Optimal Energy and Reserve Market Management in Renewable Microgrid-PEVs Parking Lot Systems: V2G, Demand Response and Sustainability Costs

Viviani Caroline Onishi, Carlos Henggeler Antunes and João Pedro Fernandes Trovão
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Viviani Caroline Onishi: Centre for Mechanical Technology and Automation, Department of Mechanical Engineering, Campus de Santiago, University of Aveiro, 3810-193 Aveiro, Portugal
Carlos Henggeler Antunes: INESC Coimbra, University of Coimbra, DEEC, Polo II, 3030-290 Coimbra, Portugal
João Pedro Fernandes Trovão: INESC Coimbra, University of Coimbra, DEEC, Polo II, 3030-290 Coimbra, Portugal

Energies, 2020, vol. 13, issue 8, 1-24

Abstract: Vehicle-to-grid (V2G) technology heralds great promise as a demand-side resource to contribute to more efficient grid management and promote the use of decentralized renewable energy. In this light, we propose a new optimization model for the sustainable energy and reserve market management in renewable-driven microgrid (RMG) plug-in electric vehicles (PEVs) parking lot systems. The RMG is composed of a hybrid photovoltaic/wind/hydrogen energy and storage system, along with local dispatchable generation units and bidirectional grid connection. The RMG is coupled to a smart PEVs parking lot, which is equipped with grid-to-vehicle (G2V) and V2G technologies allowing for not only PEVs aggregation and control but also optimal allocation of energy resources. Time-of-use (TOU) prices are considered in a demand response program (DRP) to enhance both economic and environmental performances by encouraging end-users to shift their energy demands from peak to off-peak time periods. Additionally, the model accounts for an economic incentive to PEVs owners to compensate for battery degradation. The integrated system eco-efficiency is evaluated through the application of the novel life cycle assessment-based Eco-cost indicator. The resulting mixed-integer linear programming model to minimize sustainability costs is implemented in GAMS and solved to global optimality. Different case studies are performed to demonstrate the effectiveness of the proposed modelling approach. Energy analyses results reveal that the optimal G2V-V2G operation, allied to TOU prices in a DRP, and reserve market management can reduce around 42% the energy and environmental costs of the RMG-PEVs parking lot system.

Keywords: optimization; mixed-integer linear programming (MILP); plug-in electric vehicles (PEVs); smart parking lot (SPL); vehicle-to-grid (V2G); renewable energy; hydrogen storage system (HSS); demand response program (DRP); Eco-costs; eco-efficiency (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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