Optimal location and capacity of multi-distributed generation for loss reduction and voltage profile improvement using imperialist competitive algorithm

Abstract

This paper proposes an Imperialist Competitive Algorithm (ICA) for optimal multiple distributed generations (DGs) placement and sizing in a distribution system. The objective is to minimize the total real power losses and improve the voltage profile within real and reactive power generation and voltage limits. Three types of DG are considered and the ICA is used to find the better sizes and locations of DGs for maximum real power losses reduction and voltage improvement for given number of DG units in each type. Both integer and continuous variables are considered in ICA, integer variable for locations and continues variable for sizes. The total real power losses and voltage profile evaluation are based on a power flow method for radial distribution system with the representation of DGs. The proposed method has been demonstrated on 33 bus radial distribution system. The efficiency of the ICA in reducing the total power losses and improving voltage is validated by comparing the obtained results with Particle Swarm Optimization (PSO) algorithm.

Energy harvesting maximization by integration of distributed generation based on economic benefits

“…The MOF can be stated as the weighted sum of the transmission efficiency (TEI) and the voltage deviation index (VDI) and reactive power loss reduction index (QLI). The weighted summation method is efficient, the development of a strongly nondominated solution that can be used as the initial solution for other approaches is simple and feasible [21]. MOF minimization can be stated from (21):…”

An insight into the estimation of drilling fluid density at HPHT condition using PSO-, ICA-, and GA-LSSVM strategies

“…Figure 1 provides a simplified representation of an ICA. In addition to simply explaining the ICA approach, it may be proper to employ a straightforward pseudo-code to describe the ICA procedure as 55 , 56 :

Figure 1 Schematic representation of the ICA optimization method 57 .

Apply random points to the function to initialize the empires; Move the colonies toward the corresponding imperialist (i.e., assimilation); Apply random position alternations in several colonies (i.e., revolution); Replace the imperialist position with a colony of a lower cost, if any; Unify analogous empires; Find the total cost of the empire; Incorporate weaker colonies of weaker empires into a more powerful empire (i.e., imperialist competition) to exclude the empires of no power; and Finish the procedure if the discontinuation criterion is met; otherwise, go to step 2.…”

Voltage Quality and Power Factor Improvement in Smart Grids Using Controlled DG Units

“…The authors of [17] proposed a control method for small domestic power plants using renewable energy to reduce total harmonic distortion, and [18] used a three-phase inverter together with a new control algorithm connected to a renewable source in order to reduce voltage unbalance. Further, the imperialist competitive algorithm has been used in [19], as well as voltage indexing and the heuristic method in [20], while [21] used an experimental method to define the optimal location. Other methods have been relied upon as control techniques to drive the DG units themselves.…”