Optimum estimation of series capacitors for enhancing distribution system performance via an improved hybrid optimization algorithm

Abstract

As the load on distribution networks grows, system operators and planners are constantly challenged with the issue of voltage regulation or enhancing the quality of supply to customers at the load end of lengthy distribution lines. This paper presents the optimum determination of series capacitor units in a distribution system to maximize energy-saving and enhance voltage levels. Interestingly, series capacitors can enhance the capability of transmission lines, reduce line losses, enhance the performance of buses with large induction motor loads and reduce voltage flicker. At the same time, the limitations of series compensation are taken into consideration while calculating its optimum values. To achieve the planning objective and optimal load flow objective, two strategies: The Improved Grey Wolf Optimization method (I-GWO) and Tabu Search (TS), are hybridized to get the benefit of their advantages. The I-GWO has a movement strategy called dimension learning-based hunting for enhancing the balance between global and local search and maintaining diversity. The proposed (I-GWO-TS) algorithm can solve mixed-integer programming to achieve the planning and the optimal load flow objectives. The proposed method can be applied to a real Egyptian distribution system that is heavily loaded, with poor voltage regulation, and also has high-power losses. The obtained results demonstrate the capability of the proposed approach to determine optimal series capacitors’ location and sizing for maximization of energy saving. Further, the proposed method improves the network performance regarding the voltage profile and power losses, although the limitations of including series compensation were considered in the distribution system.