• 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.

• 전기의세계
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• v.30 no.12
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• pp.817-821
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• 1981

A simple scheme using the single equivalent machine representation, equivalent loss reprsentation and direct hydro-MW representation are applied to economic dispatch for practical applications. A,simple approach to calculation of incremental transmission losses is proposed from the fast decoupled load flow algorithm. This program is presently being tested on KECO system.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.52-54
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• 2000

Almost traditional ELD(Economic Load Dispatch) is hard to apply to power system directly and also OPF(Optimal Power Flow) is not easy to solve the problem. This paper deals with the practical application of ELD with considering power equation.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.1
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• pp.1-8
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• 1992

Hopfield neural network has been applied to the problem of economic load dispatch(ELD) of electric power. The optimum values of neuron potentials are represented in terms of large numbers. The differential synchronous transition mode is used in this simulation. Through case studies, we have shown the possibility of the application of neural network to ELD. In case of including the transmission losses, the proposed method has an advantage that the problem can be solved simply with one neural network, without calculating incremental fuel costs and incremental losses required by traditional method.

• 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.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

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.1111-1113
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• 1998

A robust economic dispatch algorithm involving transmission losses is proposed and investigated for a possibility of on-line applications. In this paper, the penalty factors are calculated directly from transposed Jacobian of load flow analysis with advantages of superiority to B-coefficients method based on its computation time and suitability for real time application since the approach is based on a current system condition. The proposed algorithm is systematically handling the generation capacity constraints with transmission losses. Implementation of the algorithm for IEEE systems and EPRI Scenario systems shows that computation time is enough to apply on-line economic dispatch to large power system and production cost is saved compared with the crude classical economic dispatch algorithm without considering transmission losses.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.9
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• pp.424-430
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• 2001

A multi-level optimal power flow(OPF) algorithm has been evolved from a simple two stage optimal Power flow algorithm for constrained power economic dispatch control. In the proposed algorithm, we consider various constraints such as ower balance, generation capacity, transmission line capacity, transmission losses, security equality, and security inequality constraints. The proposed algorithm consists of four stages. At the first stage, we solve the aggregated problem that is the crude classical economic dispatch problem without considering transmission losses. An initial solution is obtained by the aggregation concept in which the solution satisfies the power balance equations and generation capacity constraints. Then, after load flow analysis, the transmission losses of an initial generation setting are matched by the slack bus generator that produces power with the cheapest cost. At the second stage we consider transmission losses. Formulation of the second stage becomes classical economic dispatch problem involving the transmission losses, which are distributed to all generators. Once a feasible solution is obtained from the second stage, transmission capacity and other violations are checked and corrected locally and quickly at the third stage. The fourth stage fine tunes the solution of the third stage to reach a real minimum. The proposed approach speeds up the two stage optimization method to an average gain of 2.99 for IEEE 30, 57, and 118 bus systems and EPRI Scenario systems A through D testings.

• 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.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.1064-1072
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• 2017

The power of controlled generators in microgrids randomly fluctuate because of the stochastic volatility of the outputs of photovoltaic systems and wind turbines as well as the load demands. To address and dispatch these stochastic factors for daily operations, a dynamic economic dispatch model with the goal of minimizing the generation cost is established via chance-constrained programming. A Monte Carlo simulation combined with particle swarm optimization algorithm is employed to optimize the model. The simulation results show that both the objective function and constraint condition have been tightened and that the operation costs have increased. A higher stability of the system corresponds to the higher operation costs of controlled generators. These operation costs also increase along with the confidence levels for the objective function and constraints.