Stochastic energy management for a renewable energy based microgrid considering battery, hydrogen storage, and demand response

This paper presents a stochastic management algorithm to address the optimal operation of smart microgrids (MGs) in the high presence of stochastic renewable energy resources. The proposed management algorithm aims to find a day-ahead optimal operation of the renewable energy resources, including wi...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Sustainable Energy, Grids and Networks Ročník 30; s. 100652
Hlavní autori: Eghbali, Nazanin, Hakimi, Seyed Mehdi, Hasankhani, Arezoo, Derakhshan, Ghasem, Abdi, Babak
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier Ltd 01.06.2022
Predmet:
Battery
Demand response
Hydrogen storage
Mixed integer linear programming
Smart microgrid
Stochastic energy management
Stochastic programming
Hydrogen storage
Battery
Stochastic energy management
Demand response
Mixed integer linear programming
Smart microgrid
Stochastic programming
ISSN:2352-4677, 2352-4677
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:This paper presents a stochastic management algorithm to address the optimal operation of smart microgrids (MGs) in the high presence of stochastic renewable energy resources. The proposed management algorithm aims to find a day-ahead optimal operation of the renewable energy resources, including wind turbine, photovoltaic (PV) unit, Fuel Cell (FC), electrolyzer, microturbine, and energy storage that simultaneously considers the participation of the smart homes in demand response programs. The presented stochastic management is formulated as a mixed-integer linear programming (MILP) problem solved through a stochastic programming approach. Two different energy storage devices, i.e., battery and hydrogen storage tank, are modeled, and their operations are compared. Various uncertainties (e.g., wind speed, solar irradiance, demand, and electricity price) are modeled, where the scenario-based approach is applied to find a finite number of scenarios. The efficiency of the presented algorithm is verified in four scenarios to evaluate the effect of hydrogen storage and demand response program. Finally, it is shown that applying both hydrogen storage and demand response program can benefit the MG from the economic perspective and results in a significant reduction in the total cost.
ISSN:2352-4677
2352-4677
DOI:10.1016/j.segan.2022.100652