Impacts of optimal energy storage deployment and network reconfiguration on renewable integration level in distribution systems

•A dynamic and multi-objective stochastic mixed integer linear programming model is developed.•A new mechanism to quantify the impacts of network flexibility and ESS deployments on RES integration is presented.•Optimal integration of ESSs dramatically increases the level and the optimal exploitation...

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Vydané v:Applied energy Ročník 185; číslo P1; s. 44 - 55
Hlavní autori: Santos, Sérgio F., Fitiwi, Desta Z., Cruz, Marco R.M., Cabrita, Carlos M.P., Catalão, João P.S.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: United Kingdom Elsevier Ltd 01.01.2017
Elsevier
Predmet:
carbon footprint
case studies
Distributed generation
electricity
energy
Energy storage
fossil fuels
linear programming
Network reinforcement
Network switching
Renewable energy sources
Stochastic mixed integer linear programming
Renewable energy sources
Network reinforcement
Distributed generation
Network switching
Energy storage
Stochastic mixed integer linear programming
ISSN:0306-2619, 1872-9118
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Shrnutí:•A dynamic and multi-objective stochastic mixed integer linear programming model is developed.•A new mechanism to quantify the impacts of network flexibility and ESS deployments on RES integration is presented.•Optimal integration of ESSs dramatically increases the level and the optimal exploitation of renewable DGs.•As high as 90% of RES integration level may be possible in distribution network systems.•Joint DG and ESS installations along with optimal network reconfiguration greatly contribute to voltage stability. Nowadays, there is a wide consensus about integrating more renewable energy sources-RESs to solve a multitude of global concerns such as meeting an increasing demand for electricity, reducing energy security and heavy dependence on fossil fuels for energy production, and reducing the overall carbon footprint of power production. Framed in this context, the coordination of RES integration with energy storage systems (ESSs), along with the network’s switching capability and/or reinforcement, is expected to significantly improve system flexibility, thereby increasing the capability of the system in accommodating large-scale RES power. Hence, this paper presents a novel mechanism to quantify the impacts of network switching and/or reinforcement as well as deployment of ESSs on the level of renewable power integrated in the system. To carry out this analysis, a dynamic and multi-objective stochastic mixed integer linear programming (S-MILP) model is developed, which jointly takes the optimal deployment of RES-based DGs and ESSs into account in coordination with distribution network reinforcement and/or reconfiguration. The IEEE 119-bus test system is used as a case study. Numerical results clearly show the capability of ESS deployment in dramatically increasing the level of renewable DGs integrated in the system. Although case-dependent, the impact of network reconfiguration on RES power integration is not significant.
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USDOE Office of Nuclear Energy (NE), Nuclear Fuel Cycle and Supply Chain
ISSN:0306-2619
1872-9118
DOI:10.1016/j.apenergy.2016.10.053