• Journal of Electrical Engineering and Technology
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• v.4 no.3
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• pp.337-345
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• 2009

Deregulation in power industry has made the reactive power ancillary service management a critical task to power system operators from both technical and economic perspectives. Reactive power management in power systems is a complex combinatorial optimization problem involving nonlinear functions with multiple local minima and nonlinear constraints. This paper proposes a practical market-based reactive power ancillary service management scheme to tackle the challenge. In this paper a new model for voltage security and reactive power management is presented. The proposed model minimizes reactive support cost as an economic aspect and insures the voltage security as a technical constraint. For modeling validation study, two optimization algorithm, a genetic algorithm (GA) and particle swarm optimization (PSO) method are used to solve the problem of optimum allocation of reactive power in power systems under open market environment and the results are compared. As a case study, the IEEE-30 bus power system is used. Results show that the algorithm is well competent for optimal allocation of reactive power under practical constraints and price based conditions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.8
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• pp.923-929
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• 2019

The stability of the propulsion system is crucial for the autonomous vessel. Multiple power generation and propulsion systems should be provided for the stability of the propulsion system. High power generation capacity is calculated for stability, resulting in economical decline due to low load operation. To solve this problem, we need to optimize the power system. In this paper, an OPMS for electric propulsion ship is constructed. The OPMS consists of a hybrid power generation system, an energy storage system, and a control load system. The power generation system consists of a dual fuel engine, the energy storage system is a battery, and the control load system consists of the propulsion load, continuous load, intermittent load, cargo part load and deck machine load. The power system was constructed by modeling the characteristics of each system. For the experiment, a scenario based on ship operation was prepared and the stability and economical efficiency were compared with existing electric propulsion ships.

• Nuclear Engineering and Technology
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• v.54 no.8
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• pp.2840-2851
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• 2022

Electric boilers (EBs) are the backup steam source for the auxiliary steam system of high-temperature gas-cooled reactor nuclear power plants. When the plant is in normal operations, the EB is always in hot standby status. However, the current hot standby operation strategy has problems of slow response, high power consumption, and long operation time. To solve these problems, this study focuses on the optimization of hot standby operations for the EB system. First, mathematical models of an electrode immersion EB and its accompanying deaerator were established. Then, a control simulation platform of the EB system was developed in MATLAB/Simulink implementing the established mathematical models and corresponding control systems. Finally, two optimization strategies for the EB hot standby operation were proposed, followed by dynamic simulations of the EB system transient from hot standby to normal operations. The results indicate that the proposed optimization strategies can significantly speed up the transient response of the EB system from hot standby to normal operations and reduce the power consumption in hot standby operations, improving the dynamic performance and economy of the system.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.742-751
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• 2018

Electric vehicles (EV) are emerging as the future transportation vehicle reflecting their potential safe environmental advantages. Vehicle to Grid (V2G) system describes the hybrid system in which the EV can communicate with the utility grid and the energy flows with insignificant effect between the utility grid and the EV. The paper presents an optimal power control and energy management strategy for Plug-In Electric Vehicle (PEV) charging stations using Wind-PV-FC-Battery renewable energy sources. The energy management optimization is structured and solved using Multi-Objective Particle Swarm Optimization (MOPSO) to determine and distribute at each time step the charging power among all accessible vehicles. The Model-Based Predictive (MPC) control strategy is used to plan PEV charging energy to increase the utilization of the wind, the FC and solar energy, decrease power taken from the power grid, and fulfil the charging power requirement of all vehicles. Desired features for EV battery chargers such as the near unity power factor with negligible harmonics for the ac source, well-regulated charging current for the battery, maximum output power, high efficiency, and high reliability are fully confirmed by the proposed solution.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2145-2157
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• 2018

Congestion Management (CM) is an attractive research area in the electrical power transmission with the power compensation abilities. Reconfiguration and the Flexible Alternating Current Transmission Systems (FACTS) devices utilization relieve the congestion in transmission lines. The lack of optimal power (real and reactive) usage with the better transfer capability and minimum cost is still challenging issue in the CM. The prediction of suitable place for the energy resources to control the power flow is the major requirement for power handling scenario. This paper proposes the novel optimization principle to select the best location for the energy resources to achieve the real-reactive power compensation. The parameters estimation and the selection of values with the best fitness through the Symmetrical Distance Travelling Optimization (SDTO) algorithm establishes the proper controlling of optimal power flow in the transmission lines. The modified fitness function formulation based on the bus parameters, index estimation correspond to the optimal reactive power usage enhances the power transfer capability with the minimum cost. The comparative analysis between the proposed method with the existing power management techniques regarding the parameters of power loss, cost value, load power and energy loss confirms the effectiveness of proposed work in the distributed renewable energy systems.

