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Biogeography-Based Optimization (BBO) is a recently developed global optimization algorithm and has shown its ability to solve complex optimization problem. The convergence of original BBO to the optimum value is slow as it lacks the exploration ability. An Accelerated Biogeography-Based Optimization (ABBO) technique is proposed in this paper to solve economic load dispatch problem. In this paper,...
In this paper, the nonlinear constrained multi-objective environmental economic dispatch (EED) problem is solved using fast multi-objective evolutionary programming (FMOEP). Due to the global warming by fossil fuel, environmental concern becomes more and more important in recent years. The purpose of multi-objective optimization algorithm is minimizing all the different objectives simultaneously and...
This paper proposes a version of fuzzy controlled parallel particle swarm optimization approach based decomposed network (FCP-PSO) to solve large nonconvex economic dispatch problems. The proposed approach combines practical experience extracted from global database formulated in fuzzy rules to adjust dynamically the three parameters associated to PSO mechanism search. The adaptive PSO executed in...
Economic Load Dispatch (ELD) problems are nonlinear constrained problems which occupy an important role in the economic operation of power system. Recently, as an alternative to the conventional mathematical approaches, evolutionary algorithms have been given much attention by researchers due to their ability to find good solutions in ELD problems. In this paper, a biogeography based-optimization...
China is going to realize clean power generation in the future, and introducing energy-saving dispatch is one of the important measures taken. Although this new dispatch model can generate great benefit for the society, the utility will bare increasing reserve purchasing costs. This paper dealt with the optimal reserve purchasing strategy for the utilities. The optimal energy purchase model under...
To deal with the uncertainty in the demand and the lack of compliance from generators to follow instructions, Independent System Operators (ISO) evaluate commitment and dispatch solutions for different demand scenarios (low, medium and high). A robust dispatch algorithm that guarantees the ??reach-ability?? of the low and high demand scenarios from the medium demand dispatch is proposed in this paper...
This paper presents an application of Bees Algorithm (BA) for solving various types of Economic Dispatch (ED) problem. Complete ED problem formulation prohibited, operating zones, ramp-rate limits, and non-smooth or non-convex cost functions arising from the use of multiple fuels should be taken into consideration. To show its efficiency, the Bee algorithm is applied to solve various types ED problems...
This Paper presents a Biogeography-Based Optimization (BBO) algorithm to solve Non-convex Economic Load Dispatch (ELD) problems of thermal plants in a power system. The Proposed methodology can take care of economic load dispatch problems involving constraints such as valve point loading, ramp Rate limit and Prohibited Operating zone. Biogeography deals with the geographical distribution of biological...
This paper presents the application of bio-inspired artificial bee colony (ABC) optimization to constrained economic load dispatch problem. Independent simulations were performed over various systems with different number of generating units having constraints like prohibited operating zones and ramp rate limits. The performance is also compared with other existing similar approaches. The proposed...
This paper presents a novel optimization approach using improved harmony search (IHS) algorithm to solve economic power dispatch problem. The proposed methodology easily takes care of different equality and inequality constraints of the power dispatch problem to find the optimal solution. To show its efficiency, the proposed algorithm is applied to single area and multi area system of four area having...
This paper presents potential benefits of applying model predictive control (MPC) to solving the multi-objective economic/environmental dispatch problem in electric power systems with many intermittent resources. Based on the predictive model of the available output in the next short time period (e.g. 5 minutes) from the intermittent resources, this paper introduces a look-ahead optimal control algorithm...
To incorporate large-scale wind generation in the Midwest ISO footprint, bulk transmission planning is necessary. In this paper, transmission planning for large-scale wind power is explained in detail. In expansion planning, the wind generation capacities are estimated from state Renewable Portfolio Standards (RPS) and the wind generator locations are chosen based on best wind source zones. From economic...
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...
A comparative analysis using different intelligent techniques has been carried out for the economic load dispatch (ELD) problem considering line flow constraints for the regulated power system to ensure a practical, economical and secure generation schedule. The objective of this paper is to minimize the total production cost of the thermal power generation. Economic load dispatch (ELD) has been applied...
This paper presents a new efficient approach to economic dispatch (ED) problems with smooth and non smooth cost functions using a particle swarm optimization (PSO) technique. The practical ED problems have nonsmooth cost functions with equality and inequality constraints that make the problem of finding the global optimum difficult using any mathematical approaches. In this paper a modified random...
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...
Computer simulation is an increasingly popular tool for determining the most suitable hybrid energy system type, design and control for an isolated community or a cluster of villages. This paper presents the development of the optimum control algorithm based on combined dispatch strategies, to achieve the optimal cost of battery incorporated hybrid energy system for electricity generation, during...
This paper addresses potential benefits of applying model predictive control (MPC) to solving the energy dispatch problem in electric energy systems with many intermittent renewable resources. Based on predicting the output from the intermittent resources, this paper introduces a look-ahead optimal control algorithm for dispatching the available generation with the objective of minimizing the total...
This paper presents a method for environmentally constrained economic dispatch in power systems. Economic dispatch problem is basically an optimization problem where objective function may be highly nonlinear, non-convex, non-differentiable and may have multiple local minima. Therefore classical optimization methods may be trapped to any local minima and may not be able to reach the global minima...
In this paper two loss allocation (LA) schemes based on the principle of equivalent bilateral exchanges (EBEs) and the network Z-bus matrix are compared with each other. The modified IEEE 14-bus network has been selected as case study. Several operating conditions such as, load increment and system congestions are applied to the test system in order to evaluate the loss allocation methods. In the...
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