Application of interior point method to economic dispatch

Abstract

A b s t r a c tThe paper describes the implementation of a quadratic interior point method for optimal power flow. Optimal power f l o w involves the determination of the optimal of a given objective function subject to given c o n s t r a i n t s .The scheme developed solves the quadratic or linear optimization problem subject to linear constraints. The algorithm has been evaluated on a 14-bus system, and its accuracy and speed are d e m o n s t r a t e d . I. INTRODU~IONIn the normal daily operation of a power system, emergency conditions may develop due to forced or random events. In order to maintain an economic and secure power system, several options are available to power system operators and planners. The traditional approach utilizes a trial and error technique f o r providing sub-optimum c o r r e c t i v e s t r a t e g i e s f o r alleviating violations due to planned or unexpected contingencies. This approach does not in general guarantee an acceptable optimum solution.The development of an optimal strategy for maintaining power system operation is accomplished by using several optimization approaches.Almost three decades ago, Carpentier [ 13 introduced a generalized, nonlinear programming formulation of the economic dispatch problem. It was later named optimal power flow (OPF) by Dommel and Tinney [2]. The optimal power flow computation has received widespread attention.It is of current interest to many power utilities, and has been identified as one of the most important operational tools of the power

Optimal economic power dispatch in the presence of intermittent renewable energy sources

“…From the probability density function shown in Fig. 5, the mean annual wind speed is estimated and the mean average power output in watts over one year is calculated using (15). In this case scenario, we assume that the penetration level of the wind turbine generators is 5%, and the wind turbines are assumed to be placed at buses 4, 8, and 21, respectively.…”

“…The challenges to optimal power flows are reported by Momoh et al in [5]. Examples of some methods that are used to solve the optimal power flow include, nonlinear programming [6]- [9], quadratic programming [10], Newton's method [11], [12], heuristic and swarm intelligence [13], [14], interior point method [15], [16], and linear programming (LP) based methods [17]- [20]. Amongst these methods, LP based methods are recognized as viable and promising tools in solving the constrained economic dispatch problem.…”

A Cauchy-Gaussian Quantum-Behaved Bat Algorithm Applied to Solve the Economic Load Dispatch Problem

“…programming [8], interior point programming [9], mixed integer programming [10], the Lagrangian relaxation algorithm [11], the decomposition technique [12], the branchand-bound method [13], the Newton-Raphson method [14], Lambda iteration [15] and the gradient method [16]. However, these classical methods experience difficulty when finding initial solutions and are prone to local optimal convergence [17].…”

A Cauchy-Gaussian Quantum-Behaved Bat Algorithm Applied to Solve the Economic Load Dispatch Problem

“…As an optimization problem, the economic dispatch (ED) problem consists of an objective function and various constraints [4]. In previous years, several methods known as conventional methods have been used to solve economic dispatch problems, such as linear programming [5], nonlinear programming [6], quadratic programming [7], dynamic programming [8], interior point programming [9], mixed integer programming [10], the Lagrangian relaxation algorithm [11], the decomposition technique [12], the branch-and-bound method [13], the Newton-Raphson method [14], Lambda iteration [15] and the gradient method [16]. However, these classical methods experience difficulty when finding initial solutions and are prone to local optimal convergence [17].…”