• Journal of Electrical Engineering and Technology
• /
• 제7권5호
• /
• pp.681-688
• /
• 2012

This paper presents the application of Differential Evolution (DE) algorithm to obtain a solution for Bid Based Dynamic Economic Dispatch (BBDED) problem including the transmission losses and to maximize the social profit in a deregulated power system. The IEEE-30 bus test system with six generators, two customers and two trading periods are considered under various bidding strategies in a day-ahead electricity market. By matching the bids received from supplying and distributing entities, the Independent System Operator (ISO) maximize the social profit, (with the choices available). The simulation results of DE are compared with the results of Particle swarm optimization (PSO). The results demonstrate the potential of DE algorithm and show its effectiveness to solve BBDED.

• Journal of Electrical Engineering and Technology
• /
• 제12권4호
• /
• pp.1417-1426
• /
• 2017

Power system analysis, Non-Convex Economic Dispatch (NED) is considered as an open and demanding optimization problem. Despite the fact that realistic ED problems have non-convex cost functions with equality and inequality constraints, conventional search methods have not been able to effectively find the global answers. Considering the great potential of meta-heuristic optimization techniques, many researchers have started applying these techniques in order to solve NED problems. In this paper, a new and efficient approach is proposed based on imperialist competitive algorithm (ICA). The proposed algorithm which is named multi-operator ICA (MuICA) merges three operators with the original ICA in order to simultaneously avoid the premature convergence and achieve the global optimum answer. In this study, the proposed algorithm has been applied to different test systems and the results have been compared with other optimization methods, tending to study the performance of the MuICA. Simulation results are the confirmation of superior performance of MuICA in solving NED problems.

• 대한전기학회논문지
• /
• 제41권1호
• /
• pp.1-8
• /
• 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.

• 전기학회논문지P
• /
• 제59권3호
• /
• pp.245-252
• /
• 2010

This paper proposes a constrained multi-area dispatch scheduling algorithm applicable to interconnected power system operations. The dispatch scheduling formulated as an MIP problem can be efficiently computed by GBD algorithm. GBD guarantees adequate computation speed and solution convergence by reducing the dimension of the dispatch scheduling problem. In addition, the regional decomposition technique based on ADM is introduced to obtain efficient inter-temporal OPF solution. It can find the most economic dispatch schedule incorporating power transactions without each regional utility's private information open.

• 한국인터넷방송통신학회논문지
• /
• 제16권2호
• /
• pp.181-188
• /
• 2016

본 논문은 경제급전 최적화 문제에 개별 발전회사별로 독립적으로 경제급전을 수행하는 방법에 비해 중앙에서 통합하여 경제급전 최적화를 수행하는 경우가 보다 경제적임을 보였다. 이 경우에 적용된 알고리즘으로 밸브지점으로 발전량을 조절하는 균형방법을 수행한 후 발전량을 감소시킬 때의 비용 감소분과 증가시킬 때의 비용 증가분 차이로 발전량을 상호 교환하는 방법으로 최적화를 수행하였다. 10대, 13대과 40대-발전기를 독립적으로 운영하는 경우와 통합된 63대-발전기를 경제급전하는 경우를 비교한 결과 통합운영 방법이 독립적 경제급전에 비해 발전비용을 획기적으로 감소시켜 경제적인 이익을 극대화 시킬 수 있음을 보였다.

• 한국컴퓨터정보학회논문지
• /
• 제17권11호
• /
• pp.189-196
• /
• 2012

본 논문은 동적 경제급전의 최적화 문제를 풀기 위해 교환 알고리즘을 제안하였다. 제안된 알고리즘은 첫 번째로, 발전단가 $C_i^{max}/P_i^{max}$가 비싼 발전기는 가동을 중지시키는 개념을 도입하여 총 요구량 $P_d$와 총 발전량 ${\Sigma}P_i$의 균형을 맞추었다. 다음으로 발전량을 $P_i=P_i{\pm}{\Delta}$, (${\Delta}$=1.0, 0.1, 0.01, 0.001)에 대해 $_{max}[F(P_i)-F(P_i-{\Delta})]$ > $_{min}[F(P_j+{\Delta})-F(P_j)]$, $i{\neq}j$이면 $P_i=P_i-{\Delta}$, $P_j=P_j+{\Delta}$로 발전량을 교환하는 방법을 적용하였다. 동적 경제급전 문제의 시험사례에 제안된 알고리즘을 적용한 결과 기존의 휴리스틱 알고리즘 최적화 발전비용을 크기 감소시켜 경제적인 이익을 극대화 시켰다.

• Journal of Electrical Engineering and Technology
• /
• 제3권2호
• /
• pp.199-206
• /
• 2008

The introduction of competition in electricity markets emphasizes the importance of sufficient transmission capacities to guarantee effective power transactions. Therefore, for the economic and stable electric power system operation, transmission security constrains should be incorporated into the dispatch scheduling problem. With the intent to solve this problem, we decompose a dispatch scheduling problem into a master problem(MP) and several subproblems(SPs) using Benders decomposition. The MP solves a general optimal power flow(OPF) problem while the SPs inspect the feasibility of OPF solution under respective transmission line contingencies. If a dispatch scheduling solution given by the MP violates transmission security constraints, then additional constraints corresponding to the violations are imposed to the MP. Through this iterative process between the MP and SPs, we derive an optimal dispatch schedule incorporating the post-contingency corrective rescheduling. In addition, we consider interruptible loads as active control variables since the interruptible loads can participate as generators in competitive electricity markets. Numerical examples demonstrate the efficiency of the proposed algorithm.

• Journal of Electrical Engineering and Technology
• /
• 제9권2호
• /
• pp.423-432
• /
• 2014

Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is applied for solving Combined Economic Emission Dispatch (CEED) problem with valve-point loading of thermal generators. This CEED problem with valve-point loading is a nonlinear, constrained multi-objective optimization problem, with power balance and generator capacity constraints. The valve-point loading introduce ripples in the input-output characteristics of generating units and make the CEED problem as a nonsmooth optimization problem. To validate its effectiveness of NSGA-II, two benchmark test systems, IEEE 30-bus and IEEE 118-bus systems are considered. To compare the Pareto-front obtained using NSGA-II, reference Pareto-front is generated using multiple runs of Real Coded Genetic Algorithm (RCGA) with weighted sum of objectives. Comparison with other optimization techniques showed the superiority of the NSGA-II approach and confirmed its potential for solving the CEED problem. Numerical results show that NSGA-II algorithm can provide Pareto-front in a single run with good diversity and convergence. An approach based on Technique for Ordering Preferences by Similarity to Ideal Solution (TOPSIS) is applied on non-dominated solutions obtained to determine Best Compromise Solution (BCS).

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1998년도 하계학술대회 논문집 C
• /
• pp.1100-1102
• /
• 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.

• 대한전기학회논문지:전력기술부문A
• /
• 제53권8호
• /
• pp.484-489
• /
• 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.