The main objective of this paper is to develop a distributed model using grid environment through which the Economic load dispatch solutions of multi-area power systems can be obtained continuously. Grid computing is a viable solution in order to exploit the enormous amount of computing power available across Internet to solve large interconnected power system problems. A grid service model is proposed for Economic load dispatch, which provides the solutions at specific intervals of time. The proposed model is designed in such a way that any node in the grid can provide the Economic load dispatch (ELD) solution. The node which serves as a server node at a specific instance in the grid can obtain the power system data from other client grid nodes and responds with Economic load dispatch solutions. The proposed model is highly distributed and has inherent features of scalability, reliability and also uses all available computing power, hence Economic feasibility of analyzing power system problems was taken care implicitly.

This paper presents a new solution method to efficiently handle non-convexity stemmed from valve points in the Economic load dispatch problem. The proposed solution technique integrates both the advantage of fast solution algorithms of linear programming and powerful solution techniques of nonlinear programming to find the global solution. In the first step of the proposed solution framework, non-convex terms are replaced by some linear segments and the new linear model solved by modern fast algorithms. In the second step, a nonlinear programming algorithm as a powerful local search algorithm solves the original non-convex model to improve the solution obtained in the previous step. By exploiting the main strength of linear and nonlinear programming algorithms, the proposed solution approach can quickly converge to nearly the global solution method. By experimental results on three test cases with different sizes, we show that the presented method outperforms the other algorithms published in the literature in the quality of the solution.

Economic load dispatch (ELD) is an important part of cost minimization procedure in power system operation. Di erent derivative and probabilistic methods are used to solve ELD problems. This paper proposes a powerful Sine Cosine Algorithm (SCA) to explain the ELD issue including equality and inequality restrictions. The main aim of ELD is to satisfy the entire electric load at minimum cost. The SCA is a population-based probabilistic method, which guides its search agents that are randomly placed in the search space towards an optimal point using their  tness functions and keeps a track of the best solution achieved by each search agent. SCA was used to solve the ELD problem due to its favorable exploration and local optima escaping technique. This algorithm con rmed that promising areas of the search space were exploited to have a smooth transition from exploration to exploitation using sine and cosine functions. Simulation results proved that the proposed algorithm surpassed other existing optimization techniques in terms of quality of the solution obtained and computational e ciency. The  nal results also proved the robustness of the SCA.

In recent years, soft computing methods have generated a large research interest. The synthesis of the fuzzy logic and the evolutionary algorithms is one of these methods. A particular evolutionary algorithm (EA) is differential evolution (DE). As for any EA, DE algorithm also requires parameters tuning to achieve desirable performance. In this paper tuning the perturbation factor vector of DE is done with a Fuzzy Logic Controller (FLC) that adjusts this parameter dynamically. We apply the fuzzy logic controlled differential evolution(FLC-DE) to solve the Economic load dispatch problem of two test systems consisting of 13 and 40 thermal generators whose non-smooth fuel cost function takes into account the valve-point loading effects. Simulation results indicate that the performance of the FLC-DE present the best results when compared with other optimization approaches in solving Economic load dispatch problems.

Power system network is formed to mainly generate power through all generators to fulfil total load demand and compensate for transmission line losses. The Economic load dispatch (ELD) problem is considered one of the most important problems of cost minimization in power system operations. Various approaches have been employed so far to solve the ELD problem. In this paper, a powerful Search Group Optimization (SGO) technique was implemented to solve the ELD problem. SGO maintains a good balance between its exploitation and exploration phases. This optimization technique tends to  nd promising regions of the search space from the first iteration onwards. The algorithm uses five important steps to reach an optimal solution to the ELD problem and they include initial population, initial selection of search group, search group mutation, family generation, and new search group selection. Using these five steps, the SGO tends to make a smooth transition towards the optimized solution. The SGO was applied to five test systems and the final results were compared to those of various other recently developed optimization techniques. The results proved the robustness, feasibility, effectiveness, and efficiency of SGO in terms of computational time and proximity to global optimum solution.