Optimization Model Of Urban Energy Under Uncertainty

Energy is essential to the development, and the operation of a city. The sufficient and sustainable energy supply play a decisive role in developing socio-economy, maintaining people's living standards and improving ecological environment. In this study, an inexact optimization model for the planning of expansion of electricity-generation-facility was developed. Interval-parameter linear programming, fuzzy-robust programming, random boundary interval programming and fuzzy-robust random boundary interval programming and mixed-integer programming techniques have been integrated with an electricity systems planning model. The developed model can thus handle not only the uncertainties in objective function and constraints, but also the dynamics of capacity expansion of power generation. The interval solutions can be obtained and decision alternatives can be generated by adjusting decision variables within their solution intervals. The developed model was then applied to Beijing, China. The results of case study suggest that power supply based on a mixed electricity supply schemes (consisting of coal-fired, nature-gas fired electricity, renewable energy and alternative electricity generation technologies), would meet the electricity demand for the economic and social development in Beijing.