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Sharing Energy in Wide Area: A Two-Layer Energy Sharing Scheme for Massive Prosumers

Yifan Su, Peng Yang, Kai Kang, Zhaojian Wang, Ning Qi, Tonghua Liu, Feng Liu

TL;DR

The paper tackles the challenge of coordinating energy sharing among massive prosumers by introducing a two-layer market with local-area markets (LAMs) and a wide-area market (WAM). It proves that the Nash equilibrium in the LAM is equivalent to a convex optimization problem and presents a hierarchically distributed bidding algorithm that avoids binary variables, enabling scalable clearing. The WAM aggregates uncleared energy from LAMs and uses a DLMP-inspired price mechanism to ensure network feasibility while approaching social welfare. Case studies on the IEEE 123-bus system with 11250 prosumers demonstrate convergence, scalability, and significant social-efficiency gains from wide-area sharing, even in the presence of network congestion and price discrimination. This framework offers a practical path to large-scale, market-based energy sharing without overbearing computational requirements.

Abstract

The popularization of distributed energy resources transforms end-users from consumers into prosumers. Inspired by the sharing economy principle, energy sharing markets for prosumers are proposed to facilitate the utilization of renewable energy. This paper proposes a novel two-layer energy sharing market for massive prosumers, which can promote social efficiency by wider-area sharing. In this market, there is an upper-level wide-area market (WAM) in the distribution system and numerous lower-level local-area markets (LAMs) in communities. Prosumers in the same community share energy with each other in the LAM, which can be uncleared. The energy surplus and shortage of LAMs are cleared in the WAM. Thanks to the wide-area two-layer structure, the market outcome is near-social-optimal in large-scale systems. However, the proposed market forms a complex mathematical program with equilibrium constraints (MPEC). To solve the problem, we propose an efficient and hierarchically distributed bidding algorithm. The proposed two-layer market and bidding algorithm are verified on the IEEE 123-bus system with 11250 prosumers, which demonstrates the practicality and efficiency for large-scale markets.

Sharing Energy in Wide Area: A Two-Layer Energy Sharing Scheme for Massive Prosumers

TL;DR

The paper tackles the challenge of coordinating energy sharing among massive prosumers by introducing a two-layer market with local-area markets (LAMs) and a wide-area market (WAM). It proves that the Nash equilibrium in the LAM is equivalent to a convex optimization problem and presents a hierarchically distributed bidding algorithm that avoids binary variables, enabling scalable clearing. The WAM aggregates uncleared energy from LAMs and uses a DLMP-inspired price mechanism to ensure network feasibility while approaching social welfare. Case studies on the IEEE 123-bus system with 11250 prosumers demonstrate convergence, scalability, and significant social-efficiency gains from wide-area sharing, even in the presence of network congestion and price discrimination. This framework offers a practical path to large-scale, market-based energy sharing without overbearing computational requirements.

Abstract

The popularization of distributed energy resources transforms end-users from consumers into prosumers. Inspired by the sharing economy principle, energy sharing markets for prosumers are proposed to facilitate the utilization of renewable energy. This paper proposes a novel two-layer energy sharing market for massive prosumers, which can promote social efficiency by wider-area sharing. In this market, there is an upper-level wide-area market (WAM) in the distribution system and numerous lower-level local-area markets (LAMs) in communities. Prosumers in the same community share energy with each other in the LAM, which can be uncleared. The energy surplus and shortage of LAMs are cleared in the WAM. Thanks to the wide-area two-layer structure, the market outcome is near-social-optimal in large-scale systems. However, the proposed market forms a complex mathematical program with equilibrium constraints (MPEC). To solve the problem, we propose an efficient and hierarchically distributed bidding algorithm. The proposed two-layer market and bidding algorithm are verified on the IEEE 123-bus system with 11250 prosumers, which demonstrates the practicality and efficiency for large-scale markets.
Paper Structure (26 sections, 6 theorems, 30 equations, 8 figures, 1 table, 2 algorithms)

This paper contains 26 sections, 6 theorems, 30 equations, 8 figures, 1 table, 2 algorithms.

Table of Contents

  1. Introduction
  2. Background
  3. Related Works
  4. Contributions
  5. Organization
  6. Overall Market Architecture
  7. Lower-Level Local-Area Sharing Market
  8. Energy Sharing Mechanism
  9. Energy Sharing as A Nash Game
  10. Bidding Algorithm
  11. Prices in Equilibrium
  12. Upper-Level Wide-Area Sharing Market
  13. Energy Sharing Mechanism
  14. Bidding Algorithm
  15. Social Efficiency
  16. ...and 11 more sections

Key Result

Proposition 1

Under Assumption assum_price_discrimination, given $x_{j'}, \forall j'\in \mathcal{U}_i \setminus \left\{j\right\}$, the optimal purchased and sold electricity are complementary, i.e., $p_j^+ p_j^- = 0$.

Figures (8)

  • Figure 1: Two-layer architecture of the energy sharing market.
  • Figure 2: An illustration of the relationship among prices.
  • Figure 3: Configuration of the IEEE 123-bus system.
  • Figure 4: Total cost relative error and sharing price during iterations in the WAM.
  • Figure 5: Total cost relative errors and sharing prices during iterations in the LAMs.
  • ...and 3 more figures

Theorems & Definitions (15)

  • Proposition 1
  • Proposition 2
  • Definition 1: Nash Equilibrium
  • Proposition 3
  • Definition 2: Shadow Price
  • Proposition 4
  • Proposition 5
  • Proposition 6
  • Definition 3: Social Optimum
  • Remark 1
  • ...and 5 more