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In this circumstance of global warming, energy market deregulation, and enormous load growth, distribution network entails a proficient strategy to maintain the reliability and efficiency of the power service. Incorporation of solar photovoltaic (PV) system and battery storage (BS) in coordination with distributed static compensator (DSTATCOM) is a competent and practical approach to alleviate the power quality and reliability concern. In this study, a comprehensive strategic model is presented to optimally deploy PV, BS, and DSTATCOM to maximise voltage profile improvement, reliability, economic, and ecological benefit of the network. An accurate and precise novel voltage profile improvement indicator namely network voltage profile improvement index is proposed. Benefit-cost ratio and environment benefit index are proposed to quantify economic and environmental benefits, respectively. Similarly, reliability indices such as expected energy not served are used to appraise the system reliability. A fuzzy based extended version of NSGA II is utilised for the optimal deployment of the devices considering security limits. The proposed method is tested on 33-bus and 69-bus distribution networks considering time variant practical load models and the obtained results validate the efficacy and efficiency of the proposed method when compared with other multi-objective algorithms.

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The enormous load growth in recent times has forced distribution companies to undertake comprehensive planning of the active distribution system (ADS) to maintain superior service to their consumers. Under different critical situations in the restructured power system, reconfiguration in combination with the incorporation of renewable energy sources (RESs) and distributed static compensator (DSTATCOM) must be utilised for accurate system planning. In addition, from a practical viewpoint, the time-variant load demand of different consumers and the intermittency of RES units must be considered. This study proposes a modified multi-objective particle swarm optimisation (m-MOPSO) technique for ADS planning considering reconfiguration, RES, and DSTATCOM to enhance voltage stability, reduce pollution, improve reliability, and maximise financial benefits. In the proposed m-MOPSO, a novel non-dominant sorting strategy is used to maintain diversity among the nondominated solutions. The time-varying system load, yearly load growth, and intermittent power generation of RES are considered to construct a realistic planning model. The proposed technique is tested on the 33-bus ADS considering different planning schemes to provide the most suitable planning scheme to the ADS planners. Moreover, the accuracy of the proposed algorithm is confirmed by comparing it with other multi-objective algorithms.

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Summary In this study, a hybrid approach based on fuzzy logic and rooted tree optimization (RTO) algorithm is proposed for the strategic incorporation of distributed generation (DG) and distributed static compensator (DSTATCOM) in radial distribution system (RDS) to improve voltage profile, reduce losses, and maximize economic and environmental benefits. Fuzzy logic is applied to bring the objectives in the same range, and using RTO technique, the optimal site and size of the devices are determined. Considering the uncertainty in DG's output and time‐varying system load, the proposed technique is tested on 69‐bus and 118‐bus RDSs, and to check the accuracy and feasibility, the simulation results are compared with other existing techniques. The Wilcoxon signed rank test (WSRT) is applied to confirm the superiority of the proposed algorithm. Furthermore, comparative performance analysis is conducted between different planning schemes for facilitating the distribution system planner to select the most suitable one.

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