Modeling and analysis of a microgrid considering the uncertainty in renewable energy resources, energy storage systems and demand management in electrical retail market. (January 2021)

• Record Type: Journal Article
• Authors: Wang, Chong; Zhang, Zheng; Abedinia, Oveis; Farkoush, Saeid Gholami
• Is Part Of: Journal of energy storage. Volume 33(2021)
• Publication Date: 2021-01
• Subjects: Demand management -- Particle swarm optimization (PSO) -- Energy storage system (ESS) -- Electrical market price -- Price reduction -- Renewable energy sources' uncertainty; Energy storage -- Periodicals; Energy storage -- Research -- Periodicals; 621.3126
• DOI: 10.1016/j.est.2020.102111
• Languages: English
• ISSNs: 2352-152X

Abstract

Highlights: Presenting a new implementation of dispatchable and undispatchable DGs, ESS and DR. Utilizing ESS will lead to stability, energy quality and peak backup improvement. DSM strategy is used to improve energy quality and network voltage stability. The primal cost function is presented based on the market price, RES DGs and ESS systems. Stochastic modeling of RESs using PDF will lead to increased problem accuracy. Considering heat and electrical demand with fuel cell (FC) existence in the MG. Abstract: The renewable energy resources (RESs) are naturally generated such as wind turbine, photovoltaic cell and etc., which can be used in microgrids. In this paper, a heuristic method has been proposed for load demand management based on the produced power and the forecasted market clearing price in which the uncertain parameters of uncontrolled resources and load demand is taken into consideration. With the intermittent output of RESs due to the uncertainty in solar irradiation and wind speed, the forecasting unit will inform the operator on the power production levels in the upcoming 24 h. The energy storage system (ESS) is added to the network based on the modeling of demand management to induce operation costs of the microgrid (MG). Afterwards, the optimization unit utilizes a new decision-making criterion and the particle swarm optimization (PSO) method to define generation schedule and resources' economic dispatch to reduce consumers' costs. Moreover, the proposed model is used to guarantee voltage stability and basic load support. The simulation results are presented by three scenarios with and without price-based demand response. The comparisons among the results illustrate the effectiveness of demand management on system costs. As shown in simulation results, demand response has highly reduced total cost (20–30% related to the case without that) where voltage dip (maximum 1.4%) and power deviation (maximum 1.25%) are also improved in the microgrid.