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Wind power is developing rapidly all around the world and at present total installed capacity is about 120,000 MW. Due to continuous improvements in turbine efficiency and increasing fuel prices, wind power is becoming economically competitive compared to conventional power generation. Combined economic/emission dispatch (CEED) involves the simultaneous optimization of two conflicting objectives namely...
The conventional economic dispatch problem in electric power generation is mainly concerned with minimizing operating cost. This study presents a multiple PSO algorithm of solving the multi-objective power dispatch problem that minimizes both the fuel cost and environmental impact from emission. An integrated factor is used to combine the multiple objective functions. The PSO method and a distance...
This paper proposes a new objective function for solving the optimal management of MicroGrid (MG) problem. This objective function aims to minimize MicroGrid's operating cost as well as the emissions of atmospheric pollutants while constraining it to meet the load demands. Some Objective constraints are presented in this paper for the safety of MG system. Moreover, the particle swarm-based-simulated...
This paper presents a fuzzy controlled parallel particle swarm optimization approach based decomposed network (FCP-PSO) to solving the large economic power dispatch with non-smooth cost fuel functions. The proposed approach combines practical experience extracted from global database formulated in fuzzy rules, the adaptive PSO executed in parallel based in decomposed network procedure as a local search...
This paper presents a new optimization algorithm, Music Based Harmony Search (MBHS) applied to the Optimal Power flow (OPF) problem with line constraints for minimizing the Fuel costs together with Generator Reactive power losses. The proposed method is compared with other optimization techniques like Simple Genetic Algorithm (SGA), Adaptive Genetic Algorithm (AGA) and Particle Swarm Optimization...
System security in the generation market is one of the important aspects in power system operation under deregulated environment. It becomes more crucial when thermal power system is integrated with wind system. This paper presents an approach to determine the security constrained unit commitment (SCUC) for thermal units integrated with wind power system. A Lagrangian relaxation based algorithm with...
Energy management of CHP-based microgrid is largely dependent on optimal deployment of distributed energy resources (DERs), where optimal bus-locations, capacity-sizes, and types are three major points to be considered in a microgrid planning. Investment and O&M cost, including fuel cost, are solely dependent on types of DERs. Present paper searches a way-out of how a electrical tracking demand...
This paper proposed multi-objective fuzzy particle swarm optimization (MOFPSO) for the Proton Exchange Membrane Fuel Cells (PEMFC) generation system. The PEM fuel cell generation system efficiency decreases as its output power increases. Thus, an optimum efficiency should exist and should result in a cost-effective PEM fuel cell generation system. In the optimization approach, the efficient and economic...
This paper presents the use of Pareto optimization techniques that was previously analyzed with small scale power plant models where results could be verified analytically. Further research has been conducted into the use of applying these techniques to large scale models and analyzing performance. These approaches have been verified to scale well to larger applications. Through the use of multi-objective...
The energy management strategy renders significant impacts on the operating performance of plug-in hybrid electric vehicles (PHEV), which are similar to the traditional hybrid electric vehicle. A comprehensive methodology based on Particle Swarm Optimization (PSO) is presented in the paper to achieve parameter optimization for the energy management strategy, with a view to reducing the fuel consumption...
A new multi-objective evolutionary algorithm for Environmental/Economic power Dispatch (EED) problem based on Particle Swarm Optimization (PSO) is proposed in this paper. The new algorithm has adopted the maintenance method of Pareto candidate solution set based on the max-min distance density. The algorithm effectively guarantees the convergence of the algorithm and the diversity solutions. The performance...
The matching design problem of the ship-engine-propeller is a non-linear constrained multi-objective optimization problem which is performed based on multiple objectives,such as system efficiency and the life cycle cost. A multi-objective particle swarm optimization (MOPSO) approach for matching design problem of the ship-engine-propeller problem is presented in this paper.A real matching design problem...
This paper proposes an improved approach based on conventional particle swarm optimization (PSO) for solving an economic dispatch(ED) problem with considering the generator constraints. The mutation operators of the differential evolution (DE) are used for improving diversity exploration of PSO, which called hybrid particle swarm optimization - differential evolution (PSO-DE). The mutation operators...
Hybrid fuel cell power plants have been introduced as an alternative power source for distributed generation, which can improve the power quality and reliability of the power grid. One of the most important issues of plant operations is the optimal control of the power plant, which will provide significant economic and environmental benefits in the long run. As a commercialized fuel cell technology,...
In this work, multi-objective optimization for design of a benchmark cogeneration system known as CGAM cogeneration system is performed. In optimization approach, the exergetic and economic aspects are considered, simultaneously. The thermoeconomic objective is minimized while the exergetic objective is maximized. A multi-objective particle swarm optimization (MOPSO) algorithm is used to find a set...
Ship design is a complex endeavor requiring the successful coordination of many different disciplines. According to various disciplines requirements, how to get a balanced performance is imperative in ship design. Thus, a all-in-one Multidisciplinary Design Optimization (MDO) approach is proposed to get the optimum performance of the ship considering three disciplines, structure; cargo loads and power...
Dynamic economic dispatch (DED) problem is an optimization problem with an objective to determine the optimal combination of power outputs for all generating units over a certain period of time in order to minimize the total fuel cost while satisfying dynamic operational constraints and load demand in each interval. Recently social foraging behavior of Escherichia coli bacteria has been explored to...
The dynamic economic dispatch (DED) is an optimization problem with an objective to determine the optimal combination of power outputs for all generating units over a certain period of time in order to minimize the total fuel cost while satisfying dynamic operational constraints and load demand in each interval. Social foraging behavior of Escherichia coli bacteria has been explored to develop a novel...
In this paper, a new hybrid meta-heuristic method is proposed to solve a unit commitment (UC) problem with nonsmooth fuel cost functions effectively. The proposed method focuses on global optimization in a sense that a generation company need carry out the cost reduction under competitive environment. The proposed method integrates parallel evolutionary particle swarm optimization (PEPSO) with variable...
This paper presents biogeography-based optimization (BBO) technique for solving constrained economic dispatch problems in power system. Many nonlinear characteristics of generators, like valve point loading, ramp rate limits, prohibited zone, and multiple fuels cost functions are considered. Two Economic Load Dispatch (ELD) problems with different characteristics are applied and compared its solution...
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