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... 00 A Fuzzy Expert System for Evaluation of Demand-Side Management Alternatives SCOTT J. BENSON Lincoln Electric System 1040 “O” St. Lincoln, NE 68501, USA sbenson@les.lincoln.ne.us SOHRAB ASGARPOOR Department ...
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ABSTRACT This paper introduces and evaluates a new index called “Expected Cost Penalty due to Deviation from the Economic Dispatch” (EPDED) for interconnected power systems. This index represents the cost penalties associated with... more
ABSTRACT This paper introduces and evaluates a new index called “Expected Cost Penalty due to Deviation from the Economic Dispatch” (EPDED) for interconnected power systems. This index represents the cost penalties associated with uncertainties such as random failure of generating units, load growth, and fuel costs in interconnected power systems. The significance of this index is that it represents common events such as operating problems that can be observed over short periods (e.g., one or two years) rather than the rare events such as load curtailment which is currently used for reliability evaluation of power systems. This paper presents two techniques to evaluate this index. Monte-Carlo simulation and a tree structured state enumeration. System studies are performed to determine the variation of expected cost penalty with respect to changes in load values and probability of failure of generating units
Research Interests: Economics, Monte Carlo Simulation, Power System, Probability, Monte Carlo Methods, and 15 moreFailure Analysis, Power Generation, Power Transmission, Costing, Index, Mathematical Model, Demand, Economic Dispatch, Cost Analysis, Electric energy, Indexation, Cost Function, Electrical And Electronic Engineering, Fossil Fuel, and Electric Power Generation
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Detailed maintenance modeling is indispensable for utilities to determine optimum maintenance policy. Traditional reliability studies assume that transition rates or probabilities in Markov models are accurate. However, in reality,... more
Detailed maintenance modeling is indispensable for utilities to determine optimum maintenance policy. Traditional reliability studies assume that transition rates or probabilities in Markov models are accurate. However, in reality, reliability data is either insufficient or mixed with uncertainty. This paper intends to utilize fuzzy set theory to represent parameters for Markov and semi-Markov processes. Previous single equipment maintenance models are extended with fuzzy transition parameters in Markov processes. The sensitivity analysis is performed to determine how fuzzy membership functions and boundary ranges impact equipment availability. Results are also compared with tradition non-fuzzy method. This work is valuable for utilities to develop maintenance models with incomplete and uncertain reliability data.
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ABSTRACT Aging infrastructures have become a challenge for many utilities in North America, which increases the complexity of operation, maintenance and replacement decisions. For managing asset fleets with aging equipment, utilities have... more
ABSTRACT Aging infrastructures have become a challenge for many utilities in North America, which increases the complexity of operation, maintenance and replacement decisions. For managing asset fleets with aging equipment, utilities have developed many risk-based approaches to identify high-risk assets, in order to ensure cost-effective maintenance decisions under budget constraints. This paper presents a multiperspective risk analysis approach to assist asset owners in identifying high risk assets within asset fleets. Comprehensive evaluation of equipment performance, operation and maintenance (O&M) cost and equipment criticality risk indicators are presented. Case studies of risk analysis for circuit breakers of two substations are presented. The approach developed enhances the traditional risk diagram with multiperspective risk indicators that can be integrated into utility asset management practices.
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ABSTRACT The integration of increasingly available renewable energy sources, such as wind energy, into the power grid will have the potential to reduce dependence on fossil fuels and minimize greenhouse gas emission. However, due to the... more
ABSTRACT The integration of increasingly available renewable energy sources, such as wind energy, into the power grid will have the potential to reduce dependence on fossil fuels and minimize greenhouse gas emission. However, due to the stochastic nature of renewable generation, balancing of generation and load becomes difficult. Energy storage is expected to play a major role in promoting the development of renewable energy by intermittent power source balancing, storing surplus generation, and providing electricity during high demands. One of the various emerging energy storage technologies is Compressed Air Energy Storage (CAES). In this paper, we model a wind generation-CAES system which can generate, store, and sell electricity to the grid. In addition, two optimization methodologies based on particle swarm optimization (PSO) are used to optimize the short-term operation and long-term planning of the wind generation-CAES system. The goal is to determine the optimum capacities of these resources as well as the optimum day-to-day operation strategy in order to maximize profit. The variables considered in this study include electricity market price, wind speed, gas price, etc., from a local electric utility. A number of sensitivity analyses are performed to evaluate the profitability of the wind generation-CAES system and the impact of different factors on the results.
