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Network and Market-Aware Bidding to Maximize Local RES Usage and Minimize Cost in Energy Islands with Weak Grid Connections

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  • Konstantinos Smpoukis

    (Department of Electrical and Computer Engineering, Institute of Communication and Computer Systems (ICCS), National Technical University of Athens (NTUA), 15780 Athens, Greece)

  • Konstantinos Steriotis

    (Department of Electrical and Computer Engineering, Institute of Communication and Computer Systems (ICCS), National Technical University of Athens (NTUA), 15780 Athens, Greece)

  • Nikolaos Efthymiopoulos

    (Department of Electrical and Computer Engineering, Institute of Communication and Computer Systems (ICCS), National Technical University of Athens (NTUA), 15780 Athens, Greece)

  • Georgios Tsaousoglou

    (Department of Electrical Engineering, Eindhoven University of Technology, 5612 AP Eindhoven, The Netherlands)

  • Prodromos Makris

    (Department of Electrical and Computer Engineering, Institute of Communication and Computer Systems (ICCS), National Technical University of Athens (NTUA), 15780 Athens, Greece)

  • Emmanouel (Manos) Varvarigos

    (Department of Electrical and Computer Engineering, Institute of Communication and Computer Systems (ICCS), National Technical University of Athens (NTUA), 15780 Athens, Greece)

Abstract

The increasing renewable energy sources RES penetration in today’s energy islands and rural energy communities with weak grid connections is expected to incur severe distribution network stability problems (i.e., congestion, voltage issues). Tackling these problems is even more challenging since RES spillage minimization and energy cost minimization for the local energy community are set as major pre-requisites. In this paper, we consider a Microgrid Operator (MGO) that: (i) gradually decides the optimal mix of its RES and flexibility assets’ (FlexAsset) sizing, siting and operation, (ii) respects the physical distribution network constraints in high RES penetration contexts, and (iii) is able to bid strategically in the existing day-ahead energy market. We model this problem as a Stackelberg game, expressed as a Mathematical Problem with Equilibrium Constraints (MPEC), which is finally transformed into a tractable Mixed Integer Linear Program (MILP). The performance evaluation results show that the MGO can lower its costs when bidding strategically, while the coordinated planning and scheduling of its FlexAssets result in higher RES utilization, as well as distribution network aware and cost-effective RES and FlexAsset operation.

Suggested Citation

  • Konstantinos Smpoukis & Konstantinos Steriotis & Nikolaos Efthymiopoulos & Georgios Tsaousoglou & Prodromos Makris & Emmanouel (Manos) Varvarigos, 2020. "Network and Market-Aware Bidding to Maximize Local RES Usage and Minimize Cost in Energy Islands with Weak Grid Connections," Energies, MDPI, vol. 13(16), pages 1-16, August.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:16:p:4043-:d:394616
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    References listed on IDEAS

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    1. Steven A. Gabriel & Antonio J. Conejo & J. David Fuller & Benjamin F. Hobbs & Carlos Ruiz, 2013. "Complementarity Modeling in Energy Markets," International Series in Operations Research and Management Science, Springer, edition 127, number 978-1-4419-6123-5, March.
    2. Zhao, Bo & Chen, Jian & Zhang, Leiqi & Zhang, Xuesong & Qin, Ruwen & Lin, Xiangning, 2018. "Three representative island microgrids in the East China Sea: Key technologies and experiences," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 262-274.
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    1. Hernandez-Matheus, Alejandro & Löschenbrand, Markus & Berg, Kjersti & Fuchs, Ida & Aragüés-Peñalba, Mònica & Bullich-Massagué, Eduard & Sumper, Andreas, 2022. "A systematic review of machine learning techniques related to local energy communities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).

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