Probabilistic optimal coordinated planning of molten carbonate fuel cell-CHP and renewable energy sources in microgrids considering hydrogen storage with point estimate method

• Published in: Energy conversion and management Vol. 206; p. 112495
• Main Authors: Bornapour, Mosayeb, Hemmati, Reza, Pourbehzadi, Motahareh, Dastranj, Aliakbar, Niknam, Taher
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 15.02.2020; Elsevier Science Ltd
• Subjects: algorithms; Alternative energy sources; carbonates; Cogeneration; Combined Heat and Power (CHP); Distributed generation; electricity costs; Electricity pricing; Energy resources; Energy storage; Evolutionary algorithms; Evolutionary computation; fuels; heat; hydrogen; Hydrogen storage; Irradiation; Irregular electrical power market; Microgrid (MG); Mixed integer; Molten carbonate fuel cells; Molten Carbonate Fuel Cells (MCFC); Nonlinear programming; operating costs; Optimization; Parameter uncertainty; Photovoltaic cells; Photovoltaics; planning; Probability theory; Radiation; Renewable Energy Source (RES); Renewable energy sources; Renewable resources; Schedules; solar energy; Stochastic models; stochastic processes; Strategy of storing hydrogen; Thermal analysis; Turbines; Wind power; Wind speed; Wind turbines; Microgrid (MG); Combined Heat and Power (CHP); Molten Carbonate Fuel Cells (MCFC); Irregular electrical power market; Strategy of storing hydrogen; Renewable Energy Source (RES)
• ISSN: 0196-8904; 1879-2227
• DOI: 10.1016/j.enconman.2020.112495

[Display omitted] •Stochastic model is proposed for coordinated scheduling of renewable energy sources.•The effect of combined heat and power is considered.•Hydrogen storage is considered for fuel cells.•Proposing a modified Evolution methodology to solve the problem.•Point estimate method is used for considering uncertainties. The ever-growing augmentation of Renewable Energy Sources (RES) and Combined Heat and Power (CHP) units in microgrids (MG) exacerbates schedule management requirements in such systems. In this paper, a modified hybrid Bird Mating Optimization Differential Evolution (BMO-DE) algorithm is developed to address the mixed integer nonlinear programming problem of MG units’ probabilistic optimal planning. The proposed MG structure is consisted of MCFC-CHP, Wind Turbines (WT) and Photovoltaics (PV). The presented stochastic model schedules MG units coordinately, while the strategy of MCFC-CHP hydrogen storage is taken into account. The proposed solution models the uncertain parameters of electricity price, wind speed and sun irradiation using the 2m + 1 Point Estimate Method (PEM). The modeling of uncertain parameters results in more accurate planning and operation of the entire system. The proposed solution is applied on a 33-bus distribution network. In this manner, the total power loss decreased to 358.5 kW and the total operation cost is 3.1349 × 104$, which shows 18% decrease compared to MINLP method and 25% decrease compared to GA-PSCAD method of the total operation cost using the BMO-DE method. The results also justified the usage of CHPs while supplying thermal loads due to increased efficiency and profit.