Open AccessOptimal Resources Planning of Residential Complex Energy System in a Day-ahead Market Based on Invasive Weed Optimization Algorithm
Author(s) -
Pourya Ahmadi,
Mohammad Hassan Nazari
Publication year - 2017
Publication title -
engineering, technology and applied science research/engineering, technology and applied science research
Language(s) - English
Resource type - Journals
eISSN - 2241-4487
pISSN - 1792-8036
DOI - 10.48084/etasr.1324
Subject(s) - schedule , photovoltaic system , grid , computer science , environmental economics , electricity , smart grid , electric power system , energy management system , operations research , energy (signal processing) , mathematical optimization , energy management , engineering , economics , electrical engineering , power (physics) , statistics , physics , geometry , mathematics , quantum mechanics , operating system
This paper deals with optimal resources planning in a residential complex energy system, including FC (fuel cell), PV (Photovoltaic) panels and the battery. A day-ahead energy management system (EMS) based on invasive weed optimization (IWO) algorithm is defined for managing different resources to determine an optimal operation schedule for the energy resources at each time interval to minimize the operation cost of a smart residential complex energy system. Moreover, in this paper the impacts of the sell to grid and purchase from grid are also considered. All practical constraints of the each energy resources and utility policies are taken into account. Moreover, sensitivity analysis are conducted on electricity prices and sell to grid factor (SGF), in order to improve understanding the impact of key parameters on residential CHP systems economy. It is shown that proposed system can meet all electrical and thermal demands with economic point of view. Also enhancement of electricity price leads to substantial growth in utilization of proposed CHP system.