CLOES: cross-layer optimal energy scheduling mechanism in a smart distributed multi-microgrid system
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ORIGINAL RESEARCH
CLOES: cross‑layer optimal energy scheduling mechanism in a smart distributed multi‑microgrid system Nitesh Funde1 · Meera Dhabu1 · Parag Deshpande1 Received: 12 February 2019 / Accepted: 27 January 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Optimal scheduling of multi-microgrids is one of the important tasks in multi-microgrid operations as it is an effective way to enhance operational and economic performance. However, with the presence of varied distributed dispatchable and nondispatchable generation and loads in different microgrids make the optimal scheduling very challenging. This paper presents a cross-layer optimal energy scheduling (CLOES) mechanism in a multimicrogrid system, covering different elements of a community in a smart city such as industry, commercial/office, single residence and multi-dwelling unit with their varied nature of distributed generations and loads. The cross-layer sequential coordinated operations are performed between two layer i.e. lower and upper layer. The lower layer consists of different microgrids, whereas the upper layer comprises distribution system operator. The cross-layer sequential interactions between upper and lower layer lead to an optimal energy scheduling for each microgrid which is essential for the reliability of a multi-microgrid system. The importance of internal and external trading prices is described in a unique way for energy trading in a multi-microgrid system. The simulation result and discussions show the effectiveness of the proposed CLOES in terms of cost reduction in a multi-microgrid system compared to the independent external trading of each individual microgrid with the utility grid. Keywords Optimal energy management · Energy trading · Sequential interactions · Multi-microgrids Abbreviations DG Distributed generation DERs Distributed energy resources PV Photovoltaics EMS Energy management strategy DSO Distribution system operator RES Renewable energy resources CHP Combined heat and power MCCA Microgrid central controller agent ESS Energy storage system EV Electric vehicle SOC State of charge MILP Mixed integer linear programming UG Utility grid * Nitesh Funde [email protected] Meera Dhabu [email protected] Parag Deshpande [email protected] 1
Visvesvaraya National Institute of Technology, Nagpur 440010, India
MG Microgrid MMG Multimicrogrid system Parameters EtCHPmin Min production of CHP at t EtCHPmax Max production of CHP at t CtCHP Energy production cost in CHP Grid buying price 𝜆GBP t Grid selling price 𝜆GSP t Microgrid buying price 𝜆MBP t MSP Microgrid selling price 𝜆t EtPVI PV energy production in industry EtPVSR PV energy production in single-residence EtPVMU PV energy production in multi-dwelling Unit LtI Load demand in industry LtC Load demand in commercial building LtSR Load demand in single-residence LtMU Load demand in multi-dwelling MG 𝜂c , 𝜂d Charging and discharging Efficiency EtESS,max Max energy capacity of ESS EtESS,min Min
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