Cost-based analysis and optimization of distributed generations and shunt capacitors incorporated into distribution systems with nonlinear demand modeling

• Published in: Expert systems with applications 2022-07, Vol.198, p.116844, Article 116844
• Main Author: Eid, Ahmad
• Format: Article
• Language: English
• Subjects: Active-reactive power; Allocations; Capacitors; Cost allocation; Cost analysis; Cost of energy loss; Demand; Distributed generation; Electric potential; Electric power loss; Electrical loads; Energy costs; Heuristic methods; Jellyfish search algorithm; Loss reduction; Multi-objective optimization; Nonlinear systems; Optimization; Power loss reduction; Radial distribution; Search algorithms; Shunt capacitors; Systems stability; Total operating cost; Voltage
• ISSN: 0957-4174; 1873-6793
• DOI: 10.1016/j.eswa.2022.116844

•Six nonlinear demands of distribution systems are modeled and solved.•The DG and SC banks allocation is solved using the jellyfish search algorithm (JSA).•The adopted JSA minimized the total operating cost, costs of energy loss, and devices.•Both single- and multi-objective functions are solved using the adopted JSA. This paper optimizes the allocations of Distributed Generators (DG) and Shunt Capacitor (SC) banks to minimize a multi-objective problem consisting of four different indices. These indices include active/reactive power loss reduction, voltage profile improvement, and system stability enhancement. Consequently, the costs of energy loss, allocated devices, and total operation are estimated per year for different installed DG/SC pairs for studied systems. Multi-DG and SC banks are optimally installed in the standard 69-bus and 136-bus radial distribution systems considering six nonlinear load models. The six models are generated from the nonlinear relationship between the system voltage and demand. Furthermore, the load type affects the DG/SC allocation optimization problem and other performance parameters such as the total voltage deviation (TVD), stability index (SI), and the power drawn from the utility. A new metaheuristic optimization called the Jellyfish Search Algorithm (JSA) is adopted and applied to allocate the DG units and the SC banks optimally into the distribution systems. The savings in the annual energy loss reach 65.88%, 95.99%, and 97.91% with industrial load demand for 1DG/1SC, 2DG/2SC, and 3DG/3SC allocations, respectively for the 69-bus RDS. While for the 136-bus RDS, the saving reaches 39.71% with constant-impedance demand, 58.84%, and 73.87% with commercial demand for 1DG/1SC, 3DG/3SC, and 6DG/6SC pairs, respectively. It is found that the JSA is practical and suitable for solving these nonlinear optimization problems, and it gives better results as compared to other algorithms in the literature.