Abstract— In this paper

Abstract— In this paper, proposed optimization technique called whale optimization algorithm (WOA) is presents to identify the optimum location and sizing of distributed generation (DG) and capacitor in radial distribution systems considering minimization of single and multi-objective function namely, (network power losses, voltage deviation, and total operating cost). The multi objective function is formed by the use of weighted sum method. In this regard, multiple-DG units are simultaneously allocated and analyzed under two load power factors (i.e., unity and optimal). The proposed technique has been applied to a 33-bus radial distribution system. The performance of the WOA technique is compared with other evolutionary optimization methods under different system operating conditions in terms of all measures. The simulation results show the effectiveness of installing the proper size of DG at the suitable location based on different techniques.
Keywords—Optimization Algorithm; Radial Distribution system; Distributed generation; Capacitor banks; Power loss reduction; voltage deviation improvement; total operating cost reduction.
I. INTRODUCTION
Load demand is increased so that the distribution network expands radially. Distributed generation units are installed in the distribution network. DGs impacts on distribution system by changing the power flow of the distribution feeders 1.
Distributed generation (DG) can be defined as small electric power source with the capacity of less than 100MW connected directly to distribution system in the load part 2, 3, and 4. There are four type of DG. The first type of DG injects only Real power such as PV, MT and FC with PE interface. The second type of DG injects only reactive power only such as synchronous compensator and capacitor bank. The third type of DG injects both real power and reactive power such as Synchronous generator. The fourth type of DG injects real power and consumed reactive power such as wind turbines 5.
Some advantages of DG are listed by Hernandez, Velasco, and Trujillo (2011) 6 includes: (a) Minimization of total network power losses. (b) Improves the reliability and voltage profile of the system. (c) Reduces the total emission of the system. (d) More flexible energy solution due to the small size. (e) Mitigates environmental concerns.
The problem of finding the optimal allocation of DG units is a high. Random placement of DG sources in a distribution network leads to; increasing power loss, reducing reliability level and growing cost in the system. Therefore, it is important to allocate of DG to maximize and improving the system performance 7, 8.
Optimization techniques have become the most common use in recent years, and extend to include a different type of study. Different optimization methods have been applied to solve the optimal allocation problem for DG and capacitor while reducing the total network power losses, voltage deviation, and total operating cost.
In order to obtain an optimal allocation of DG, the previous researchers have been used several methods that are classified as:
Effect of DG only; The effects of DG on the stability of the power system, angle, frequency and voltage stability have been presented by Dang Jiqing Yu Tong Dang Bo HanK., Chengdu A (2011) 9; Donnelly, Dagle, Trudnowski, & Rogers (1996) 10; Reza, Slootweg, Schavemaker, Kling, & Van der Sluis (2003) 11. Prakash DB, Lakshminarayana C (2016) 12 is presented the effect of type and number of DG on the network power losses, and voltage profile. Nguyen TP, VO DN (2018) 13 is presented the impact of DG on the network power losses. The effect of DG was formulated with multi-objective functions explained by clonal selection based artificial immune system (AIS) 7, the four objectives are to minimize the real and reactive power loss, improve the voltage regulation and voltage stability. Evolutionary particle swarm optimization (EPSO) 14 is used to calculate the DG capacity, taking into account reducing energy loss and improving voltage profile. A multi-objective harmony search algorithm 15 is presented to evaluate the effect of DG location for optimal planning, power loss minimization and voltage profile improvement are the objective functions presented. Bat Algorithm (BA) 16 was used to obtained the optimal allocation of DG considering minimization of total network power loss and improving the voltage stability index.