Stochastic electricity market model in networked microgrids considering demand response programs and renewable energy sources

被引:71
作者
Bahmani, Ramin [1 ]
Karimi, Hamid [1 ]
Jadid, Shahram [1 ]
机构
[1] Iran Univ Sci & Technol, Sch Elect Engn, Tehran, Iran
关键词
Demand response; Electricity market; Microgrid scheduling; Multi-microgrids; Stochastic optimization; MULTI-MICROGRIDS; OPTIMAL OPERATION; STORAGE SYSTEM; MANAGEMENT; OPTIMIZATION; GENERATION; TRANSACTIONS; INTEGRATION; RESOURCES; DISPATCH;
D O I
10.1016/j.ijepes.2019.105606
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, a cooperative market mechanism is proposed to define the energy transactions and market price in multi-microgrids (MMGs). The proposed model can be used for both the grid-connected and isolated MMG as well as models with several MG owners. We use a cooperative approach that guarantees the existence of the optimal solution, while the Nash equilibrium points cannot ensure the Pareto optimality of the solution in the competitive approaches. Microgrids (MGs) send their bids/offers to the market operator, and the devoted energy will be announced to MGs in order to set the production of their resources. Various energy production units such as renewable energy resources (Photovoltaic, and wind), dispatchable energy resources, Energy Storage Systems (ESS), and demand response program have been taken into account. Moreover, an incentive-based demand response program motivates the consumers to take part in the market and benefit from the deployed market. Scenario generation and reduction methods are used to consider various uncertainties in the power system. The proposed model is formulated as a Mixed Integer Linear Programming (MILP) and solved by GAMS software. Several case studies are tested and the simulation results show the efficiency of the proposed model.
引用
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页数:14
相关论文
共 41 条
[1]   Evaluation of loss minimization on the energy management of multi-microgrid based smart distribution network in the presence of emission constraints and clean productions [J].
Aghdam, Farid Hamzeh ;
Ghaemi, Sina ;
Kalantari, Navid Taghizadegan .
JOURNAL OF CLEANER PRODUCTION, 2018, 196 :185-201
[2]  
[Anonymous], 2002, Market Operations in Electric Power Systems
[3]   A Decentralized Renewable Generation Management and Demand Response in Power Distribution Networks [J].
Bahrami, Shahab ;
Amini, M. Hadi ;
Shafie-Khah, Miadreza ;
Catalao, Joao P. S. .
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2018, 9 (04) :1783-1797
[4]   Stochastic dominant-subordinate-interactive scheduling optimization for interconnected microgrids with considering wind-photovoltaic-based distributed generations under uncertainty [J].
Chen, Yizhong ;
He, Li ;
Li, Jing .
ENERGY, 2017, 130 :581-598
[5]   Optimal Bidding Strategy for Microgrids Considering Renewable Energy and Building Thermal Dynamics [J].
Duong Tung Nguyen ;
Le, Long Bao .
IEEE TRANSACTIONS ON SMART GRID, 2014, 5 (04) :1608-1620
[6]   A Multiagent-Based Game-Theoretic and Optimization Approach for Market Operation of Multimicrogrid Systems [J].
Esfahani, Mohammad Mahmoudian ;
Hariri, Abla ;
Mohammed, Osama A. .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2019, 15 (01) :280-292
[7]   A novel stochastic energy management of a microgrid with various types of distributed energy resources in presence of demand response programs [J].
Farsangi, Alireza SoltaniNejad ;
Hadayeghparast, Shahrzad ;
Mehdinejad, Mehdi ;
Shayanfar, Heidarali .
ENERGY, 2018, 160 :257-274
[8]   A Market Mechanism to Quantify Emergency Energy Transactions Value in a Multi-Microgrid System [J].
Farzin, Hossein ;
Ghorani, Rahim ;
Fotuhi-Firuzabad, Mahmud ;
Moeini-Aghtaie, Moein .
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2019, 10 (01) :426-437
[9]   A Stochastic Multi-Objective Framework for Optimal Scheduling of Energy Storage Systems in Microgrids [J].
Farzin, Hossein ;
Fotuhi-Firuzabad, Mahmud ;
Moeini-Aghtaie, Moein .
IEEE TRANSACTIONS ON SMART GRID, 2017, 8 (01) :117-127
[10]   Decentralized Energy Management for Networked Microgrids in Future Distribution Systems [J].
Gao, Hongjun ;
Liu, Junyong ;
Wang, Lingfeng ;
Wei, Zhenbo .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2018, 33 (04) :3599-3610