University of Tabriz Tabriz Journal of Electrical Engineering 2008-7799 49 3 2019 12 01 Bidding Strategy of Micro-Grids in Day-Ahead Energy and Reserve Markets under Generation and Load Uncertainties Bidding Strategy of Micro-Grids in Day-Ahead Energy and Reserve Markets under Generation and Load Uncertainties 1223 1234 9598 FA P. Fazlalipour Department of Electrical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran B. Mohammadi-ivatloo Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran M. Ehsan Faculty of Electrical Engineering, Sharif University of Technology, Tehran, Iran Journal Article 2017 11 07 Micro-grids are integrated electrical systems, which can include dispatchable and non-dispatchable resources, consumption and battery storages. However, optimal management of these integrated systems requires stochastic programming approaches to consider the random nature of renewable generation and consumption. In this paper, a comprehensive bidding strategy model has been provided for renewable micro-grids to participate in the day-ahead energy and reserve markets. The uncertainties in renewable generation and load consumption have been integrated to the problem by the use of stochastic programming approach. Furthermore, the Latin Hypercube Sampling and Fast Backward/forward scenario reduction approaches have been utilized to generate and reduce the scenarios. A large size mixed integer non-liner problem with a lot of binary variables is the outcome of the optimization problem, which is maximized via combination of AlphaECP and Lindoglobal solvers in GAMS to guarantee the global solutions. The “value of the stochastic solution” shows the efficiency of the stochastic programming approach. Micro-grids are integrated electrical systems, which can include dispatchable and non-dispatchable resources, consumption and battery storages. However, optimal management of these integrated systems requires stochastic programming approaches to consider the random nature of renewable generation and consumption. In this paper, a comprehensive bidding strategy model has been provided for renewable micro-grids to participate in the day-ahead energy and reserve markets. The uncertainties in renewable generation and load consumption have been integrated to the problem by the use of stochastic programming approach. Furthermore, the Latin Hypercube Sampling and Fast Backward/forward scenario reduction approaches have been utilized to generate and reduce the scenarios. A large size mixed integer non-liner problem with a lot of binary variables is the outcome of the optimization problem, which is maximized via combination of AlphaECP and Lindoglobal solvers in GAMS to guarantee the global solutions. The “value of the stochastic solution” shows the efficiency of the stochastic programming approach. https://tjee.tabrizu.ac.ir/article_9598_b81feadd4e7258b51c4b500b4188fa62.pdf