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Research Interests: Government, Wind Energy, Renewable energy resources, Induction Generators, Distributed System, and 13 moreStability, renewable Energy sources, Wind Power, Uncertainty, Fossil Fuels, Wind Turbines, Steady state, Carbon Emissions, Government Policy, Voltage, Indexation, Power flow, and Renewable Energy Source
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ABSTRACT An analytical method for determining the optimum maintenance of substations based on stochastic modeling is presented in this paper. The analytical method includes reliability modeling of operation states, and different types of... more
ABSTRACT An analytical method for determining the optimum maintenance of substations based on stochastic modeling is presented in this paper. The analytical method includes reliability modeling of operation states, and different types of maintenance for individual components, which provides more detail information comparing with traditional modeling. Importance analysis is performed to quantify the reliability contribution of each individual component towards a specific load point, which also gives the priority of a component's maintenance significance. Moreover, economical analysis is also included in this paper, which calculates the expected benefit that can be achieved for a load point with corresponding maintenance schedule. An application of using the proposed method for evaluating substation maintenance schedule is given. The optimal maintenance schedule and the corresponding expected reliability and benefit are presented in this paper.
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Today's electric utilities are confronted with a myriad of challenges that include increased numbers of aging equipment, high operation and maintenance costs, and coping with growing uncertainties. For management of critical utility... more
Today's electric utilities are confronted with a myriad of challenges that include increased numbers of aging equipment, high operation and maintenance costs, and coping with growing uncertainties. For management of critical utility assets and maintenance planning, all these issues should be addressed to improve equipment reliability under limited budget constraints. This paper proposes an algorithm that enables maintenance impact analysis
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ABSTRACT A method is presented to determine the amount of preventive maintenance to be performed on equipment in order to maximize availability. The method uses a continuous-time semi-Markov process that assumes equipment can fail due to... more
ABSTRACT A method is presented to determine the amount of preventive maintenance to be performed on equipment in order to maximize availability. The method uses a continuous-time semi-Markov process that assumes equipment can fail due to both deterioration and random occurrences. Preventive maintenance can be performed from working state to prevent deterioration failure. An example is used to demonstrate the method using MATLAB and Maple software. Additional flexibility in equipment modeling using semi-Markov processes is described.
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1. ABSTRACT Today, preserving and/or enhancing system reliability and reducing operations and maintenance (O&M) costs are top priorities for electric utilities. As system equipment continue to age and gradually deteriorate, the... more
1. ABSTRACT Today, preserving and/or enhancing system reliability and reducing operations and maintenance (O&M) costs are top priorities for electric utilities. As system equipment continue to age and gradually deteriorate, the probability of service interruption ...
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Optimal levels of preventive maintenance performed on any system ensures cost-effective and reliable operation of the system. In this paper a component with deterioration and random failure is modeled using Markov processes while... more
Optimal levels of preventive maintenance performed on any system ensures cost-effective and reliable operation of the system. In this paper a component with deterioration and random failure is modeled using Markov processes while incorporating the concept of minor and major preventive maintenance. The optimal mean times to preventive maintenance (both minor and major) of the component is determined by maximizing its availability with respect to mean time to preventive maintenance. Mathematical optimization programs Maple 7 and Lingo 7 are used to find the optimal solution, which is illustrated using a numerical example. Further, an optimal maintenance policy is obtained using Markov Decision Processes (MDPs). Linear Programming (LP) is utilized to implement the MDP problem.
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Page 1. 1654 IEEE Transactions on Power Systems, Vol. 12, No. 4, November 1997 SECOND BIBLIOGRAPHY ON TRANSMISSION ACCESS ISSUES by the Bibliography Task Force on Engineering Issues Associated with Transmission Access ...
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ABSTRACT An algorithm for integrating uncertain parameters in Markov analysis is proposed. Fuzzy Markov models for aging equipment and substations are developed in which the transition rates/probabilities with uncertainty are represented... more
ABSTRACT An algorithm for integrating uncertain parameters in Markov analysis is proposed. Fuzzy Markov models for aging equipment and substations are developed in which the transition rates/probabilities with uncertainty are represented by fuzzy membership functions. An extension principle and nonlinear optimization-based approaches are utilized for calculation of fuzzy reliability indices. Sensitivity studies for analyzing the impact of various fuzzy membership functions on reliability indices are provided, and the characteristics of the results are discussed. The fuzzy Markov model presented in this paper has valuable application in extending current Markov analysis with the ability to incorporate uncertainties associated with data collected on maintenance activities, etc.
