The high average prices and high volatility of prices in many restructured markets for electricity have raised concerns about the abuse of market power by generators. At the same time, information about the true costs of generation, that was readily available under regulation, is no longer disclosed by generators. Hence, it is becoming impractical to use a comparison of actual prices with compe...

The economic load dispatch plays an important role in the operation of power system, and several models by using different techniques have been used to solve these problems. Several traditional approaches like dynamic programming, lambda-iteration and gradient method are utilized to find out the optimal solution of non-linear problem. More recently, the soft computing techniques have received m...

We develop a general framework for pricing electricity in order to optimally manage the electricity load of societal infrastructures that interact with power systems through their price-responsive electricity load. In such infrastructure systems, electricity is not the sole resource needed to serve users’ needs. Examples include cloud computing infrastructure or electric transportation networks...

Direct Search (DS) methods are evolutionary algorithms used to solve constrained optimization problems. DS methods do not require information about the gradient of the objective function while searching for an optimum solution. One of such methods is Pattern Search (PS) algorithm. This study examines the usefulness of a constrained pattern search algorithm to solve well-known power system Econo...

Since the introduction of Ant Colony Optimization (ACO) technique in 1992, the algorithm starts to gain popularity due to its attractive features. However, several shortcomings such as slow convergence and stagnation motivate many researchers to stop further implementation of ACO. Therefore, in order to overcome these drawbacks, ACO is proposed to be combined with Differential Evolution (DE) an...

In this paper, Stochastic Economic Load Dispatch problem with Multiple Fuels is solved using Pareto distribution with local convex optimization by bacterial foraging approach. Bacterial foraging optimization is swarmed intelligence technique used to solve the problem of the power system. The algorithm is based on the group foraging behavior of Escherichia coli (E-coli) bacteria present in the h...

Global optimization based on evolutionary algorithms can be used as the important component for many engineering optimization problems. Evolutionary algorithms have yielded promising results for solving nonlinear, non-differentiable and multi-modal optimization problems in the power systems area. Differential evolution (DE) is a simple and efficient evolutionary algorithm for function optimizat...

Unit commitment (UC) is a optimization task planning operation in power system and is done by scheduled the generating units in on/off states. The UC problem is to minimize system total operating cost to meet forecasting load and reserve requirement while adhering to generator and transmission constraints to satisfy a given security level. The capability of using load, energy sources and energy...

This article presents an application of generalized pattern search (PS) algorithm to solve economic load dispatch (ELD) problems with convex and non-convex fuel cost objective functions. Main objective of ELD is to determine the most economic generating dispatch required to satisfy the predicted load demands including line losses. Relaxing various equality and inequality constraints are conside...

This paper presents the applications of computational intelligence techniques to economic load dispatch problems. The fuel cost equation of a thermal plant is generally expressed as continuous quadratic equation. In real situations the fuel cost equations can be discontinuous. In view of the above, both continuous and discontinuous fuel cost equations are considered in the present paper. First,...