Mun-Kyeom Kim

A Reliability-Centered Approach to an Optimal Maintenance Strategy in Transmission Systems Using a Genetic Algorithm

Electric power transmission utilities try to maximize profit by reducing electricity supply costs and operation costs while maintaining their reliability. Developing maintenance strategies is one of the effective ways to achieve these profitable goals. The reliability-centered maintenance approach is a key method in providing optimal maintenance strategies. It considers the tradeoffs between the upfront maintenance costs and the potential costs of reliability losses. Since a transmission system is a group of different kinds of equipment and the reliability of the electric facilities varies with time, an equipment state model using a modified semi-Markov chain is proposed. In addition, a genetic algorithm is used to find the optimal maintenance strategies from a large class of possible maintenance scenarios. These optimal maintenance strategies have been tested on an IEEE 9-bus system and an IEEE 118-bus system; the results show that the proposed method minimizes the total expected costs.

Integrated Optimization of Two Design Techniques for Cogging Torque Reduction Combined With Analytical Method by a Simple Gradient Descent Method

This paper presents an integrated optimization process to minimize cogging torque in permanent-magnet (PM) machines by a simple Gradient Descent method. The presented optimization method can be easily achieved in machine design. The design techniques of nonuniformly distributed magnets and teeth are presented to illustrate the optimization process. First, with the assistance of an analytical model deduced, the initial solution and feasible domain of the optimization can be easily identified. Then a simple Gradient Descent method is combined with finite element analysis to perform the optimization within the identified feasible domain. Four representative PM machines-including surface-mounted permanent-magnet synchronous machine (SPMSM), brushless DC machine (BLDC), and interior permanent-magnet synchronous machine (IPMSM)-are designed and optimized by the presented method, respectively. The results verify that the presented optimization process can greatly reduce the cogging torque in PM machines. In addition, it is easily achieved and very time-saving. At last, the influence of the nonuniformly distributed magnets method on load torque is examined.

Impacts of Wind Power Integration on Generation Dispatch in Power Systems

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.

Application of Particle Swarm Optimization to the Reliability Centered Maintenance Method for Transmission Systems

Electric power transmission utilities make an effort to maximize profit by reducing their electricity supply and operation costs while maintaining their reliability. The development of maintenance strategies for aged components is one of the more effective ways to achieve this goal. The reliability centered approach is a key method in providing optimal maintenance strategies. It considers the tradeoffs between the upfront maintenance costs and the potential costs incurred by reliability losses. This paper discusses the application of the Particle Swarm Optimization (PSO) technique used to find the optimal maintenance strategy for a transmission component in order to achieve the minimum total expected cost composed of Generation Cost (GC), Maintenance Cost (MC), Repair Cost (RC) and Outage Cost (OC). Three components of a transmission system are considered: overhead lines, underground cables and insulators are considered. In regards to aged and aging component, a component state model that uses a modified Markov chain is proposed. A simulation has been performed on an IEEE 9-bus system. The results from this simulation are quite encouraging, and then the proposed approach will be useful in practical maintenance scheduling.

Determination of Available Transfer Capability Using Continuation Power Flow with Fuzzy Set Theory

In trying to determine available transfer capability (ATC) considering uncertainty, this paper demonstrates an algorithm of fuzzy set theory to continuation power flow (CPF). For the calculation ATC using the fuzzy continuation power flow (FCPF), this paper assumes that the uncertainties of involved in ATC calculation can be estimated or measured. Regarding the major uncertain factors affecting the ATC value, a fuzzy model is formulated in which the availability of uncertain parameters is considered as fuzzy variables following a possibility distribution. The motivation in this paper is to develop a FCPF algorithm that can handle simultaneous uncertainties in the load parameters and bus injections. We demonstrated the efficiency of the proposed method by comparison with values obtained from conventional continuation power flow (CPF) and the probabilistic power flow (PPF) for the IEEE-24 bus reliability test system (RTS).

