Day-Ahead scheduling of centralized energy storage system in electrical networks by proposed stochastic MILP-Based bi-objective optimization approach

被引:24
作者
Eslahi, M. [1 ]
Nematollahi, A. Foroughi [1 ]
Vahidi, B. [1 ]
机构
[1] Amirkabir Univ Technol, Dept Elect Engn, Tehran 1591634311, Iran
关键词
Energy storage system scheduling; Stochastic bi-objective optimization; Scenario-based decision-making method; Uncertainty modeling; DEMAND-SIDE; WIND; GENERATION; ALLOCATION; UNCERTAINTY; MANAGEMENT; COST;
D O I
10.1016/j.epsr.2020.106915
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
Recently, employing environmentally-friendly devices such as Energy Storage Systems (EESs) and Renewable Energy Resources (RERs) has been one of the remarkable ways to reduce electricity generation cost as well as environmental issues. Due to the stochastic nature of injected power through the RERs resulting from variable weather conditions, serving the devices and systems to the electrical grid in order to alleviate the output fluctuations of these resources should be taken into consideration. Installation of energy storage units can be one of the applicable ways that lessens the power variations of RESs by exchanging the required real power into the network through a day. In the current paper, the day-ahead scheduling of ESS in the presence of wind farm uncertainty has been obtained by implementing the proposed stochastic Mixed Integer Linear Programming (MILP)-based bi-objective optimization approach. The suggested objective functions are the daily electricity generation cost and emission pollutants released through the thermal power plants. Based on the presented framework, a simultaneous cost-emission minimization scheme is carried out by deriving Pareto optimal solutions by epsilon-constraint technique. It is noteworthy that one strategy is required to determine optimal ESS operation according to the decision maker's point of view. Thus, the Fuzzy satisfying method as a selection criterion has been exploited to obtain the appropriate solution by compromising between the objective functions. The case study is the IEEE-30BUS system. According to simulation results derived from implementing the proposed framework, it has been concluded that during off-peak periods of the day, the hourly electricity generation cost and emission are increased. On the other hand, the hourly cost and emission have been reduced during on-peak hours. The daily cost and emission are reduced by employing the energy storage unit. Moreover, peak-shaving and peak-shifting resulting from the suitable ESS operation are illustrated in this paper.
引用
收藏
页数:13
相关论文
共 34 条
[1]   A comprehensive review on uncertainty modeling techniques in power system studies [J].
Aien, Morteza ;
Hajebrahimi, Ali ;
Fotuhi-Firuzabad, Mahmud .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2016, 57 :1077-1089
[2]   MPC-based approach for online demand side and storage system management in market based wind integrated power systems [J].
Arasteh, Farzad ;
Riahy, Gholam H. .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2019, 106 :124-137
[3]   Towards efficient energy management in smart grids considering microgrids with day-ahead energy forecasting [J].
Aslam, Sheraz ;
Khalid, Adia ;
Javaid, Nadeem .
ELECTRIC POWER SYSTEMS RESEARCH, 2020, 182
[4]   Optimal ESS Allocation and Load Shedding for Improving Distribution System Reliability [J].
Awad, Ahmed S. A. ;
EL-Fouly, Tarek H. M. ;
Salama, Magdy M. A. .
IEEE TRANSACTIONS ON SMART GRID, 2014, 5 (05) :2339-2349
[5]   Energy Management Strategy in Dynamic Distribution Network Reconfiguration Considering Renewable Energy Resources and Storage [J].
Azizivahed, Ali ;
Arefi, Ali ;
Ghavidel, Sahand ;
Shafie-khah, Miadreza ;
Li, Li ;
Zhang, Jiangfeng ;
Catalao, Joao P. S. .
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2020, 11 (02) :662-673
[6]   Tri-objective scheduling of residential smart electrical distribution grids with optimal joint of responsive loads with renewable energy sources [J].
Chamandoust, Heydar ;
Derakhshan, Ghasem ;
Hakimi, Seyed Mehdi ;
Bahramara, Salah .
JOURNAL OF ENERGY STORAGE, 2020, 27
[7]   Comparison of multi-objective optimization methodologies for engineering applications [J].
Chiandussi, G. ;
Codegone, M. ;
Ferrero, S. ;
Varesio, F. E. .
COMPUTERS & MATHEMATICS WITH APPLICATIONS, 2012, 63 (05) :912-942
[8]   A Linear-Programming Approximation of AC Power Flows [J].
Coffrin, Carleton ;
Van Hentenryck, Pascal .
INFORMS JOURNAL ON COMPUTING, 2014, 26 (04) :718-734
[9]   Two-Stage Optimization of Battery Energy Storage Capacity to Decrease Wind Power Curtailment in Grid-Connected Wind Farms [J].
Dui, Xiaowei ;
Zhu, Guiping ;
Yao, Liangzhong .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2018, 33 (03) :3296-3305
[10]   Stochastic Capacity Expansion Planning of Remote Microgrids With Wind Farms and Energy Storage [J].
Hajipour, Ehsan ;
Bozorg, Mokhtar ;
Fotuhi-Firuzabad, Mahmud .
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2015, 6 (02) :491-498