• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.8
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• pp.47-53
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• 2014

This paper presents an Differential Search(DS) Algorithm for solving the economic load dispatch(ELD) problems with Valve-Point loading constraints. DS algorithm simulates the Brownian-like random-walk movement used by an organism to migrate. Numerical results on a test system consisting of 13 units show that the proposed approach is faster, more robust and powerful than conventional algorithms. Case studies show the simulation results are better than Lagrange method, the Hopfield neural networks and GA.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.11
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• pp.520-527
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• 2001

This paper suggests a new methodology of evolutionary computations - an Adaptive Evolutionary Algorithm (AEA) for solving the Economic Load Dispatch (ELD) problem which has piecewise quadratic cost functions and prohibited operating zones with many local minima. AEA uses a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner in order to take merits of two different evolutionary computations: global search capability of GA and local search capability of ES. In the reproduction procedure, proportions of the population by GA and the population by ES are adaptively modulated according to the fitness. Case studies illustrate the superiority of the proposed methods to existing conventional methods in power generation cost and computation time. The results demonstrate that the AEA can be applied successfully in the solution of ELD with piecewise quadratic cost functions and prohibited operating zones

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.1
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• pp.1-6
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• 2006

The emergence of competitive power market makes dispatch algorithm with transient stability constraints increasingly important for the transparent power system operation. Heuristic and off-line evaluation for the operation point can produce a discrimination among market players in the deregulated power system. In this paper, a dispatch algorithm with transient stability constraints is proposed. Energy margin under the TEF(Transient Energy Function) structure is adopted as a measure for the stability index. Implementation issues and simulation results are discussed in the context of a 10-bus system

• 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.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.571-573
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• 1995

This paper presents a method for optimal dispatch which minimizes transmission losses and improves voltage profile of power systems using genetic algorithm based on the mechanism of natural genetics and natural selection. The constraints are VAR sources(transformer tap, generator voltage magnitude and shunt capacitor/reactor), load bus voltages and generator reactive power. Real variable-based genetic algorithms which can save coding times and maintain the accuracy are applied for optimal dispatch of reactive power. The genes of genetic algorithm consisted of integers for considering discrete VAR sources. A efficient operator for crossover is proposed to consider the effect of close genes. The algorithm proposed can apply to problems for large scale power systems with multi-variables and complex nonlinear functions efficiently. The proposed method is applied to IEEE 30 buses model system to show its effectiveness.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.574-577
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• 1995

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.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.524-527
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• 1995

This paper deals with the optimal dynamic dispatch problem owing to spinning-reserve and power-rate limits. Two computational modules are used in the solution of the problems. The first is an efficient dispatch module for the consideration of reasonable spinning-reserve requirements. The latter os the Lagrange multipliers adjusting module, which is satisfying the Kuhn-Tucker conditions for power-rate constraints. The proposed algorithm obtains very fast solution speed and maintains good accuracy from test examples.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.9
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• pp.550-556
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• 2003

Price-based unit commitment is one of bidding strategies which a Genco may take in a practical manner. For that purpose, it is required for a Genco to decide output levels of its generators at each trade period. In this paper, an economic dispatch of thermal units is proposed considering the quantity of reserve contracts. A gradient projection algorithm is adopted as an optimization tool. A direct form of a projection matrix without any calculation of matrix inverse and multiplications is induced. Besides, it is proved that there is no need to check one of the two optimality conditions in the gradient projection method, which also requires matrix inverse and multiplications.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.12
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• pp.586-591
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• 2005

This paper presents a method of minimizing of generation cost on individual electrical power utility. The method is based on the Economic Dispatch (ED) and linear Available Transfer Capability (ATC). The economic dispatch redistributes the total load to individual units to minimize the generation cost without transmission network constraints. The proposed method is implemented using ATC calculated from Power Transfer Distribution Factor (PTDF) for the transmission network constraints. The performance of the proposed method has been tested for the IEEE-30 bus system. It has also been observed that the results of the proposed method is compared with that of optimal power flow.

• 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.