Optimal Operation of the Campus Microgrid considering the Resource Uncertainty and Demand Response Schemes

Abstract

Present power systems face problems such as rising energy charges and greenhouse gas (GHG) releases. These problems may be assuaged by participating distributed generators (DGs) and demand response (DR) policies in the distribution system (DS). The main focus of this paper is to propose an energy management system (EMS) approach for campus microgrid (µG). For this purpose, a Pakistani university has been investigated and an optimal solution has been proposed. Conventionally, it contains electricity from the national grid only as a supply to fulfil the energy demand. Under the proposed setup, it contains campus owned nondispatchable DGs such as solar photovoltaic (PV) panels and microturbines (MTs) as dispatchable sources. To overcome the random nature of solar irradiance, station battery has been integrated as energy storage. The subsequent nonlinear mathematical problem has been scheduled by mixed-integer nonlinear programming (MINLP) in MATLAB for saving energy cost and battery aging cost. The framework has been validated under deterministic and stochastic environments. Among random parameters, solar irradiance and load have been taken into consideration. Case studies have been carried out considering the demand response strategies to analyze the proposed model. The obtained results show that optimal management and scheduling of storage in the presence of DGs mutually benefit by minimizing consumption cost (customer) and grid load (utility) which show the efficacy of the proposed model. The results obtained are compared to the existing literature and a significant cost reduction is found.

Optimal Energy Management System of IoT-Enabled Large Building Considering Electric Vehicle Scheduling, Distributed Resources, and Demand Response Schemes

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Optimal Scheduling of Campus Microgrid Considering the Electric Vehicle Integration in Smart Grid

“…The authors in [26] proposed an EMS to analyze the economic and environmental effects of PV and ESS in a campus microgrid located in Pakistan. An EMS is proposed in [27] to optimally schedule the PV and storage system in a campus microgrid for reducing energy consumption cost and battery degradation cost. The nonlinear problem was formulated using mixed-integer nonlinear programming (MINLP) and simulated in MATLAB.…”

“…Fully discharging the battery can damage the system. For that reason, the charging and discharging of ESS must be within the limits specified by the following equations [27]:…”

Energy Hub Planning and Operation Optimization by Applying Demand Side Management Using GAMS

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