Application Of Multi-Layered Perceptron Neural Network (MLPNN) With Consideration Losses And Emission Dispatch

Nowadays, optimum generation and consumption of energy are considered as two important problems. Economic Dispatch that is the most optimum is one of important problems in power system. This paper presents a multi-layered perceptron neural network (MLPNN) method to solve the combined Losses and emission dispatch problem. Therefore, knowing Problem-Solving in Economic Dispatch is a necessity. First, the Economic Dispatch is explained and then neural network is reviewed. Next, different kinds of neural networks are mentioned by using in Economic Dispatch

Application Of Multi-Layered Perceptron Neural Network (MLPNN) With Consideration Losses And Emission Dispatch

Nowadays, optimum generation and consumption of energy are considered as two important problems. Economic Dispatch that is the most optimum is one of important problems in power system. This paper presents a multi-layered perceptron neural network (MLPNN) method to solve the combined Losses and emission dispatch problem. Therefore, knowing Problem-Solving in Economic Dispatch is a necessity. First, the Economic Dispatch is explained and then neural network is reviewed. Next, different kinds of neural networks are mentioned by using in Economic Dispatch

Antlion optimization algorithm for optimal non-smooth economic load dispatch

This paper presents applications of Antlion optimization algorithm (ALO) for handling optimal economic load dispatch (OELD) problems. Electricity generation cost minimization by controlling power output of all available generating units is a major goal of the problem. ALO is a metaheuristic algorithm based on the hunting process of Antlions. The effect of ALO is investigated by solving a 10-unit system. Each studied case has different objective function and complex level of restraints. Three test cases are employed and arranged according to the complex level in which the first one only considers multi fuel sources while the second case is more complicated by taking valve point loading effects into account. And, the third case is the highest challenge to ALO since the valve effects together with ramp rate limits, prohibited operating zones and spinning reserve constraints are taken into consideration. The comparisons of the result obtained by ALO and other ones indicate the ALO algorithm is more potential than most methods on the solution, the stabilization, and the convergence velocity. Therefore, the ALO method is an effective and promising tool for systems with multi fuel sources and considering complicated constraints

Optimization methods for electric power systems: An overview

Power systems optimization problems are very difficult to solve because power systems are very large, complex, geographically widely distributed and are influenced by many unexpected events. It is therefore necessary to employ most efficient optimization methods to take full advantages in simplifying the formulation and implementation of the problem. This article presents an overview of important mathematical optimization and artificial intelligence (AI) techniques used in power optimization problems. Applications of hybrid AI techniques have also been discussed in this article

An Efficient Simulated Annealing Algorithm for Economic Load Dispatch Problems

This paper presents an efficient simulated annealing (SA) algorithm with a single decision variable to solve the economic load dispatch (ELD) problems. The philosophy involves the introduction of a new decision variable through a prudent mathematical transformation of the relation between the decision variable and the optimal generations. The objectives of ELD problems in electric power generation is to programmed the devoted generating unit outputs so as to meet the mandatory load demand at lowest amount operating cost while satisfying all units and system equality and inequality constraints. Global optimization approaches is inspired by annealing process of thermodynamics. The proposed SA algorithm presented here is applied to two case studies, which analyze power systems having three, and six generating units. The results determined by the proposed approach are compared to those found by conventional quadratic programming (QP) and genetic algorithm (GA)

Economic load dispatch solutions considering multiple fuels for thermal units and generation cost of wind turbines

In this paper, economic load dispatch (ELD) problem is solved by applying a suggested improved particle swarm optimization (IPSO) for reaching the lowest total power generation cost from wind farms (WFs) and thermal units (TUs). The suggested IPSO is the modified version of Particle swarm optimization (PSO) by changing velocity and position updates. The five best solutions are employed to replace the so-far best position of each particle in velocity update mechanism and the five best solutions are used to replace previous position of each particle in position update. In addition, constriction factor is also used in the suggested IPSO. PSO, constriction factor-based PSO (CFPSO) and bat optimization algorithm (BOA) are also run for comparisons. Two systems are used to run the four methods. The first system is comprised of nine TUs with multiple fuels and one wind farm. The second system is comprised of eight TUs with multiple fuels and two WFs. From the comparisons of results, IPSO is much more powerful than three others and it can find optimal power generation with the lowest total power generation cost

Solving Economic Dispatch Problem with Valve-Point Effect using a Modified ABC Algorithm

This paper presents a new approach for solving economic dispatch (ED) problem with valve-point effect using a modified artificial bee colony (MABC) algorithm. Artificial bee colony algorithm is a recent population-based optimization method which has been successfully used in many complex problems. This paper proposes a novel best mechanism algorithm based on a modified ABC algorithm, in which a new mutation strategy inspired from the differential evolution (DE) is introduced in order to improve the exploitation process. To demonstrate the effectiveness of the proposed method, the numerical studies have been performed for two different sample systems. The results of the proposed method are compared with other techniques reported in recent literature. The results clearly show that the proposed MABC algorithm outperforms other state-of-the-art algorithms in solving ED problem with the valve-point effect.DOI:http://dx.doi.org/10.11591/ijece.v3i3.251