Solving practical economic load dispatch problem using crow search algorithm

The practical economic load dispatch problem is a non-convex, non-smooth, and non-linear optimization problem due to including practical considerations such as valve-point loading effects and multiple fuel options. An optimization algorithm named crow search algorithm is proposed in this paper to solve the practical non-convex economic load dispatch problem. Three cases with different economic load dispatch configurations are studied. The simulation results and statistical analysis show the efficiency of the proposed crow search algorithm. Also, the simulation results are compared to the other reported algorithms. The comparison of results confirm the high-quality solutions and the effectiveness of the proposed method for solving the non-convex practical economic load dispatch problem

Non-convex constrained economic power dispatch with prohibited operating zones and piecewise quadratic cost functions

This paper is focused on the solution of the non-convex economic power dispatch problem with piecewise quadratic cost functions and practical operation constraints of generation units. The constraints of the economic dispatch problem are power balance constraint, generation limits constraint, prohibited operating zones and transmission power losses. To solve this problem, a meta-heuristic optimization algorithm named crow search algorithm is proposed. A constraint handling technique is also implemented to satisfy the constraints effectively. For the verification of the effectiveness and the superiority of the proposed algorithm, it is tested on 6-unit, 10-unit and 15-unit test systems. The simulation results and statistical analysis show the efficiency of the proposed algorithm. Also, the results confirm the superiority and the high-quality solutions of the proposed algorithm when compared to the other reported algorithms

A review of meta-heuristic algorithms for reactive power planning problem

Reactive power planning (RPP) is generally defined as an optimal allocation of additional reactive power sources that should be installed in the network for a predefined horizon of planning at minimum cost while satisfying equality and inequality constraints. The optimal placements of new VAR sources can be selected according to certain indices related to the objectives to be studied. In this paper, various solution methods for solving the RPP problem are extensively reviewed which are generally categorized into analytical approaches, arithmetic programming approaches, and meta-heuristic optimization techniques. The research focuses on the disparate applications of meta-heuristic algorithms for solving the RPP problem. They are subcategorized into evolution based, and swarm intelligence. Also, a study is performed via the multi-objective formulations of reactive power planning and operations to clarify their merits and demerits

Experimental evaluation of 8 kW grid-connected photovoltaic system in Egypt

An experimental observation study of 8 kW grid-connected photovoltaic (PV) system that is installed at Electronics Research Institute (ERI), Giza, Egypt (Latitude 30.04°N, Longitude 31.21°E), is presented. This study includes the quality of the electrical power generated and injected into the network. The considered system consists of 28 × 295 Wp multicrystalline PV modules, StecaGrid three-phase 8 kW grid-connected inverter and a Solar-Log 300 PM+ for data acquisition and remote monitoring. The power quality parameters at the inverter output side have been measured using CA8335 power quality analyzer. The system has been installed in August 2014 and generated 5.7 MWh till February 2015. The produced electricity by the system is injected directly into the grid without storage device. The purpose of this paper is to present and evaluate the measurements of the power quality parameters obtained from the PV site. Also, this paper presents a comprehensive evaluation of the performance of the system over a period of one week. The observation and analyses exploitation of the collected data can help to evaluate the performance of the PV system connected to the network