Energy Saving Maximization of Balanced and Unbalanced Distribution Power Systems via Network Reconfiguration and Optimum Capacitor Allocation Using a Hybrid Metaheuristic Algorithm

The main aim of this work was the maximization of the energy saving of balanced and unbalanced distribution power systems via system reconfiguration and the optimum capacitor's bank choice, which were estimated by using a new algorithm: modified Tabu search and Harper sphere search (MTS-HSSA). The results demonstrated that the proposed method is appropriate for energy saving and improving performance compared with other methods reported in the literature for IEEE 33-bus adopted systems, including large scale systems such as IEEE 119 and the IEEE 123 unbalanced distribution system. Moreover, it can be used for unbalanced distribution systems distributed generators (DGs). The results demonstrated that the proposed method (the optimal choice of shunt capacitor(SC) banks and the optimal reconfiguration via the proposed algorithm) is appropriate for energy saving compared with different strategies for energy saving, which included distributed generation (DG) at different cost levels.

Determinations of Annual Investments of DisCo and Private Sector in Expansion Planning of Distribution Network

Ever-increasing load-demand, threaten the continuity of power supply and diminishes power quality causing serious technical challenges in distribution networks. In this regards, commonly used cheaper practices like capacitor allocation and network configuration, can enhance operational parameters of the network. On the other hand, supplying the future loaddemand, requires installing new substations or distributed generations (DGs). Because of DGs inherent technical and economic advantages, Distribution Company (DisCo), encourage private investment to install DGs, by signing long-term Power Purchase Agreement (PPA) with DG owners (DGO). In such a situation created, DG allocation and simultaneously capacitor allocation and network configuration can be economical for both DisCo and DGO and also can enhance the reliability and power quality. So, this paper is aimed to find the annual instants for network configuration; timing, sizing and sitting of capacitors and DGs, and PPA rates using Multi-Objective Particle Swarm Optimization (MOPSO). Also, the uncertainties of load-demand and electricity-price, voltage-sensitive loads and load priority in power supply are applied into the planning problem. Voltage deviation and voltage stability are considered as constraints which must be better in optimum solution. The effectiveness of the proposed scheme, is validated by computer simulation done on a 33-Bus IEEE distribution network and the outcomes are discussed.