[Paper Review] Transactive Energy System: Market-Based Coordination of Distributed Energy Resources

Sen Li, Jianming Lian+2 more|arXiv (Cornell University)|Aug 9, 2019

Smart Grid Energy Management129 references4 citations

TL;DR

This paper proposes a unifying framework for transactive energy systems that standardizes the modeling of market-based coordination among distributed energy resources (DERs). By formalizing four core elements—agent preference, control decision, information structure, and solution concept—it enables systematic comparison and design of transactive systems, demonstrating that mechanism design with VCG mechanisms achieves efficient, budget-balanced, and individually rational outcomes with minimal communication and computation.

ABSTRACT

Distributed energy resources (DER) provide significant value for renewable energy integration in modern power grids. However, unlocking this value requires complex design and coordination. This paper focuses on the emerging {\em transactive energy systems}, which draw tools and principles from economics to design the coordination strategies for DERs. The concept of transactive energy system broadly captures a huge body of literature, and many of them are closely related but fundamentally different. This gives rise to the following questions: how to formally compare different transactive energy systems and their proposed approaches? How to choose the right transactive energy system to formulate a given problem? What tools are available in the literature for each class of transactive energy systems? In this paper, we answer these questions by synthesizing a unifying framework for a large class of problems studied in the literature. The framework consists of preferences, control decision, information structure and solution concept. These elements are important in identifying and distinguishing various transactive energy systems in the literature. We employ the proposed framework to analyze a few important class of transactive energy systems. Their connections and differences are discussed, and available tools for each class of problems are surveyed.

Motivation & Objective

• Address the lack of a systematic framework to compare and analyze diverse transactive energy systems in the literature.
• Formalize the key structural elements that differentiate transactive energy systems, such as competitive markets, Stackelberg games, and mechanism design.
• Enable the design of efficient, budget-balanced, and individually rational transactive energy mechanisms for DER coordination.
• Provide a standardized toolset for researchers and practitioners to select and adapt appropriate coordination mechanisms based on system requirements.
• Facilitate future research by identifying gaps in modeling dynamics and uncertainties in transactive energy systems.

Proposed method

• Define a unifying framework with four components: agent preference (utility functions), control decision (action variables), information structure (information availability), and solution concept (rationality assumptions).
• Model transactive energy systems as strategic games where agents submit parameters (e.g., bid signals) to influence system outcomes.
• Apply the VCG mechanism to ensure efficiency, budget balance, and individual rationality in mechanism design-based systems.
• Use the outcome function $ a^*(\sigma) = \arg\!\max_a \sum_i \bar{V}_i(a_i; \sigma_i) $ to determine optimal allocations based on declared parameters.
• Implement payment rules $ t_i(\sigma) = \sum_{j \neq i} \bar{V}_j(a_j^*; \sigma_j) + h_i(\sigma_{-i}) $ to ensure incentive compatibility.
• Demonstrate that under mild regularity conditions (strict concavity, differentiability, and surjectivity of marginal utilities), Nash equilibria achieve social welfare maximization.

Experimental results

Research questions

• RQ1 How can transactive energy systems be systematically classified and compared based on their structural and behavioral components?
• RQ2 What are the key differences in design and performance between competitive markets, Stackelberg games, reverse Stackelberg games, and mechanism design in transactive energy systems?
• RQ3 Under what conditions can mechanism design ensure efficiency, budget balance, and individual rationality in DER coordination?
• RQ4 How can minimal communication and computation requirements be achieved while maintaining system efficiency and incentive compatibility?
• RQ5 What tools and analytical frameworks are available to model and evaluate different classes of transactive energy systems?

Key findings

• The proposed unifying framework successfully standardizes the formulation of transactive energy systems by identifying four essential components: agent preference, control decision, information structure, and solution concept.
• The VCG mechanism applied within the framework ensures that the Nash equilibrium achieves social welfare maximization, i.e., $ \sigma^* = \arg\!\max_a \sum_i U_i(a_i; \theta_i) $, under regularity conditions.
• Efficient mechanisms can be constructed with minimal communication—e.g., a quadratic $ \bar{V}_i $ requires only a scalar parameter per agent—while maintaining computational tractability via quadratic programming.
• The framework supports budget balance and individual rationality, as demonstrated by results from [132], [135], [136], and [137], making mechanisms practical for real-world deployment.
• The framework enables the design of mechanisms that elicit private information (e.g., baselines or demand response parameters) for improved system coordination without compromising efficiency.
• The analysis reveals that supply function bidding leads to bounded efficiency loss, and extensions to capacity and network constraints are feasible, as shown in [139]–[143].