Integration of distributed generation units (DGs) and capacitor banks (CBs) in distribution systems aim to enhance the system performance. This paper proposes water cycle algorithm (WCA) for optimal placement and sizing of DGs and CBs. The proposed method aims to achieve technical, economic, and environmental benefits. Different objective functions: minimizing power losses, voltage deviation, total electrical energy cost, total emissions produced by generation sources and improving the voltage stability index are considered. WCA emulates the water flow cycle from streams to rivers and from rivers to sea. Five different operational cases are considered to assess the performance of the proposed methodology. Simulations are carried out on three distribution systems, namely IEEE 33-bus, 69-bus test systems, and East Delta network, as a real part of Egyptian system. The simulated results demonstrate the effectiveness of the proposed method compared with other optimization algorithms. Also, the results demonstrate that the proposed WCA gives superior performance for the system and give distinguished improvements in both economic and environmental benefits. Moreover, the results give the flexible operation with controllable power factor DGs that is better than those using DGs at fixed power factor.

This study presents a two‐stage procedure to identify the optimal locations and sizes of capacitors in radial distribution systems. In first stage, the loss sensitivity analysis using two loss sensitivity indices (LSIs) is employed to select the most candidate capacitors locations. In second stage, the ant colony optimisation algorithm is investigated to find the optimal locations and sizes of capacitors considering the minimisation of energy loss and capacitor costs as objective functions while system constraints are fully achieved. The fixed, practical switched and the combination of fixed and switched capacitors are considered to find the optimal solution. The backward/forward sweep algorithm is developed for the load flow calculations. The proposed procedure is applied to different standard test systems as 34‐bus and 85‐bus radial distribution systems. In addition, the application of the proposed procedure on a real distribution system of the East Delta Network as a part of the Unified Egyptian Network is used as a test system. Numerical results show the capability of the proposed procedure to find the optimal solution for significant saving in the total cost with more accurate and efficient, competitive compared with other methods in the literature especially with increasing the distribution system sizing.

Controlling active/reactive power in distribution systems has a great impact on its performance. The placement of distributed generators (DGs) and shunt capacitors (SCs) are the most popular mechanisms to improve the distribution system performance. In this line, this paper proposes an enhanced genetic algorithm (EGA) that combines the merits of genetic algorithm and local search to find the optimal placement and capacity of the simultaneous allocation of DGs/SCs in the radial systems. Incorporating local search scheme enhances the search space capability and increases the exploration rate for finding the global solution. The proposed procedure aims at minimizing both total real power losses and the total voltage deviation in order to enhance the distribution system performance. To prove the proposed algorithm ability and scalability, three standard test systems, IEEE 33 bus, 69 bus and 119-bus test distribution networks, are considered. The simulation results show that the proposed EGA can efficiently search for the optimal solutions of the problem and outperforms the other existing algorithms in the literature. Moreover, an economic based cost analysis is provided for light, shoulder and heavy loading levels. It was proven, the proposed EGA leads to significant improvements in the technical and economic points of view.