• Proceedings of the KIEE Conference
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• 1987.07a
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• pp.640-643
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• 1987

A probabilistic production costing model based on the economic load dispatch has been developed. Objective function is composed of fuel cost which is a function of generation output and the failure cost. Coefficients of the failure cost is determined from the known equivalent generation cost. The model is compared with other existing methodolgies and the excellent results are obtained.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.7
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• pp.318-323
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• 2001

This paper proposes an efficient method of On-Line Economic Load Dispatch(ELD) using Evolutionary Programming(EP) technique at KwangYang steel works. The economic operation of steel works is done by experienced engineer. So far, there is no formulation and algorithm of economic operation of steel works. In this paper, we propose the formulation and On-Line algorithm of economic operation of steel works. The EP technique is the kind of Evolutionary Computation(EC), which has become a candidate for many optimization applications due to its flexibility and efficiency. Based on the EP technique, the proposed algorithm is capable of not only solving the economic problem, but also obtaining the global optimal solutions within reasonable execution time. To validate our proposed approach, the algorithm is demonstrated on many sample systems and compared to actual values of steel works.

• Proceedings of the KIEE Conference
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• 2000.11a
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• pp.116-118
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• 2000

This paper proposes an efficient method of On-Line Economic Load Dispatch(ELD) using Evolutionary Programming(EP) technique at Kwangyang steel works. The economic operation of steel works is done by experienced engineer. So far, there is no formulation and algorithm of economic operation of steel works. In this paper, we propose the formulation and On-Line algorithm of economic operation of steel works. The EP technique is the kind of Evolutionary Computation(EC) which has become a candidate for many optimization applications due to its flexibility and efficiency. Based on the EP technique, the proposed algorithm is capable of not only solving the economic problem, but also obtaining the global optimal solutions within reasonable execution time. To validate our proposed approach, the algorithm is demonstrated on many sample systems and compared to actual values of steel works.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.8
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• pp.1327-1333
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• 2008

Since Cost Based Pool markets has been continued to power markets, Genco. needs economic analysis about investment in power plants. Particularly most Private Genco.s have presently a construction plan about LNG combined cycle thermal power plants. In this paper, we propose a economic analysis method of LNG combined cycle thermal power plants using Economic Dispatch and Optimal Power Flow in CBP markets. Also we develope computation model using it for decision making to build a plant. This method can consider a variation of power facility like power plants and transmission lines in CBP markets. Finally, this dissertation provides a relevant case study to confirm the effect of cost factor to economical efficiency.

• Journal of Electrical Engineering and Technology
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• v.3 no.1
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• pp.52-59
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• 2008

This paper describes the secant method for solving the economic dispatch (ED) problem with generator constraints and transmission losses. The ED problem is an important optimization problem in the economic operation of a power system. The proposed algorithm involves selection of minimum and maximum incremental costs (lambda values) and then the evaluation of optimal lambda at required power demand is done by secant method. The proposed algorithm has been tested on a power system having 6, 15, and 40 generating units. Studies have been made on the proposed method to solve the ED problem by taking 120 and 200 units with generator constraints. Simulation results of the proposed approach were compared in terms of solution quality, convergence characteristics, and computation efficiency with conventional methods such as lambda iterative method, heuristic methods such as genetic algorithm, and meta-heuristic methods like particle swarm optimization. It is observed from different case studies that the proposed method provides qualitative solutions with less computational time compared to various methods available in the literature.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.1100-1102
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• 1998

This paper presents the Two-Phase Neural Network(TPNN) to slove the Optimal Economic Environmental Dispatch problem of thermal generating units in electric power system. The TPNN, Compared with other Neural Networks, is very accurate and it takes smaller computer time for a optimization problem to converge. In this work, in order to provide useful information to the system operator, we are used the total environmental weight and relative weighting of individual insults(e.g., $SO_2$, $NO_X$ and $CO_2$) also, presented the simulation results of the dispatch changes according to the weights. The Two-Phase Neural Network is tested on a 11-unit 3-pollutant system to prove of effectiveness and applicability.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.8
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• pp.484-489
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• 2004

When the energy resource available to a particular plant (be it coal, oil, gas, water, or nuclear fuel) is a limiting factor in the operation of the plant, the entire economic dispatch calculation must be done differently. Each economic dispatch calculation must account for what happened before and what will happen in the future. This paper presents a formulation and a solution method for the optimization problem with a fuel constraint in a competitive electricity market. Take-or- Pay (TOP) contract for an energy resource is the typical constraint as a limiting factor. Two approaches are proposed in this paper for modeling the dispatch calculation in a market mechanism. The approaches differ in the subject who considers and inserts the fuel-constraint into its optimization problem. Market operator and each power producer having a TOP contract are assumed as such subjects. The two approaches are compared from the viewpoint of profits. surplus. and social welfare on the basis of Nash Equilibrium.

• Journal of Energy Engineering
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• v.6 no.2
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• pp.129-136
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• 1997

This paper presents a new economic load dispatch considering atmospheric emissions such as NOx and SO$_2$caused by the operation of fossil-fueled thermal generation in power systems. The proposed method is described for scheduling their output of thermal power units so as to comply with total emission constraint, area emission constraint and the both of those constraints. Also, by using a trade-off curve, representing all dispatch alternatives and conflict between the emission and the fuel cost, the sensitivity analysis of the emission and the fuel cost is applied to this algorithm. By the way, this proposed method is analyzed how dispatch changes as a function of the total environmental cost, and as a function of the relative weighting of individual environmental insults, e.g, NOx and SO$_2$. By applying the proposed method to the system, the usefulness of this method is verified.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.255-262
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• 2015

In the absence of a deterministic algorithm for economic load dispatch optimization problem (ELDOP), existing algorithms proposed as solutions are inevitably non-deterministic heuristic algorithms. This paper, therefore, proposes a balance-and-swap algorithm to solve an ELDOP. Firstly, it balances the initial value to ${\Sigma}P_i=P_d$ by subsequently reducing power generation for each adult-step and baby-step and selects the minimum cost-generating method. Subsequently, it selects afresh the minimum cost-generating method after an optimization of the previously selected value with adult-step baby-step swap and giant-step swap methods. Finally, we perform the $P_i{\pm}{\beta}$, (${\beta}=0.1,0.01,0.001,0.0001$) swap. When applied to the 3 most prevalently used economic load dispatch problem data, the proposed algorithm has obtained improved results for two and a result identical to the existing one for the rest. This algorithm thus could be applied to ELDOP for it has proven to consistently yield identical results and to be applicable to all types of data.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.6
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• pp.1023-1030
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• 2007

This paper presents a new and efficient approach for solving the economic dispatch (ED) problems with nonconvex cost functions using particle swarm optimization (PSO). Although the PSO is easy to implement and has been empirically shown to perform well on many optimization problems, it may easily get trapped in a local optimum when solving problems with multiple local optima and heavily constrained. This paper proposes an improved PSO, which combines the conventional PSO with chaotic sequences (CPSO). The chaotic sequences combined with the linearly decreasing inertia weights in PSO are devised to improve the global searching capability and escaping from local minimum. To verify the feasibility of the proposed method, numerical studies have been performed for two different nonconvex ED test systems and its results are compared with those of previous works. The proposed CPSO algorithm outperforms other state-of-the-art algorithms in solving ED problems, which consider valve-point and multi-fuels with valve-point effects.