Establishing a Hierarchical Local Market Structure Using Multi-cut Benders Decomposition 

By Haoyang Zhang, Sen Zhan, Koen Kok, and Nikolaos G. Paterakis

Department of Electrical Engineering, Eindhoven University of Technology

Introduction and Motivation

The need for a novel market framework to manage the increasing deployment of distributed energy resources (DERs), energy storage systems (ESSs), and smart meters is addressed. This framework facilitates local energy exchange and enhances grid reliability. The proposed solution integrates local electricity markets (LEMs) with local flexibility markets (LFMs) to enable prosumers to trade electricity and flexibility services while ensuring grid stability.

Market Framework

A hierarchical prosumer-centric market framework combining a hybrid LEM and an LFM is proposed. The LEM includes a peer-to-peer (P2P) market and community-based markets. The multi-cut Benders decomposition (MCBD) method is used to decompose the integrated LEM into a centralized P2P market and several community-based markets. Aggregators manage energy sources and demands as virtual power plants (VPPs) within the low voltage (LV) distribution networks, participating in P2P trading over the medium voltage (MV) distribution network. A modified MCBD (M-MCBD) approach is introduced to accelerate the convergence process.

Local Flexibility Market (LFM)

The LFM, operated by the distribution system operator (DSO), is formulated as a mixed-integer nonlinear programming (MINLP) problem and relaxed to a mixed-integer second-order cone programming (MI-SOCP) problem. VPPs submit quantity-price bids to provide flexibility services such as up-regulation and down-regulation. The LFM ensures grid operations under constraints and minimizes the total procurement cost of flexibility services.

Case Study

A case study demonstrates the efficacy of the proposed framework. Two distribution networks were analyzed: one with 31 buses and 30 VPPs, and another with 97 buses and 90 VPPs. The study compared scenarios with and without LFM, showing that LFM effectively manages grid constraints, alleviates congestion, and ensures stable operations.

Conclusion and future work

The hierarchical market framework, incorporating both a hybrid LEM and LFM, successfully coordinates electricity trading and flexibility services while maintaining grid stability. The M-MCBD method significantly improves convergence speed and accuracy. Future research will explore multi-agent reinforcement learning algorithms for preference negotiation among agents and extend the LFM to meshed distribution networks.

Key contributions

Development of a hierarchical local market framework combining LEM and LFM.

  1. Use of MCBD and M-MCBD to decompose and accelerate the convergence of the integrated hybrid LEM.

  2. Formulation of the LFM as an MINLP and relaxation to MI-SOCP.

  3. Demonstration of the framework’s effectiveness in managing grid operations through a detailed case study.

By implementing this framework, the economic benefits for prosumers are enhanced, and the overall efficiency and reliability of electricity systems are improved.

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This research is part of the research project MegaMind (Measuring, Gathering, Mining and Integrating Data for Self-management in the Edge of the Electricity System), (partly) funded by NWO (Dutch Research Council) through the Perspectief program under number P19–25.

Zhang, Haoyang, Zhan, Sen, Kok, Koen, and Paterakis, Nikolaos G., Establishing a Hierarchical Local Market Structure Using Multi-cut Benders Decomposition. Department of Electrical Engineering, Eindhoven University of Technology, Applied Energy 363 (2024) 123073. Available at: https://doi.org/10.1016/j.apenergy.2024.123073