Effect of demand response program of loads in cost optimization of microgrid considering uncertain parameters in PV/WT, market price and load demand. (1st March 2020)

• Record Type: Journal Article
• Authors: Rajamand, Sahbasadat
• Is Part Of: Energy. Volume 194(2020)
• Publication Date: 2020-03-01
• Subjects: Demand response -- Energy storage system -- Point estimation method -- Market price -- Heat-electrical demand -- Cost reduction; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2020.116917
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: Using renewable distributed generators as photovoltaic cell and wind turbine in microgrid includes green and free energy exploitation. However, uncertainty of generated energy from these resources may underestimate energy planning for load demands. The uncertainty may be from market price and load demand in addition to the renewable distributed generators. To overcome the uncertainty challenge, energy storage system and demand response program with cooperation of users on demand side are applied as solutions to plan the energy flow in microgrid to guarantee the voltage stability and essential load supporting. In this paper, price-based demand response for industrial, commercial and house loads are considered in which the effect of demand response on the cost reduction is analyzed and discussed. Electrical and heat demand are considered in the microgrid while uncertainty of renewable distributed generators, market price and load demand are modeled and estimated by point estimation method. Simulation results with three scenarios are performed with and without price-based demand response program and results are compared. As shown in simulation results, demand response has highly reduced total cost (22–28% related to the case without that) where voltage dip (maximum 1.5%) and power deviation (maximum 1.33%) are also improved in the microgird. Highlights: Price-based DR program of different loads in the cost optimization. Analysis of profit profile of traded energy between MG and main grid. Point estimation method to model four uncertainty parameters as wind speed, solar radiation, market price and load demand. Applying transferable house loads in DR program and final cost function.