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Analyzing the Role of the DSO in Electricity Trading of VPPs via a Stackelberg Game Model

Peng Wang, Xi Zhang, Luis Badesa

TL;DR

The paper analyzes the role of a Distribution System Operator (DSO) as a trading organizer for Virtual Power Plants (VPPs) using a Stackelberg bilevel model, where the upper-level DSO maximizes profit and the lower-level VPPs minimize operating costs. The lower level is replaced by its KKT conditions to yield a single-level MPEC, solved with BilevelJuMP.jl and SCIP.jl to obtain a Stackelberg equilibrium. Results show that DSO-mediated trading (Mode 2) reduces energy flows to the wholesale market and lowers VPP costs, while allowing the DSO to capture profits, highlighting regulatory concerns about market fairness. The findings emphasize implications for market design, illustrating how an intermediary DSO can coordinate internal trading to benefit itself and VPPs, but potentially at the expense of wholesale-market revenues; future work should extend to ancillary services and formal proofs of equilibrium properties.

Abstract

The increasing penetration of distributed energy resources has sparked interests in participating in power markets. Here, we consider two settings where Virtual Power Plants (VPPs) with some flexible resources participate in the electricity trading, either directly in the wholesale electricity market, or interfaced by the Distribution System Operator (DSO) who is the transaction organizer. In order to study the role of DSO as a stakeholder, a Stackelberg game is represented via a bi-level model: the DSO maximizes profits at the upper level, while the VPPs minimize operating costs at the lower level. To solve this problem, the Karush-Kuhn-Tucker conditions of lower level is deduced to achieve a single-level problem. The results show that the role of the DSO as an intermediary agent leads to a decrease in operating costs of the VPPs by organizing lower-level trading, while making a profit for itself. However, this result comes with interests loss of the wholesale market, implying that stakeholders in the market need to abide by regulatory constraints.

Analyzing the Role of the DSO in Electricity Trading of VPPs via a Stackelberg Game Model

TL;DR

The paper analyzes the role of a Distribution System Operator (DSO) as a trading organizer for Virtual Power Plants (VPPs) using a Stackelberg bilevel model, where the upper-level DSO maximizes profit and the lower-level VPPs minimize operating costs. The lower level is replaced by its KKT conditions to yield a single-level MPEC, solved with BilevelJuMP.jl and SCIP.jl to obtain a Stackelberg equilibrium. Results show that DSO-mediated trading (Mode 2) reduces energy flows to the wholesale market and lowers VPP costs, while allowing the DSO to capture profits, highlighting regulatory concerns about market fairness. The findings emphasize implications for market design, illustrating how an intermediary DSO can coordinate internal trading to benefit itself and VPPs, but potentially at the expense of wholesale-market revenues; future work should extend to ancillary services and formal proofs of equilibrium properties.

Abstract

The increasing penetration of distributed energy resources has sparked interests in participating in power markets. Here, we consider two settings where Virtual Power Plants (VPPs) with some flexible resources participate in the electricity trading, either directly in the wholesale electricity market, or interfaced by the Distribution System Operator (DSO) who is the transaction organizer. In order to study the role of DSO as a stakeholder, a Stackelberg game is represented via a bi-level model: the DSO maximizes profits at the upper level, while the VPPs minimize operating costs at the lower level. To solve this problem, the Karush-Kuhn-Tucker conditions of lower level is deduced to achieve a single-level problem. The results show that the role of the DSO as an intermediary agent leads to a decrease in operating costs of the VPPs by organizing lower-level trading, while making a profit for itself. However, this result comes with interests loss of the wholesale market, implying that stakeholders in the market need to abide by regulatory constraints.
Paper Structure (18 sections, 23 equations, 6 figures, 5 tables)

This paper contains 18 sections, 23 equations, 6 figures, 5 tables.

Table of Contents

  1. Introduction
  2. Stackelberg Game Model for DSO and VPPs
  3. Game Model of Leader-DSO for Pricing
  4. Utility Function
  5. Constraints
  6. Game Model of Followers-VPPs for Managing Energy
  7. Utility Function
  8. Constraints
  9. Stackelberg Game Model
  10. Case Studies
  11. Test System Setting
  12. Analysis of Trading Results through the Stackelberg Game
  13. Cost Reduction Analysis for $\text{VPP}_\text{1}$
  14. Cost Reduction Analysis for $\text{VPP}_\text{2}$
  15. Cost Reduction Analysis for $\text{VPP}_\text{3}$
  16. ...and 3 more sections

Figures (6)

  • Figure 1: Diagram of energy and cash flows in the two market settings considered.
  • Figure 2: Stackelberg game framework for DSO and VPPs.
  • Figure 3: Load profiles and available wind power in each VPP.
  • Figure 4: Trading prices in two modes.
  • Figure 5: Profits changing of the wholesale power market.
  • ...and 1 more figures