A hybrid storage-wind virtual power plant (VPP) participation in the electricity markets: A self-scheduling optimization considering price, renewable generation, and electric vehicles uncertainties

被引:107
作者
Alahyari, Arman [1 ,2 ]
Ehsan, Mehdi [1 ]
Mousavizadeh, MirSaeed [3 ]
机构
[1] Sharif Univ Technol, Dept Elect Engn, Tehran, Iran
[2] Skolkovo Inst Sci & Technol Skoltech, Ctr Energy Syst, Moscow, Russia
[3] Tarbiat Modares Univ, Fac Elect & Comp Engn, Tehran, Iran
关键词
Electric vehicle (EV); Energy storage; Virtual power plant (VPP); Uncertainty; ENERGY-STORAGE; BATTERY DEGRADATION; SYSTEMS; IMPACT; PREDICTION; ALGORITHM; MODEL; STATE;
D O I
10.1016/j.est.2019.100812
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 fast growth of technologies most of which depend on natural sources of energy has resulted in a huge consumption of fossil fuels. In this regard, many solutions have been suggested to alleviate the side effects such as air pollution and global warming. Among these solutions, mobile storages like electric vehicles (EVs) and renewable generations, have grown significantly due to being more applicable. But uncoordinated operation and uncertain nature of these distributed energy resources (DERs) can bring forward new challenges and issues to the operators of power system. Thus, in many cases it is more efficient to co-operate them in a hybrid system. In this study, we address a virtual power plant (VPP) that aggregates the EVs charging and discharging power into electricity markets, day-ahead (DA) energy and reserve, while enjoying wind power generation capacity. Not only we consider uncertainty of electricity market prices and the amount of energy produced by wind generation but also we present a novel EV uncertainty modelling in which we introduce a new facet that incorporates all the uncertain parameters of these vehicles into the whole stochastic optimization model along with other uncertainty sources. The proposed method can be utilized in case of a VPP that has wind generation and parking-lots accommodating EVs to optimally schedule its assets prior to participating in the electricity markets. The theoretical approach in developing the proposed self-scheduling model and its applicability is verified through several numerical simulations.
引用
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页数:12
相关论文
共 45 条
[1]   Coordinated operation of electric vehicle charging and wind power generation as a virtual power plant: A multi-stage risk constrained approach [J].
Abbasi, Mohammad Hossein ;
Taki, Mehrdad ;
Rajabi, Amin ;
Li, Li ;
Zhang, Jiangfeng .
APPLIED ENERGY, 2019, 239 :1294-1307
[2]   Towards collaborative Virtual Power Plants: Trends and convergence [J].
Adu-Kankam, Kankam O. ;
Camarinha-Matos, Luis M. .
SUSTAINABLE ENERGY GRIDS & NETWORKS, 2018, 16 :217-230
[3]   Incorporating Customer Reliability Cost in PEV Charge Scheduling Schemes Considering Vehicle-to-Home Capability [J].
Alahyari, Arman ;
Fotuhi-Firuzabad, Mahmud ;
Rastegar, Mohammad .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2015, 64 (07) :2783-2791
[4]   Stochastic scheduling of aggregators of plug-in electric vehicles for participation in energy and ancillary service markets [J].
Alipour, Manijeh ;
Mohammadi-Ivatloo, Behnam ;
Moradi-Dalvand, Mohammad ;
Zare, Kazem .
ENERGY, 2017, 118 :1168-1179
[5]  
Amini M, 2018, 2018 POWER SYSTEMS COMPUTATION CONFERENCE (PSCC)
[6]  
[Anonymous], 2018, OMIE MARKET DATA
[7]   PEV Charging Profile Prediction and Analysis Based on Vehicle Usage Data [J].
Ashtari, Ali ;
Bibeau, Eric ;
Shahidinejad, Soheil ;
Molinski, Tom .
IEEE TRANSACTIONS ON SMART GRID, 2012, 3 (01) :341-350
[8]  
Baringo A, 2018, 2018 POWER SYSTEMS COMPUTATION CONFERENCE (PSCC)
[9]   A linear programming approach for battery degradation analysis and optimization in offgrid power systems with solar energy integration [J].
Bordin, Chiara ;
Anuta, Harold Oghenetejiri ;
Crossland, Andrew ;
Gutierrez, Isabel Lascurain ;
Dent, Chris J. ;
Vigo, Daniele .
RENEWABLE ENERGY, 2017, 101 :417-430
[10]   Electrical energy storage in highly renewable European energy systems: Capacity requirements, spatial distribution, and storage dispatch [J].
Cebulla, F. ;
Naegler, T. ;
Pohl, M. .
JOURNAL OF ENERGY STORAGE, 2017, 14 :211-223