Optimal sizing and siting of smart microgrid components under high renewables penetration considering demand response

作     者：Hakimi, Seyed Mehdi Hasankhani, Arezoo Shafie-khah, Miadreza Catalao, Joao P. S. 

作者机构：Islamic Azad Univ Dept Elect Engn Damavand Branch Damavand Iran Amirkabir Univ Technol Dept Elect Engn Tehran Iran Univ Vaasa Sch Technol & Innovat Vaasa 65200 Finland Univ Porto Fac Engn P-4200465 Porto Portugal INESC TEC P-4200465 Porto Portugal 

出 版 物：《IET RENEWABLE POWER GENERATION》 (IET. Renew. Power Gener.)

年 卷 期：2019年第13卷第10期

页      面：1809-1822页

核心收录：

学科分类：0820[工学-石油与天然气工程] 0808[工学-电气工程] 08[工学] 

基　　金：research council of Islamic Azad University, Damavand, Iran FEDER funds through COMPETE 2020 Portuguese funds through FCT [POCI-01-0145-FEDER-029803 (02/SAICT/2017), POCI-01-0145-FEDER-006961 (UID/EEA/50014/2019)] 

主　　题：energy storage wind turbines smart power grids renewable energy sources battery storage plants photovoltaic power systems optimisation distributed power generation hybrid power systems particle swarm optimisation energy management systems smart microgrid components high renewables penetration demand response size place different components microgrids including renewable energy resources wind speed solar irradiance load growth Ekbatan residential complex pilot case study Ekbatan complex smart MGs multiobjective optimisation problem RERs uncertainties minimizing power loss particle swarm optimisation algorithm different constraints energy storage systems capacity controllable loads wind turbine PV fuel cell /hydrogen tank MGs system 

摘      要：The purpose of this article is to determine the size and place of different components in microgrids (MGs) including renewable energy resources (RERs). Various factors like reliability, the uncertainty of wind speed, solar irradiance, load, and load growth are considered. The Ekbatan residential complex is studied as the pilot case study placed in Tehran, Iran. Ekbatan complex has three separate sets of buildings called phase 1, 2, and 3 considered as smart MGs. The multi-objective optimisation problem is solved considering RERs uncertainties, improving reliability and power quality and minimizing power loss by particle swarm optimisation algorithm. Different constraints in terms of voltage, frequency, resources, and energy storage systems (ESSs) capacity are taken into consideration. The effect of load growth, photovoltaic (PV) and ESSs placement, changing the capital cost of RERs, and demand response of controllable loads are studied on optimal sizing and siting. The proposed method is tested on a wind turbine/PV/fuel cell (FC)/hydrogen tank MGs system and the optimal sizing and siting of mentioned sources could decelerate the rate of increase in the total cost of MG considering the load growth.