract In this paper, the energy procurement problem for a large electricity consumer is solved under various resources. In this problem, the uncertainty of pool market price is a big challenge to achieve optimal result. In this paper, the information gap decision theory has been proposed to handle the pool market price uncertainty. The results of information gap decision theory are presented in three different strategies for the large consumer. These three strategies include risk-averse, risk-neutral and risk-taker strategies which examine the large consumer risk at various prices in pool market. In addition, the results in all strategies point out the importance of Demand Response Program in reducing the large consumer’s costs. In the risk-neutral strategy, the large consumer cost with and without Demand Response Program is $36,945 and $40,253 respectively. Therefore, the positive impact of Demand Response Program has reduced large consumer cost about 8.2%. Large consumer resistance is 72.5% higher than the without use of Demand Response Program mode in the risk-averse strategy. Finally, large consumer cost is 8% less than the without use of Demand Response Program mode in the risk-taker strategy.
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retracted risk assessment of photovoltaic wind battery grid based large industrial consumer using information gap decision theory
Solar Energy, 2018Co-Authors: Hamid Asadi Bagal, Yashar Nouri Soltanabad, Milad Dadjuo, Karzan Wakil, Noradin GhadimiAbstract:Abstract In this paper, the energy procurement problem for a large electricity consumer is solved under various resources. In this problem, the uncertainty of pool market price is a big challenge to achieve optimal result. In this paper, the information gap decision theory has been proposed to handle the pool market price uncertainty. The results of information gap decision theory are presented in three different strategies for the large consumer. These three strategies include risk-averse, risk-neutral and risk-taker strategies which examine the large consumer risk at various prices in pool market. In addition, the results in all strategies point out the importance of Demand Response Program in reducing the large consumer’s costs. In the risk-neutral strategy, the large consumer cost with and without Demand Response Program is $36,945 and $40,253 respectively. Therefore, the positive impact of Demand Response Program has reduced large consumer cost about 8.2%. Large consumer resistance is 72.5% higher than the without use of Demand Response Program mode in the risk-averse strategy. Finally, large consumer cost is 8% less than the without use of Demand Response Program mode in the risk-taker strategy.