Coal power plant-enabled grid resilience through distributed energy resources and demand response integration

• Published in: Electrical engineering Vol. 106; no. 4; pp. 4415 - 4437
• Main Authors: Saxena, Vivek, Kumar, Narendra, Nangia, Uma
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 2024; Springer Nature B.V
• Subjects: Clean energy; Coal-fired power plants; Coordination; Distributed generation; Economics and Management; Electric power demand; Electrical Engineering; Electrical Machines and Networks; Energy distribution; Energy management; Energy Policy; Energy resources; Energy sources; Engineering; Flow stability; Optimization techniques; Original Paper; Particle swarm optimization; Power dispatch; Power Electronics; Power flow; Power plants; Renewable energy; Renewable resources; Battery energy storage system; Renewable energy; Coal power plant; Distributed generation; Demand response; CO; Multilevel optimization
• ISSN: 0948-7921; 1432-0487
• DOI: 10.1007/s00202-024-02239-5

In the growing world, the utilization of electrical energy is increasing rapidly. Excessive use of fossil fuels will drain them and also invite hazardous pollution. Integrating renewable energy resources as distributed generators (DGs) can fulfill the rapidly increasing electrical energy demand and promote green energy generation to a large extent. The intermittent nature of renewable energy and higher penetration of DG may adversely affect the operation of the distribution network (DN). As a result, power disparity, reverse power flow to the grid, and voltage instability may exist. One key solution is to optimally integrate the renewable energy-based DG and battery energy storage system (BESS) in the coordination of demand response (DR). This paper proposes a multilevel particle swarm optimization technique to synchronize the distributed energy resources (DER) and DR in the DN. The proposed approach is implemented on the IEEE 33 bus system energized by coal power plant (CPP). The first level of optimization finds the sizes and locations of DER (DG and BESS), and the next level determines the optimal power dispatch in the coordination of DR. The outcomes of this framework exhibit effectiveness in the optimal utilization of renewable energy resources and the enhancement of power quality parameters in DN so that CO 2 emissions are reduced by 32.71% from CPP.