Impact Analysis of Demand Response Intensity and Energy Storage Size on Operation of Networked Microgrids

Abstract

Integration of demand response (DR) programs and battery energy storage system (BESS) in microgrids are beneficial for both microgrid owners and consumers. The intensity of DR programs and BESS size can alter the operation of microgrids. Meanwhile, the optimal size for BESS units is linked with the uncertainties associated with renewable energy sources and load variations. Similarly, the participation of enrolled customers in DR programs is also uncertain and, among various other factors, uncertainty in market prices is a major cause. Therefore, in this paper, the impact of DR program intensity and BESS size on the operation of networked microgrids is analyzed while considering the prevailing uncertainties. The uncertainties associated with forecast load values, output of renewable generators, and market price are realized via the robust optimization method. Robust optimization has the capability to provide immunity against the worst-case scenario, provided the uncertainties lie within the specified bounds. The worst-case scenario of the prevailing uncertainties is considered for evaluating the feasibility of the proposed method. The two representative categories of DR programs, i.e., price-based and incentive-based DR programs are considered. The impact of change in DR intensity and BESS size on operation cost of the microgrid network, external power trading, internal power transfer, load profile of the network, and state-of-charge (SOC) of battery energy storage system (BESS) units is analyzed. Simulation results are analyzed to determine the integration of favorable DR program and/or BESS units for different microgrid networks with diverse objectives.

Impact Analysis of Survivability-Oriented Demand Response on Islanded Operation of Networked Microgrids with High Penetration of Renewables

“…Various EMS architectures are available in the literature, each having their own merits and demerits. Among various types of EMS architectures, cooperative networked microgrid communities have gained popularity due to their merits, as mentioned in [24,25]. Especially, for islanded microgrids due to their ability to better utilize system level resources and ability to assist the on-emergency microgrids of the network.…”

“…The net non-critical load on X-side microgrid at t can be computed using Equation (23). The maximum amount of load which can be shifted from any time interval t is constrained by the amount of available shiftable load at that interval, as given by Equation (24). Finally, Equation (25) indicates that load shifting to any interval having load shedding is not allowed.…”

Location and Sizing of Battery Energy Storage Units in Low Voltage Distribution Networks

“…The integration of BESSs with appropriate control strategies has been shown to be able to improve the frequency stability [6]. At the distribution system level, a BESS is mainly used for enhancing the grid integration of RES by mitigating the effects of the uncertainty on load and distributed generation [7,8], improving the distribution system reliability by avoiding operations close to the line thermal limits and thus more exposed to the risk of protection trips [9], enhancing the quality of the supply with relatively high-power and low-energy solutions [10], reducing the need for grid expansion, shaving the power demand peaks through load shifting or load leveling [9], optimizing the energy transaction costs [11], and integrating BESSs with the demand response in microgrid applications [12]. In [13], a distinction is made between a centralized BESS (that participates in reducing the demand deviation, avoiding the reverse power flow and correcting the power factor), and a distributed BESS (that aims at annual energy loss reduction, reduction of the demand deviation, and improvement of the voltage profile).…”

Impacts of Responsive Loads and Energy Storage System on Frequency Response of a Multi-Machine Power System

“…In a smart grid environment, the responsive loads are integrated through demand response (DR) programs which are advantageous to consumers and utility [7,8]. Several strategies of integration of responsive loads and their benefits in enhancing the power grid's performance and economy are reported in literature.…”

“…In contrast to previously mentioned literature which either discuss DR [6][7][8][9][10][11] or ESS [16][17][18][19][20], this work considers their combined operation in a smart grid environment. Moreover, prevalent multi-machine power system is considered for mathematical modelling and simulation results instead of a single-machine power system [21][22][23][24][25].…”