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 presents a proposed cuckoo search algorithm with interactive learning and linear decreasing probability strategy (CSIL) to solve the economic dispatch problem with power balance, prohibited operating zones, valve point effect, and ramp rate. In the new approach, interactive learning strategy helps the nest to exchange good information from each other. Meanwhile, the linear decreasing probability...
This paper aimed at exploring the performance of Particle Swarm Optimisation with Exponentially Varying Inertia Weight Factor (PSO-EVIWF) for solving Multi-Area Economic Dispatch (MAED) problem with tie line constraints considering valve-point loading in each area. The effectiveness of the proposed algorithm has been verified on 4 interconnected areas with 16 generators standard test system. The paper...
Distributed optimization problems are generally described as the minimization of a global objective function in a system, where each agent can get information only from a neighborhood defined by a network topology. To solve this problem, we present a local strategy based on population dynamics (i.e., the local replicator equation (LRE)), to define functions and tasks assigned to each node in a system...
The practical economic dispatch (ED) problems have many non-convex characteristics, which makes the searching of the global optimum difficult when using traditional mathematical methods. This paper presents a novel hybrid algorithm (HA) to the ED problems based on the particle swarm optimization (PSO) technique and differential evolution (DE) algorithm. Since the standard PSO has the adversity of...
This paper proposes a new hybrid algorithm of combining the conventional Particle Swarm Optimization (PSO) algorithm with Differential Evolution (DE) strategy, named by the authors as Particle Swarm Differential Evolution Optimization (PSDEO) to enhance better balance between local and global search abilities, while solving the economic load dispatch (ELD) problems considering all practical complex...
In this paper, a self-adaptive differential evolution algorithm (SaDEA) is proposed for solving conventional economic dispatch (ED) problem with transmission losses consideration. The purpose of ED problem is to minimize the total fuel cost of thermal power plants associated with the technical operation and economical constraints. The software development has been performed within the mathematical...
This paper introduced a genetic particle evolutionary swarm optimization (GPESO) for solving the economic dispatch (ED) in power systems. GPESO is based on the genetic particle swarm optimization (GPSO). GPSO was derived from the original particle swarm optimization (OPSO), which was incorporated with the genetic reproduction mechanisms, namely crossover and mutation. To enhance the search performance...
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.