Security Cost Analysis with Linear Ramp Model using Contingency Constrained Optimal Power Flow

This paper proposes a novel technique for calculating the security costs that properly includes ramping constraints in the operation of a deregulated power system. The ramping process is modeled by a piecewise linear function with certain assumptions. During this process, a ramping cost is incurred if the permissible limits are exceeded. The optimal production costs of the power producers are calculated with the ramping cost included, considering a time horizon with N-1 contingency cases using contingency constrained optimal power flow (CCOPF), which is solved by the primal-dual interior point method (PDIPM). A contingency analysis is also performed taking into account the severity index of transmission line outages and its sensitivity analysis. The results from an illustrative case study based on the IEEE 30-bus system are analyzed. One attractive feature of the proposed approach is that an optimal solution is more realistic than the conventional approach because it satisfies physical constraints, such as the ramping constraint.

Distributed power flow and economic operation in a South Korea distribution system

In this paper, we describe the development of a distributed power flow and the economic operation for a power distribution system undergoing conversion to a strategic business unit (SBU) operation for the division of the power distribution business sectors in South Korea. The SBU is a self-regulated entity with independent responsibility for operating a local system within its budget. The financial results appear through independent, available financial sheets designed to motivate management innovation and cost saving curtailment. In the SBU, the distributed power flow algorithm in a power distribution system should be changed as the system is divided so that each sector then needs its own operational system. In this study, we developed a distributed power flow algorithm and the economic operation for a power distribution system undergoing SBUs after the division into power distribution business sectors in South Korea.

A New Approach to Short-term Price Forecast Strategy with an Artificial Neural Network Approach: Application to the Nord Pool

In new deregulated electricity market, short-term price forecasting is key information for all market players. A better forecast of market-clearing price (MCP) helps market participants to strategically set up their bidding strategies for energy markets in the short-term. This paper presents a new prediction strategy to improve the need for more accurate short-term price forecasting tool at spot market using an artificial neural networks (ANNs). To build the forecasting ANN model, a three- layered feedforward neural network trained by the improved Levenberg-marquardt (LM) algorithm is used to forecast the locational marginal prices (LMPs). To accurately predict LMPs, actual power generation and load are considered as the input sets, and then the difference is used to predict price differences in the spot market. The proposed ANN model generalizes the relationship between the LMP in each area and the unconstrained MCP during the same period of time. The LMP calculation is iterated so that the capacity between the areas is maximized and the mechanism itself helps to relieve grid congestion. The addition of flow between the areas gives the LMPs a new equilibrium point, which is balanced when taking the transfer capacity into account, LMP forecasting is then possible. The proposed forecasting strategy is tested on the spot market of the Nord Pool. The validity, the efficiency, and effectiveness of the proposed approach are shown by comparing with time-series models

Maintenance Priority Index of Overhead Transmission Lines for Reliability Centered Approach

Overhead transmission lines are crucial components in power transmission systems. Well- designed maintenance strategy for overhead lines is required for power utilities to minimize operating costs, while improving the reliability of the power system. This paper presents a maintenance priority index (MPI) of overhead lines for a reliability centered approach. Proposed maintenance strategy is composed of a state index and importance indices, taking into account a transmission condition and importance in system reliability, respectively. The state index is used to determine the condition of overhead lines. On the other hand, the proposed importance indices indicate their criticality analysis in transmission system, by using a load effect index (LEI) and failure effect index (FEI). The proposed maintenance method using the MPI has been tested on an IEEE 9-bus system, and a numerical result demonstrates that our strategy is more cost effective than traditional maintenance strategies.

Calculation of Distribution Network Charging for DG Embedded Distribution System

With the advent of smart grid, distribution network charges have been one of keystones of ongoing deregulation and privatization in power industries. This paper proposes a new charging methodology to allocate the existing distribution network cost with an aim of reflecting the true cost and benefit of network customers, especially of distribution generator (DG). The proposed charging methodology separates distribution network costs due to the respective real and reactive power flows. The costs are then allocated to network users according to each charge for the actual line capacity used and available capacity. This distribution network charging model is able to provide the economic signals to reward network users who are contributing to better power factors, while penalizing customers who worsen power factors. The proposed method is shown on IEEE 37 bus system for distribution network, and then the results are validated through the comparison with the MW-Miles and MVA-Miles methods. The charges derived from the proposed method can provide appropriate incentives/penalties to network customers to behave in a manner leading to a better network condition.