Renewable energies can play an important role in mitigating the emissions associated with electricity power generation and diversification of the energy supply. The challenge is that renewable resources such as wind and solar have intermittent production patterns and their incorporation into conventional electricity grids will increase the degree of uncertainty. The present research proposes a comprehensive framework in which design and operation of the electricity grid are considered simultaneously and the uncertainties in the wind and solar generation as well as demand are systematically taken into account. The case of retrofitting the current UK electricity grid to include 50% renewable power generation by 2030 was posed as the demonstrating example. The research problem was formulated as a piece-wise linear mixed integer optimization under uncertainty and solved using CPLEX v12.0 in GAMS. The results suggested that it is possible to retrofit the electricity grid using renewable generators while optimizing the overall profitability and ensuring the secure supply of electricity. It was also observed that at the price of higher computational costs, stochastic optimization generates more realistic and robust solutions for the design and operation of the smart electricity grid. KeywordsIntegrated renewable energy systems, wind power, solar energy, stochastic mixed-integer optimization, uncertainty. , , ( ) Power generated by i natural gas power plant in scenario s at node n at time t , , ( ) Power generated by k nuclear power plant in scenario s at node n at time t , ( ) Wind power generated in scenario s at node n at time t , ( ) Solar power generated in scenario s at node n at time t , ( ) Power pumped from storage to node n in scenario s at time t , ( ) Power pumped to storage from node n in scenario s at time t cite this publication at: Mahdi Sharifzadeh, Helena Lubiano-Walochik, Nilay Shah. Integrated renewable electricity generation considering uncertainties: The UK roadmap to 50% power generation from wind and
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