Optimal Placement and Size of SVC with Cost-Effective Function Using Genetic Algorithm for Voltage Profile Improvement in Renewable Integrated Power Systems

• Published in: Energies (Basel) 2023-03, Vol.16 (6), p.2637
• Main Authors: Dandotia, Ashish, Gupta, Mukesh Kumar, Banerjee, Malay Kumar, Singh, Suraj Kumar, Đurin, Bojan, Dogančić, Dragana, Kranjčić, Nikola
• Format: Article
• Language: English
• Subjects: Algorithms; Alternative energy sources; Buses; cost function; Costs; Electric power loss; Electric power systems; Electricity distribution; Flexible AC power transmission systems; genetic algorithm; Genetic algorithms; Identification methods; Optimization; Optimization techniques; Rankings; Stability analysis; SVC; Systems stability; total reduction cost; TVDN; Voltage; Voltage drop; voltage profile; Voltage stability
• ISSN: 1996-1073; 1996-1073
• DOI: 10.3390/en16062637

Given the concern for maintaining voltage stability in power systems integrated with renewable power systems due to a mismatch in generation and demand, there remains a need to invoke flexible alternating current transmission system (FACTS) devices in the distribution network. The present paper deals with identifying the locations of placement of a static var compensator in an experimental IEEE 14-bus system; the voltage drop in different buses in an IEEE 14-bus system is calculated by the standard formula. The total voltage drop in the network (TVDN) is also calculated as a reference. The ranking of buses in order of decreasing voltage drop is made, and the weak buses are identified as those showing the maximum or near-maximum voltage drop for the installation of a Static Var Compensator (SVC). The optimum usable size is calculated using a Genetic Algorithm approach to optimize the installation cost. After size optimization, installing a 2 MW solar generator is considered for the weak and most potential bus, which suffers from voltage drops or power loss. Based on the generator at the weakest bus, the total power loss in the network is calculated and compared with a similar method to assess the efficiency of the proposed model. Thus, the voltage stability enhancement problem is solved by applying a Genetic algorithm (GA) to optimize SVC size and using the Total Voltage Drop in Network (TVDN) method to identify weak buses in the systems. It is found that the performance of the proposed system is comparable with another existing system. It is further observed that a gain in power loss to 6.56% is achievable by adopting the proposed strategy, and the gain is better than the other system.