Applying fuzzy mathematics to the evaluation of avoided cost for a load management program

Chen, C.S.; Sheen, J.N.

doi:10.1016/0378-7796(93)90025-a

Cited by 6 publications

(2 citation statements)

References 10 publications

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“…(8) represents the AC at t ¼ 0, so this AC should be fully allocated among the customers who participate in the program at the time of its implementation. Although the AGCC indicates the AC in terms of its present value, it can be converted to an annual incentive, AI, by means of an annuity method [3,22], i.e.…”

Section: Avoided Generation Capacity Cost (Agcc)mentioning

confidence: 99%

Incentive pricing and economic profitability of load management program

Sheen

2006

Energy

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Section: Avoided Generation Capacity Cost (Agcc)mentioning

confidence: 99%

Incentive pricing and economic profitability of load management program

Sheen

2006

Energy

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“…Based on these method, there were a large number of applications to environmental and energy management and planning [198][199][200][201][202][203][204][205][206]. For example, Chen and Sheen introduced a generalized fuzzy mathematical model for energy-load management [207]. Kagan and Adams addressed the problems of electrical power distribution systems by planning under uncertainty through the formulation of a fuzzy mathematical model [208].…”

Section: Fuzzy Mathematical Programmingmentioning

confidence: 99%

A Review on Optimization Modeling of Energy Systems Planning and GHG Emission Mitigation under Uncertainty

et al. 2011

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Abstract:Energy is crucial in supporting people's daily lives and the continual quest for human development. Due to the associated complexities and uncertainties, decision makers and planners are facing increased pressure to respond more effectively to a number of energy-related issues and conflicts, as well as GHG emission mitigation within the multiple scales of energy management systems (EMSs). This quandary requires a focused effort to resolve a wide range of issues related to EMSs, as well as the associated economic and environmental implications. Effective systems analysis approaches under uncertainty to successfully address interactions, complexities, uncertainties, and changing conditions associated with EMSs is desired, which require a systematic investigation of the current studies on energy systems. Systems analysis and optimization modeling for low-carbon energy systems planning with the consideration of GHG emission reduction under uncertainty is thus comprehensively reviewed in this paper. A number of related methodologies and applications related to: (a) optimization modeling of GHG emission mitigation; (b) optimization modeling of energy systems planning under uncertainty; and (c) model-based decision support tools are examined. Perspectives of effective management schemes are investigated, demonstrating many demanding areas for enhanced research efforts, which include issues of data availability and reliability, concerns in OPEN ACCESSEnergies 2011, 4 1625 uncertainty, necessity of post-modeling analysis, and usefulness of development of simulation techniques.

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Fuzzy Regression Systems and Fuzzy Linear Models

Soliman

Al-Kandari

2010

Electrical Load Forecasting

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Applying fuzzy mathematics to the evaluation of avoided cost for a load management program

Cited by 6 publications

References 10 publications

Incentive pricing and economic profitability of load management program

Incentive pricing and economic profitability of load management program

A Review on Optimization Modeling of Energy Systems Planning and GHG Emission Mitigation under Uncertainty

Fuzzy Regression Systems and Fuzzy Linear Models

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