• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 학술대회 논문집 전문대학교육위원
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• pp.104-106
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• 2000

This paper presents an algorithm for optimal reactive power dispatch problem based on Improved Genetic Algorithm(IGA). Optimal Reactive Power Dispatch (ORPD) is particularized to the minimization of transmission line losses by suitable selection of generator reactive power outputs and transformer tap setting. For the objective, in this paper, Loss Re-Distribution Algorithm(LRDA) is new applied to the equality constraint of ORPD. The proposed method has been evaluated on the IEEE 30 bus system. Results of the application of the method are compared with a base case.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 추계학술대회 논문집 학회본부
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• pp.212-214
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• 1997

This paper presents a genetic algorithm based optimal reactive power dispatch (ORPD) in which voltage dependent load model is considered. The objective of this study is to minimize the transmission loss with consideration of voltage and reactive power constraints. The proposed algorithm has been evaluated with the IEEE 30-bus system. Simulation results, compared with each cases, are presented to show the performance of the proposed method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 추계학술대회 논문집 학회본부 A
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• pp.190-192
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• 1999

This paper presents an algorithm for optimal reactive power dispatch problem based on genetic algorithm. Optimal reactive power dispatch is particularized to the minimization of transmission line losses by suitable selection of generator reactive power outputs and transformer tap settings. To attain for the objective, in this paper, loss re-distribution algorithm(LRDA) is applied to ORPD. The proposed method has been evaluated on the IEEE 30 bus system. Results of the application of the method are compared with a simple genetic algorithm.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 A
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• pp.190-193
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• 2001

This paper presents a linear programming based Optimal Reactive Power Dispatch (ORPD) problem using modified sensitivity method. The proposed model minimizes the real power losses and improves the voltage profiles in the system with consideration of voltage and reactive power constraints. The method employs modified sensitivity relationships of power systems to establish both the objective function for minimizing the system losses and the system performance sensitivities relating dependent and control variables. The proposed algorithm has been evaluated with the IEEE 6-bus and IEEE 30-bus systems.

• 대한전기학회논문지
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• 제32권4호
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• pp.145-154
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• 1983

This paper presents a new method for optimal real and reactive power dispatch for the economic operation of a power system. Unlike the usual approach of minimizing the transmission loss, this method minimizes the total production cost not only for the real power optimization problem, but also for the reactive power optimization. The control variables are real power generation of units for real power optimization, and reactive power optimization. The constraints are the operating limits on these control variables and the limits on the bus voltages. Methematical models are developed to represent the sensitivity relationships between dependent and control variables for both real and reactive power optimization modules, and thus eliminate the use of B-coefficients. In order to handle many functional inequality constraints, a modified version of the gradient projection method is developed for optimization procedure, and has shown a remarkable advantage in computation efficiency.

• 대한전기학회논문지:전력기술부문A
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• 제55권3호
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• pp.133-138
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• 2006

This paper presents an Optimal Power Flow (OPF) algorithm using Interior Point Method (IPM) to swiftly and precisely perform the five minute dispatch. This newly suggested methodology is based on Affine Scaling Interior Point Method which is favorable for large-scale problems involving many constraints. It is also eligible for OPF problems in order to improve the calculation speed and the preciseness of its resultant solutions. Big-M Method is also used to improve the solution stability. Finally, this paper provides relevant case studies to confirm the efficiency of the proposed methodology.

• 전기학회논문지
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• 제57권8호
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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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• 제10권1호
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• pp.18-29
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• 2015

State Estimation (SE) is the basis of a variety of advanced applications used in most modern power systems. An SE problem formed with enough phasor measurement units (PMUs) data is simply a linear weighted least squares problem requiring no iterations. Thus, designing a minimum-cost placement of PMUs that guarantees observability of a power system becomes a worthy challenge. This paper proposes an equivalent integer linear programming method for substation-oriented optimal PMU placement (SOOPP). The proposed method uses an exhaustive search to determine a globally optimal solution representing the best PMU placement for that particular power system. To obtain a more comprehensive model, contingencies and the limitation of the number of PMU measurement channels are considered and embodied in the model as changes to the original constraints and as additional constraints. The proposed method is examined for applicability using the IEEE 14-bus, 118-bus and 300-bus test systems. The comparison between SOOPP results and results obtained by other methods reveals the excellence of SOOPP. Furthermore, practical large-scale power systems are also successfully analyzed using SOOPP.

• Journal of Electrical Engineering and Technology
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• 제11권2호
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• pp.329-337
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• 2016

With the increasing deployment of distributed generators in the distribution system, a very large search space is required when dynamic programming (DP) is applied for the optimized dispatch schedules of voltage and reactive power controllers such as on-load tap changers, distributed generators, and shunt capacitors. This study proposes a new optimal voltage and reactive power scheduling method based on dynamic programming with a heuristic searching space reduction approach to reduce the computational burden. This algorithm is designed to determine optimum dispatch schedules based on power system day-ahead scheduling, with new control objectives that consider the reduction of active power losses and maintain the receiving power factor. In this work, to reduce the computational burden, an advanced voltage sensitivity index (AVSI) is adopted to reduce the number of load-flow calculations by estimating bus voltages. Moreover, the accumulated switching operation number up to the current stage is applied prior to the load-flow calculation module. The computational burden can be greatly reduced by using dynamic programming. Case studies were conducted using the IEEE 30-bus test systems and the simulation results indicate that the proposed method is more effective in terms of saving electric charges and improving the voltage profile than loss minimization.

• Journal of Electrical Engineering and Technology
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• 제8권3호
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• pp.453-463
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• 2013

The probabilistic nature of renewable energy, especially wind energy, increases the needs for new forms of planning and operating with electrical power. This paper presents a novel approach for determining the short-term generation schedule for optimal operations of wind energy-integrated power systems. The proposed probabilistic security-constrained optimal power flow (P-SCOPF) considers dispatch, network, and security constraints in pre- and post-contingency states. The method considers two sources of uncertainty: power demand and wind speed. The power demand is assumed to follow a normal distribution, while the correlated wind speed is modeled by the Weibull distribution. A Monte Carlo simulation is used to choose input variables of power demand and wind speed from their probability distribution functions. Then, P-SCOPF can be applied to the input variables. This approach was tested on a modified IEEE 30-bus system with two wind farms. The results show that the proposed approach provides information on power system economics, security, and environmental parameters to enable better decision-making by system operators.