The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper addresses the environmental/economic dispatch (EED) problem, which aims to minimize the fuel cost and emission of pollutants in a power generation system. We propose an adaptive multiobjective differential evolution algorithm to solve the problem by seeking for the set of Pareto optimal solutions. Performance of the proposed algorithm is verified by comparing with a recent algorithm using...
In this paper a solution technique based on bat algorithm (BA) is implemented for solving the economic load dispatch problem in a power system in which every unit utilize multiple fuels for producing power. The economic load dispatch (ELD) problem is modeled as a complex mathematical function that takes cost coefficients of all the possible fuel options as well as effects of valve-point loading into...
Economic load dispatch problem involves various equality and inequality constraints which makes it complex. This paper presents a comparative study between Particle swarm optimization and Gravitational search algorithm to analyze the Economic load dispatch problem for three and six unit system. The role of heuristic optimization methods in solving the economic load dispatch problem has been highlighted...
The increase in real power demand on the distribution side of power system affects the cost of power generation. The main objective is to schedule the total demand among all the units in a thermal plant with minimum fuel cost by applying an intelligent technique. There are many conventional and intelligent techniques which are in practice for the economic dispatch of thermal units. In recent days...
According to no free lunch theorem, a single search technique cannot perform best under different conditions. The integration of principally similar search techniques is one of the option, that has been explored to effectively investigate the search area. In order to avoid stagnation at local minima and to enhance the search capability of particle swarm optimization, this paper proposes a technique...
Economic dispatch determines the optimal power generation output to meet the system load at the lowest possible cost. Characteristics of each generating unit may have an impact on the effectivity of the method used in solving economic dispatch problem. Conventional gradient-based methods are inapplicable in economic dispatch problem with non-smooth cost functions and multiple fuel options. In this...
The trends of reducing the lethal and harmful emissions in many developed countries has restricted the power producing companies to keep their lethal fuel emissions of (COx, SOx, NOx) within certain permissible limits. Hence, the problem of economic dispatch of hydrothermal energy systems has been slightly altered to the problem of Environmental Economic Dispatch of Hydrothermal Energy Systems (EEDHES)...
This paper proposes a Gaussian shuffled differential evolution (GSDE) for economic load dispatch problem. Proposed technique employs hybrid shuffled differential evolution with Gaussian mutation operator to blend differential evolution with shuffled frog leaping algorithm. Our approach uses shuffled Gaussian mutation operator for avoiding local optima during optimization and prevents prematurisation...
Economic Load Dispatch (ELD) plays an important role in advanced power system operation and control in recent times. ELD problem was solved by many types of optimization techniques. Here a new optimization method namely Backtracking Search Algorithm (BSA) technique has been used to solve the Economic Load Dispatch problem and compared with Particle Swarm Optimization with Constriction Factor Approach...
With the growth of commercial world, the utilization of electrical energy is also increased. Due to this the need to install large amount of power generation to meet the increasing load has become the basic utility, which is quite complex to distribute the power among large number of units economically in less time. This intricacy made to develop the faster convergent techniques to large systems....
Economic load dispatch problem becomes complex, when renewable energy sources are also considered with thermal power plant. Therefore, it is challenging to find the optimal solution at lower fuel cost, such that generation meets the load demand. This paper is mainly aimed to design economic load dispatch model for thermal and wind power plants. Due to the varying nature of wind speed, probabilistic...
This paper attempts to propose particle swarm optimization algorithm with smart inertia factor (PSO-SIF) to solve the problem of economic emission load dispatch (EELD) in thermal power plants. The aim of EELD solution is synchronous reduction of both fuel costs and emission level. EELD problem is a non-linear and non-convex problem which uses evolutionary algorithms as efficient to solve such problems...
This paper considers the non-convex Economic Dispatch Problem (EDP) with power losses, prohibited operating zones, and generation cost functions modeling both valve-point loading effects and multiple fuel options. This constrained problem is stated as an unconstrained problem by using the augmented Lagrange formulation, while introducing Lagrange multipliers and penalty parameters. Then, a genetic...
This paper presents the application of Bio-inspired algorithms like Particle Swarm Optimization (PSO) and Teaching-learning Based Optimization (TLBO) for solution of economic load dispatch (ELD) problem. The algorithms are used to find the optimum solution with lowest fuel cost for four different network consisting of three, six, fifteen, and twenty generating units respectively for different load...
In present days, power crisis increasing due to increase the consumer's load. To overcome this problem some optimization techniques have been used to solve the economic load dispatch problem. This paper presents an efficient and reliable Biogeography Based Optimization (BBO) algorithm, which is used to solve the Economic Load Dispatch problem of thermal power station even as generator and transmission...
With depleting fossil reserves, increasing cost and global focus on reducing emissions, efforts for increasing participation of renewable energy sources have gained momentum. The smart micro grid technology is therefore growing very fast with the aim of improving efficiency and reliability and facilitating integration of distributed energy resources (DER). The economical operation of smart grid is...
The current paper discusses the analysis of the results that emerged from a field study conducted in two consecutive years, aiming at the assessment of the economic recession's impact on the consumers' behaviour regarding energy consumption and space heating. The field survey was carried out, by means of interviews with questionnaires, in Northern Greece, an area where there is an increased energy...
With an increase in environmental considerations over the years, it has become extremely significant to reduce the emission levels in all areas of technology. Likewise, the problem of Unit Commitment (UC), which has always been thought of as a problem to reduce generation cost also involves an added objective of reducing emission levels. This paper presents a new methodology to solve this multi-objective...
In this paper, the weighted sum Particle Swarm Optimization (WSPSO) technique is projected to address multi-objective Economic Dispatch with emission minimization (EED) problem by generating sets of the Pareto-optimal solutions. These solutions provide many alternate dispatch options for reducing conflicting objectives like cost and harmful gases. A multi-attributed decision making problem consisting...
This paper investigates a new approach of computation using particle swarm in order to resolve economic environmental dispatch problem. This approach is called accelerated multiobjective particle swarm optimization (AMOPSO) which incorporates vector function as objective function and uses matrix computation and updates solutions set, in each iteration, for developing the Pareto front unlike the existing...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.