Optimal scheduling of multi-microgrids with power to hydrogen considering federated demand response

被引:6
作者
Hu, Qinran [1 ]
Zhou, Yufeng [1 ]
Ding, Haohui [1 ]
Qin, Panhao [1 ]
Long, Yu [2 ]
机构
[1] Southeast Univ, Sch Elect Engn, Nanjing, Peoples R China
[2] State Grid Jiangsu Elect Power Co Ltd, Nanjing, Peoples R China
关键词
multi-microgrids; power to hydrogen; demand response; microgrid interaction; energy management; ENERGY MANAGEMENT; SYSTEM; DISPATCH; STORAGE;
D O I
10.3389/fenrg.2022.1002045
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
Hydrogen is regarded as a promising fuel in the transition to clean energy. Nevertheless, as the demand for hydrogen increases, some microgrids equipped with P2H (MGH) will encounter the issue of primary energy deficiency. Meanwhile, some microgrids (MGs) face the difficulty of being unable to consume surplus energy locally. Hence, we interconnect MGs with different energy characteristics and then establish a collaborative scheduling model of multi-microgrids (MMGs). In this model, a federated demand response (FDR) program considering predictive mean voting is designed to coordinate controllable loads of electricity, heat, and hydrogen in different MGs. With the coordination of FDR, the users' satisfaction and comfort in each MG are kept within an acceptable range. To further adapt to an actual working condition of the microturbine (MT) in MGH, a power interaction method is proposed to maintain the operating power of the MT at the optimum load level and shave peak and shorten the operating periods of MT. In the solution process, the sequence operation theory is utilized to deal with the probability density of renewable energy. A series of case studies on a test system of MMG demonstrate the effectiveness of the proposed method.
引用
收藏
页数:13
相关论文
共 36 条
[1]   High voltage direct current modelling in optimal power flows [J].
Ambriz-Perez, H. ;
Acha, E. ;
Fuerte-Esquivel, C. R. .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2008, 30 (03) :157-168
[2]  
[Anonymous], 2012, IEEE EnergyTech, DOI DOI 10.1109/ENERGYTECH.2012.6304651
[3]  
[Anonymous], 2019, Future of wind: Deployment, investment, technology, grid integration and socio-economic aspects
[4]   Energy Management in Multi-Microgrid Systems-Development and Assessment [J].
Arefifar, Seyed Ali ;
Ordonez, Martin ;
Mohamed, Yasser Abdel-Rady I. .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2017, 32 (02) :910-922
[5]   Energy resources of the 21st century: problems and forecasts. Can renewable energy sources replace fossil fuels? [J].
Arutyunov, Vladimir S. ;
Lisichkin, Georgiy . .
RUSSIAN CHEMICAL REVIEWS, 2017, 86 (08) :777-804
[6]   Energy, environmental and economic evaluations of a CCHP system driven by Stirling engine with helium and hydrogen as working gases [J].
Chahartaghi, Mahmood ;
Sheykhi, Mohammad .
ENERGY, 2019, 174 :1251-1266
[7]   Smart energy management algorithm for load smoothing and peak shaving based on load forecasting of an island's power system [J].
Chapaloglou, Spyridon ;
Nesiadis, Athanasios ;
Iliadis, Petros ;
Atsonios, Konstantinos ;
Nikolopoulos, Nikos ;
Grammelis, Panagiotis ;
Yiakopoulos, Christos ;
Antoniadis, Ioannis ;
Kakaras, Emmanuel .
APPLIED ENERGY, 2019, 238 :627-642
[8]   Stochastic energy management for a renewable energy based microgrid considering battery, hydrogen storage, and demand response [J].
Eghbali, Nazanin ;
Hakimi, Seyed Mehdi ;
Hasankhani, Arezoo ;
Derakhshan, Ghasem ;
Abdi, Babak .
SUSTAINABLE ENERGY GRIDS & NETWORKS, 2022, 30
[9]   Discovery and geological knowledge of the large deep coal-formed Qingyang Gas Field, Ordos Basin, NW China [J].
Fu Jinhua ;
Wei Xinshan ;
Luo Shunshe ;
Zuo Zhifeng ;
Zhou Hu ;
Liu Baoxian ;
Kong Qingfen ;
Zhan Sha ;
Nan Junxiang .
PETROLEUM EXPLORATION AND DEVELOPMENT, 2019, 46 (06) :1111-1126
[10]  
Hafner M., 2020, The Geopolitics of the Global Energy Transition, DOI [10.1007/978-3-030-39066-2, DOI 10.1007/978-3-030-39066-27]