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Development of Energy Supply Model under Uncertainty

Mirkhani, Shahin | 2015

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  1. Type of Document: Ph.D. Dissertation
  2. Language: Farsi
  3. Document No: 48212 (08)
  4. University: Sharif University of Technology
  5. Department: Energy Conversion
  6. Advisor(s): Saboohi, Yadollah
  7. Abstract:
  8. Energy supply system model (ESM) is used as an analytical tool for policy making and optimizing the allocation of energy resources, selecting the best combination of energy carriers and technologies, and also determining required investments for development and operation of energy supply system, in order to meet the useful demand of energy. Although the modeled process in this Bottom-Up mathematical tool has deterministic characteristics, but evolution of exogenous parameters for energy sector have uncertainty which may impact on results of energy model. Limitations of applied methods for application of deterministic energy models under uncertain conditions result that all uncertain possibilities are not encompassed together, the imposed risks by uncertainties are not considered and the results may not be robust. In the present research work, by utilizing the stochastic processes, a new method has been developed that is based on discretized probabilistic network, to model the uncertainty as an integrated part of the energy model ESM. Since uncertainties in the energy model are realized sequentially in time, in second step, multistage stochastic version of energy supply optimization model has been developed and validated. Application of developed model and comparison of its results with those of deterministic model demonstrate the performance of stochastic model for optimal decision making and more reliable perspective of energy supply system. The results reveal optimal timing for investment and capacity expansion of the system. This stochastic model is Risk neutral since it considers any portfolio that only minimizes the expected cost of the system and ignores risks which are imposed by uncertainties. Finally, in order to capture the risk of variation in diverse uncertain parameters, risk averse stochastic energy model has been developed based on a new approach to consider coherent risk functions in objective function of energy model. Based on axiomatic characteristics, coherent risk functions guarantee the solvability of the problem, while minimizing the risks. Application of risk averse energy model for a real case study, and comparison of its results with those of risk neutral model show diversification in portfolio of energy carriers and technologies. Sensitivity analysis with respect to degree of risk aversion results in change of robustness in results and the quality for security of energy supply
  9. Keywords:
  10. Stochastic Programming ; Energy Supply Model ; Stochastic Uncertainty ; Discretized Probabilistic ; Risk Aversion Programming ; Coherent Risk Function ; Robust Decision Making

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