In this proposed study, a new long term scheduling is proposed for simultaneous placement of Distributed Generation (DG) and Distribution STATic COMpensator (DSTATCOM) in the radial distribution networks. The proposed work has a unique multi-objective function which consists of minimizing power loss, and total voltage deviation (TVD), as well as maximizing the voltage stability index (VSI) subject to equality and inequality system constraints. The multi-objective problem has been solved by a novel metaheuristic optimization algorithm called as lightning search algorithm (LSA). In the proposed approach, the feeder loads are varied linearly from light load (0.5) to peak load (1.6) with a step size of 1%. In each load step, the optimal sizing for DG and DSTATCOM are calculated by LSA. Through curve fitting technique (CFT), the optimal sizing for both DG and DSTATCOM per load level is formulated in the form of generalized equation. The proposed generalized equation will help the distribution network operators (DNOs) to select the DG and DSTATCOM sizes according to the load changes. The proposed method is tested on two test systems of 33-bus and 69-bus in different cases.

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In this literature, the simultaneous placement of both the Renewable Distribution Generation (DG) and Distribution STATCOM (DSTATCOM) in the Radial Distribution System (RDS) for Power Loss Minimization (PLM) is discussed. Loss Sensitivity Factor (LSF) is initially applied to discover the candidate location of DG and DSTATCOM in RDS. The effective Hybrid Lightning Search Algorithm‐Simplex Method (LSA‐SM) is used to compute the optimal sizing of DG and D‐STATCOM. The performance of the proposed method is tested separately on both IEEE33 and IEEE69 RDS test systems. The improvement in system Voltage Profile and operational stability before and after the allocation of DG and DSTATCOM is discussed. The improved system Voltage Stability Index values for different cases are plotted. The performance of the proposed method is compared with similar existing methods.

The electric motor is the mechanism that transforms electrical energy into mechanical energy. Nowadays, electric motors are the cause of a considerable share of the use of electricity and therefore of the energy consumptions (70% in the industrial sector and 25-30% in the tertiary sector). Faced with ever-increasing energy demand and with a view to adhering to the all-over-the world imperative of adopting measures to reduce energy consumption in all the involved sectors, the use of efficiency enhanced electric motors is required. Generally, the efficiency of an electric motor depends on the type of motor, the size of the motor, the utilization factor, but also on the quality and quantity of the materials employed. Therefore, from all these aspects the need of using energy and costefficient components for developing electric motors arises. This review paper aims to draw a general framework on the methods of increasing efficiency and of reducing weight of the electric motors.

There is a huge requirement for power systems to reduce power losses. Adding distributed generators (DGs) is the most common approach to achieving lower power losses. However, several challenges arise, such as determining the ideal size as well as location of the utilized distributed generators. Most of the existing methods do not consider the variety of load types, the variety and size of the utilized DGs besides reducing the convergence time and enhancing the optimization results. The paper performed an optimization algorithm that integrated a golden search-based flower pollination algorithm and fitness-distance balance (FDB) to find out the optimal size as well as the location of the distributed generators. It was then compared with different optimization methods to determine the best optimization technique, and it was determined to be the best technique. In addition, different types of DGs are considered, including solar energy, wind energy, and biogas, along with optimizing the size of the utilized DGs to reduce the system cost. Testing with different types of bus systems, and different types of DGs in a radial distribution system was done to reveal that the modified flower pollination with golden section search was superior in comparison to others with regards to convergence and power loss reduction.