• Journal of Electrical Engineering and Technology
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• v.4 no.4
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• pp.467-475
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• 2009

Congestion management is one of the technical challenges in power system deregulation. This paper presents single objective and multi-objective optimization approaches for optimal choice, location and size of Static Var Compensators (SVC) and Thyristor Controlled Series Capacitors (TCSC) in deregulated power system to improve branch loading (minimize congestion), improve voltage stability and reduce line losses. Though FACTS controllers offer many advantages, their installation cost is very high. Hence Independent System Operator (ISO) has to locate them optimally to satisfy a desired objective. This paper presents optimal location of FACTS controllers considering branch loading (BL), voltage stability (VS) and loss minimization (LM) as objectives at once using GA. It is observed that the locations that are most favorable with respect to one objective are not suitable locations with respect to other two objectives. Later these competing objectives are optimized simultaneously considering two and three objectives at a time using multi-objective Strength Pareto Evolutionary Algorithms (SPEA). The developed algorithms are tested on IEEE 30 bus system. Various cases like i) uniform line loading ii) line outage iii) bilateral and multilateral transactions between source and sink nodes have been considered to create congestion in the system. The developed algorithms show effective locations for all the cases considered for both single and multiobjective optimization studies.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.3
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• pp.370-374
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• 2015

Various protective equiptments are used for the power system control and protection. Numerous facilities are monitored at the same time in real time and introduction of optimization method and analysis of the method are required for generation control and facility management considering the demand fluctuations. However, the existing system analysis programs are difficult to link with the other sw and there are some problems with user convenience. To solve these problems the present conditions of the system are figured out in real time and the equipment insert method was estimated by optimization method, and the system that showed the system analysis program is developed. PSS/E has been used as system anlysis program for stabilizing system development which applied the optimization. method and Python language is applied in order to link the input and output values with the DB automatically. Lastly, DLL of matlab has been made included in C++ for solving the objective function using opmization method.By linking this to DB, power flow was calculated in PSS/E and the result was represented by Intouch screen.

• Journal of Power System Engineering
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• v.17 no.5
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• pp.64-68
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• 2013

One of the water management goals in PEM fuel cell is to avoid flooding and drying in the membrane, therefore the air humidification process is required. In order to increase water removal out of the membrane, the water management system may require the dehumidification process and it also requires a large space for application, moreover the process time is slow. In conformity with this fact, this present study proposes an advanced dynamic fuel cell water management which can be an intermittent optimization control using air flow rate instead of the air humidity as an variable in the optimization process. The results of this study have shown that the membrane flooding and drying can be avoided after being assisted by air velocity controlling method.

• Proceedings of the KIPE Conference
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• 2012.11a
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• pp.33-34
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• 2012

As the distributed power system with PV and ESS is highlighted to be one of the most prominent structure to replace the traditional electric power system, power flow scheduling is expected to bring better system efficiency. Optimal energy management system (EMS) where the power from PV and the grid is managed in time-domain using ESS needs an optimization process. In this paper, main optimization method is implemented using dynamic programming (DP). To overcome the drawback of DP in which ideal future information is required, prediction stage precedes every EMS execution. A simple auto-regressive moving-average (ARMA) forecasting followed by a PI-controller updates the prediction data. Assessment of the on-line optimal EMS scheme has been evaluated on several cases.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.12
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• pp.1965-1970
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• 2016

This paper studies generator rescheduling technique for congestion management in power system with wind farms. The proposed technique is formulated to minimize the rescheduling cost of conventional and wind generators to alleviate congestion subject to operational line overloading. The generator rescheduling method has been used with incorporation of wind farms in the power system. The locations of wind farms are selected based upon power transfer distribution factor (PTDF). Because all generators in the system do not need to participate in congestion management, the rescheduling has been done by generator selection based on the proposed generator sensitivity factor (GSF). The selected generators have been rescheduled using linear programming(LP) optimization techniques to alleviate transmission congestion. The effectiveness of the proposed methodology has been analyzed on IEEE 14-bus systems.