Risk-based energy management of renewable-based microgrid using information gap decision theory in the presence of peak load management

被引:75
作者
Mehdizadeh, Ali [1 ]
Taghizadegan, Navid [1 ]
Salehi, Javad [1 ]
机构
[1] Azarbaijan Shahid Madani Univ, Dept Elect Engn, Tabriz, Iran
关键词
Bidding strategy; Microgrid (MG); Renewable energy sources (RESs); Demand response program (DRP); Information gap decision theory (IGDT); OPTIMAL BIDDING STRATEGY; DEMAND RESPONSE; NETWORKED MICROGRIDS; GENERATION STATION; OFFERING STRATEGY; STORAGE SYSTEM; MARKET; OPTIMIZATION; CONSUMER; PROCUREMENT;
D O I
10.1016/j.apenergy.2017.11.084
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The operator of renewable-based microgrid (MG) tries to supply the local load with the lowest cost from the alternative energy sources containing upstream grid, micro-turbines (MTs), renewable energy sources (RESs) (photovoltaic (PV) systems and wind-turbines (WT)) and energy storage system (ESS). To purchase power from upstream grid, the optimal bidding curve of MG should be prepared to bid the market operator. Therefore, this paper proposes an information gap decision theory (IGDT) to obtain the bidding strategy of MG. IGDT includes the robustness and opportunity functions for upstream grid price uncertainty modeling. MG can consider the robustness decision (risk-averse) or the opportunity decision (risk-taking) under uncertainty environment. Also, the operator of MG uses the demand response program (DRP) which purpose is to reduce the energy procurement cost. Meanwhile, the proposed stochastic model considers the uncertainty modeling of local load and RESs output power by using a scenario stochastic model. To show the capability of proposed approach, two cases considering without and with DRP are studied. Beneficial results of DRP are utilized in case B, which the operation cost in case B is% 4.6 less than case A.
引用
收藏
页码:617 / 630
页数:14
相关论文
共 36 条
  • [1] RETRACTED: Energy storage system and demand response program effects on stochastic energy procurement of large consumers considering renewable generation (Retracted article. See vol. 14, pg. 6040, 2020)
    Aalami, Habib Allah
    Nojavan, Sayyad
    [J]. IET GENERATION TRANSMISSION & DISTRIBUTION, 2016, 10 (01) : 107 - 114
  • [2] A multi-agent based energy management solution for integrated buildings and microgrid system
    Anvari-Moghaddam, Amjad
    Rahimi-Kian, Ashkan
    Mirian, Maryam S.
    Guerrero, Josep M.
    [J]. APPLIED ENERGY, 2017, 203 : 41 - 56
  • [3] Low complexity energy management strategy for grid profile smoothing of a residential grid-connected microgrid using generation and demand forecasting
    Arcos-Aviles, Diego
    Pascual, Julio
    Guinjoan, Francesc
    Marroyo, Luis
    Sanchis, Pablo
    Marietta, Martin P.
    [J]. APPLIED ENERGY, 2017, 205 : 69 - 84
  • [4] Ben-Haim Y., 2001, INFORM GAP DECISION
  • [5] Brooke Anthony., 1998, A User's Guide
  • [6] A robust optimization approach to hybrid microgrid operation using ensemble weather forecasts
    Craparo, Emily
    Karatas, Mumtaz
    Singham, Dashi I.
    [J]. APPLIED ENERGY, 2017, 201 : 135 - 147
  • [7] Optimal Bidding Strategy for Microgrids Considering Renewable Energy and Building Thermal Dynamics
    Duong Tung Nguyen
    Le, Long Bao
    [J]. IEEE TRANSACTIONS ON SMART GRID, 2014, 5 (04) : 1608 - 1620
  • [8] Optimal bidding in a Day-Ahead energy market for Micro Grid under uncertainty in renewable energy production
    Ferruzzi, Gabriella
    Cervone, Guido
    Delle Monache, Luca
    Graditi, Giorgio
    Jacobone, Francesca
    [J]. ENERGY, 2016, 106 : 194 - 202
  • [9] MOD-DR: Microgrid optimal dispatch with demand response
    Jin, Ming
    Feng, Wei
    Liu, Ping
    Marnay, Chris
    Spanos, Costas
    [J]. APPLIED ENERGY, 2017, 187 : 758 - 776
  • [10] Hierarchical microgrid energy management in an office building
    Jin, Xiaolong
    Wu, Jianzhong
    Mu, Yunfei
    Wang, Mingshen
    Xu, Xiandong
    Jia, Hongjie
    [J]. APPLIED ENERGY, 2017, 208 : 480 - 494