Solution of Different Types of Economic Load Dispatch Problems Using a Pattern Search Method

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 when searching for an optimum solution. One such method is a pattern search (PS) algorithm. This study presents a new approach based on a constrained PS algorithm to solve various types of power system economic load dispatch (ELD) problems. These problems include economic dispatch with valve point (EDVP) effects, multi-area economic load dispatch (MAED), companied economic-environmental dispatch (CEED), and cubic cost function economic dispatch (QCFED). For illustrative purposes, the proposed PS technique has been applied to each of the above dispatch problems to validate its effectiveness. Furthermore, convergence characteristics and robustness of the proposed method has been assessed and investigated through comparison with results reported in literature. The outcome is very encouraging and suggests that PS methods may be very efficient when solving power system ELD problems

Application of pattern search method to power system valve-point economic load dispatch

Direct search (DS) methods are evolutionary algorithms used to solve constrained optimization problems. DS methods do not require any information about the gradient of the objective function at hand, while searching for an optimum solution. One of such methods is pattern search (PS) algorithm. This study presents a new approach based on a constrained pattern search algorithm to solve well-known power system economic load dispatch problem (ELD) with valve-point effect. For illustrative purposes, the proposed PS technique has been applied to various test systems to validate its effectiveness. Furthermore, convergence characteristics and robustness of the proposed method has been assessed and investigated through comparison with results reported in literature. The outcome is very encouraging and proves that pattern search (PS) is very applicable for solving power system economic load dispatch problem

Computer Ground-water Model for the Tillman Alluvium in Tillman County, Oklahoma

This study is concerned with the aquifer properties of the alluvial terrace and floodplain deposits in Tillman County, Oklahoma. The primary objective is to determine the maximum annual yield for the basin from July 1, 1973, to July l, 1993. A computer model is used to determine the maximum annual yield based on pumpage prior to July 1, 1973, and subsequent allocated pumpage until July 1, 1993.Geolog

Complementary Graph Coloring

The objective of the Graph Coloring problem is to color vertices of a graph in such a way that no two vertices that share an edge are assigned the same color. Aircraft Scheduling, Frequency Assignment, register allocation are all real life applications that can be solved using graph coloring. Graph Coloring is a well-known NP-complete problem to the academia in computer science and mathematics. In this paper we use the concept of complementary graphs to come up with a new heuristic for graph coloring. Our results are compared with an exact algorithm and other heuristic algorithms to evaluate our algorithm’s performance.

Optimal Performance of Dynamic Particle Swarm Optimization Based Maximum Power Trackers for Stand-Alone PV System Under Partial Shading Conditions

One of the important tasks for increasing the efficiency of photovoltaic (PV) system is the development and improvement of the maximum power point tracking algorithms (MPPT). These MPPT algorithms lead to the ability to catch efficiently the global maximum power point of the partially shaded PV array. One of these trackers is the particle swarm optimization (PSO) algorithm which is one of the Soft computing techniques. The conventional PSO based trackers have many advantages such as the simplicity of hardware implementation and independence from the installed system. The actual problem of the practical application of PSO is the determination of its parameters to ensure high effectiveness of extracting the global MPP. Analysis of scientific papers devoted to the PSO algorithm has shown that there is currently no methodology for the optimal parameters' selection of PSO algorithm based maximum power trackers for the PV system. This paper aims to create a convenient and reasonable method for choosing the optimal parameters of the PSO algorithm, taking into account the topology and parameters of the DC-DC converter and the configuration of solar panels. A new method for selecting the parameters of a buck converter connected to a battery has been presented. The optimal value of the sampling time for the digital MPP controllers, providing their maximum performance; has been determined based on a new methodology. Matlab/Simulink software package is used as the main research tool. The prominent outcomes identify that the modified PSO and its designed parameters best meet the requirements of the MPPT controller for the PV system

Solving Economic Dispatch Problem using Hybrid GA-PS-SQP Method

This study presents a new approach to solve the well-known power system Economic Load Dispatch problem (ED) using a hybrid algorithm consisting of Genetic Algorithm (GA), Pattern Search (PS) and Sequential Quadratic Programming (SQP). GA is the main optimizer of this algorithm, whereas PS and SQP are used to fine-tune the results obtained from the GA, thereby increasing solution confidence. To test the effectiveness of this approach it was applied to various test systems. Furthermore, the convergence characteristics and robustness of the proposed method have been explored through comparisons with results reported in literature. The outcome is very encouraging and suggests that the hybrid GA-PS-SQP algorithm is very effective in solving the power system economic load dispatch problem

Solving dynamic economic dispatch problems using pattern search based methods with particular focus on the West Doha Power Station in Kuwait

This thesis is concerned with Dynamic Economic Dispatch (DED) problems, in particular in the context of the current and future needs of the electrical power system in the State of Kuwait. General Economic Dispatch (ED) issues are addressed, under both static and dynamic conditions, with valve-point effects accounted for. Improvements have been achieved in terms of lower fuel costs, but also more efficient and reliable simulation algorithms. The existing ED/DED models have been improved in various ways and enhanced by developing and incorporating two renewable energy sources; namely wind energy and solar energy. These two have been identified as most relevant to the power system investigated. The models developed are general and can be adjusted to represent many practical systems.The Economic Dispatch problem had been formulated and solved as a constrained optimisation and a particular technique selected for this purpose – not explored before – was a Pattern Search (PS) algorithm. For illustrative purposes, the proposed PS technique had been applied to various test systems to validate its effectiveness. Furthermore, convergence characteristics and robustness of the method had been assessed through comparison with results reported in literature. The PS technique was found to be very competitive in terms of its overall performance. Variations of the technique have also been explored, in particular a hybrid formulation exploiting Genetic Algorithm (GA), Pattern Search (PS) and Sequential Quadratic Programming, and advantages of such a combined technique reported.A DED model for the West Doha Power Station (WDPS) in Kuwait has been developed and the penetration of renewable energy resources to this model has been discussed. The DED model was then solved using the PS method developed in this thesis to achieve the optimal dispatch with the aim to minimise fuel costs in WDPS. Considerable potential savings in electric power production of WDPS have been identified and thus the benefits of deploying renewable energy in Kuwaiti electric system demonstrated

An improved Pattern Search based algorithm to solve the Dynamic Economic Dispatch problem with valve-point effect

In this paper, an improved algorithm based on Pattern Search method (PS) to solve the Dynamic Economic Dispatch is proposed. The algorithm maintains the essential unit ramp rate constraint, along with all other necessary constraints, not only for the time horizon of operation (24 h), but it preserves these constraints through the transaction period to the next time horizon (next day) in order to avoid the discontinuity of the power system operation. The Dynamic Economic and Emission Dispatch problem (DEED) is also considered. The load balance constraints, operating limits, valve-point loading and network losses are included in the models of both DED and DEED. The numerical results clarify the significance of the improved algorithm and verify its performance