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ABSTRACT The smart grid of the future may equip customers with distributed generation and storage systems that can change their overall demand behavior. Indeed, the smart grid's infrastructure provides new opportunities for the... more
ABSTRACT The smart grid of the future may equip customers with distributed generation and storage systems that can change their overall demand behavior. Indeed, the smart grid's infrastructure provides new opportunities for the grid and its customers to exchange information regarding real-time electricity rates and demand profiles. Here we report on innovative agent-based modeling and simulation of a smart grid where active customers are modeled as self-interested, autonomous agents with their own specific load profiles and generation/storage capacities. They may choose to use locally generated power, charge/discharge their batteries, and manipulate their loads. A unique scenario for the customers analyzed for this paper is one in which customers are allowed to trade electricity within their neighborhood in order to minimize their electricity costs. Meanwhile, the grid prefers an overall uniform demand from all customers. To achieve this, we propose an effective demand flattening management scheme for the customers. A model of the active customers within the smart grid environment is used to determine the impact of the neighborhood power transactions, demand diversity, and load shifting on the customers and the utility. A number of case studies and sensitivity analyses have determined how and to what extent these parameters affect customer electricity costs and power system metrics.
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A method is presented to solve for the optimum maintenance policy of repairable power equipment. The approach uses a continuous-time semi-Markov process (SMP) to first find the optimal maintenance rate for maximum availability of the... more
A method is presented to solve for the optimum maintenance policy of repairable power equipment. The approach uses a continuous-time semi-Markov process (SMP) to first find the optimal maintenance rate for maximum availability of the equipment. Then a semi-Markov decision process (SMDP) is utilized to determine whether maintenance should be performed in each deterioration state. The approach uses a model
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This paper presents a method to find the optimum maintenance policy for a component. Random failures and failures due to deterioration are considered. Using Markov processes, the state probabilities are calculated and the optimal value of... more
This paper presents a method to find the optimum maintenance policy for a component. Random failures and failures due to deterioration are considered. Using Markov processes, the state probabilities are calculated and the optimal value of the mean time to preventive maintenance is determined by maximizing the availability of single component with respect to mean time to minimal preventive maintenance.
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ABSTRACT A new method for calculating generation system reliability using fuzzy mathematics is presented here. In reliability evaluation of power systems, a membership function can be provided to represent the uncertainties and... more
ABSTRACT A new method for calculating generation system reliability using fuzzy mathematics is presented here. In reliability evaluation of power systems, a membership function can be provided to represent the uncertainties and inaccuracies in the failure rates and repair rates of generating units. The basic unit addition recursive algorithm is modified to represent these uncertainties along with uncertainties in system load as fuzzy data. Loads are represented as clusters to overcome the difficulty of large computational time requirements. A computer program has been developed in C language to include all aforementioned factors. The program was tested with the IEEE Reliability Test System on an IBM RS/6000 workstation. Several cases were analyzed and results are presented. The algorithm developed computes reliability indices such as loss of load probability (LOLP) and the expected unserved energy (EWE) which are viewed as possibility distributions.
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This paper presents an analytical technique based on the device of stages for distribution system reliability evaluation. This technique models the aging of equipment in evaluating the reliability indices. The three main indices evaluated... more
This paper presents an analytical technique based on the device of stages for distribution system reliability evaluation. This technique models the aging of equipment in evaluating the reliability indices. The three main indices evaluated are failure rate, outage time, and average annual outage time for each load point. An additional set of indices (performance indices) is also calculated using these
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ABSTRACT As the power system moves toward more efficient operation, one of the main challenges for asset managers is to determine the optimum maintenance strategy for deteriorating equipment such as wind turbines. This problem can be... more
ABSTRACT As the power system moves toward more efficient operation, one of the main challenges for asset managers is to determine the optimum maintenance strategy for deteriorating equipment such as wind turbines. This problem can be addressed using a variety of optimization methods including analytical approaches which globally find the best strategy. However, since there are numerous factors (e.g., resource availability, weather conditions, etc.) affecting the operation and maintenance of equipment, there is not a unique solution for all of the possible situations. While it will be complicated to include these scenarios in an analytical model, a simulation model is more flexible and can easily handle these conditions. In order to benefit from the advantages of both analytical and simulation models, we propose a hybrid analytical-simulation approach toward solving a maintenance optimization problem with actual system limitations. In the first step of this approach, the optimum maintenance policy for a wind turbine is obtained using semi-Markov decision processes. Then, this model is built and solved with a Monte Carlo simulation, and the results are compared for justification of the simulation model. In the second step, the effects of maintenance and repair constraints on system availability and costs are studied using the simulation model developed. The model developed can assist the asset managers in including their own restrictions through sensitivity analysis and performing a cost/benefit analysis to determine, for example, how many technicians are required for a fleet of equipment, such as a wind farm. The effectiveness of this approach is demonstrated by the results from the case study of wind turbines where a number of maintenance and repair restrictions are considered. (c) 2013 Elsevier B.V. All rights reserved.