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An efficient scenario-based stochastic programming method for optimal scheduling of CHP-PEMFC, WT, PV and hydrogen storage units in micro grids

Bornapour, Mosayeb, Hooshmand, Rahmat-Allah, Parastegari, Moein
Renewable energy 2019 v.130 pp. 1049-1066
algorithms, fuel cells, heat, hydrogen, income, market prices, renewable energy sources, solar radiation, stochastic processes, system optimization, uncertainty, wind speed
Nowadays, renewable energy resources are increasingly used to supply electrical loads in micro grids, which these units should be scheduled coordinately. In this paper a stochastic model for coordinated scheduling of renewable and thermal units is proposed. Understudied units consists of fuel cell units with proton exchange membrane which generate heat and power simultaneously (PEMFC-CHP), wind and photovoltaic units. Moreover, the strategy of storing hydrogen is also considered for PEMFC-CHP units. Uncertainties of wind speed, solar radiation and market prices are considered using scenario based method. In the proposed stochastic programming problem, the strategy of storing hydrogen is considered by a mixed integer nonlinear programming (MINP) problem. The uncertainties of parameters convert the MINP problem to a stochastic MINP one. Moreover, optimal coordinated scheduling of renewable energy resources and thermal units in micro-grids improve the value of the objective function. To solve this problem, Modified Teaching-Learning-Based Optimization (MTLBO) algorithm is used and its performance is evaluated on a modified 33 bus distribution network. Simulation results represent that by using MTLBO method, the revenue increases more than 5 percentages in comparison with other optimization methods. In addition, considering CHP increases total profit of the system more than 15%.