[Paper Review] A Transactive Energy Market Framework Considering Network Constraints and Fairness

Fredmar N. Asarias, Michael Angelo A. Pedrasa|arXiv (Cornell University)|Mar 31, 2021

Smart Grid Energy Management27 references4 citations

TL;DR

This paper proposes a three-stage transactive energy market framework that integrates full AC optimal power flow and a fairness-aware benefit allocation algorithm to ensure equitable profit distribution among distributed energy resource (DER) participants. By jointly optimizing DER dispatch, transaction prices, and network constraints, the framework achieves system-wide welfare maximization and ensures that all participants—especially DER owners—receive fair incentives proportional to their contribution, as validated in an IEEE 33-bus system with significant cost reduction and balanced cash flows.

ABSTRACT

The continuous penetration of distributed energy resources (DER) in the electric power grid is driving a new paradigm shift towards transactive energy system (TES), an active and more sustainable system characterized by distributed generation and energy exchanges among consumers and producers in the network. This transition, however, comes with challenges such as dealing with the nonlinear and non-convex power flows of the system, determining an optimal transaction price to maximize overall system welfare, and ensuring fairness for all participants. In this paper, we propose a three-stage transactive energy framework that aims to address these challenges. In the first stage, the cost without trading is calculated which will serve as the reference in the profit maximization problem in the next stage. DER dispatch, power flows and initial transaction payments/incentives of the participants will then be determined in the second stage. A benefit allocation algorithm is applied in the third control stage to determine the optimal transaction price and final payments/incentives that will ensure fairness for trading participants. The proposed framework was tested in an IEEE 33-bus system and results show that fair benefits are given for all participants during trading and the system operates within the network and economic constraints.

Motivation & Objective

• To address the lack of fairness and accurate network modeling in existing transactive energy systems, especially with nonlinear AC power flows.
• To ensure equitable profit distribution per unit of energy traded among DER participants, preventing disincentives for smaller or renewable-rich prosumers.
• To develop a three-stage framework that integrates AC optimal power flow, profit maximization, and fairness-based incentive allocation.
• To validate the framework’s ability to maintain network constraints while improving system-wide economic efficiency and participant welfare.
• To provide a scalable, fair, and economically efficient mechanism for real-world distribution-level energy trading with high DER penetration.

Proposed method

• Stage 1 computes the baseline cost without trading, serving as a reference for profit maximization in subsequent stages.
• Stage 2 solves a joint optimization problem using AC optimal power flow (AC OPF) to determine optimal DER dispatch, power flows, and initial transaction payments/incentives.
• Stage 3 applies a benefit allocation algorithm based on Nash bargaining theory to compute fair transaction prices and final payments, ensuring equal profit per unit of energy transacted.
• The framework uses a non-linear, non-convex AC OPF model to accurately represent real distribution network constraints, avoiding linearized or relaxed approximations.
• The benefit allocation algorithm equalizes profit per unit energy across all producers and consumers, adjusting for energy exported/imported and network losses.
• The entire framework is tested on an IEEE 33-bus system under realistic time-varying load and renewable generation profiles.

Experimental results

Research questions

• RQ1 How can a transactive energy market framework ensure fairness in profit distribution among DER participants while respecting AC power flow constraints?
• RQ2 What is the impact of using a full AC OPF model versus relaxed or linearized models on the accuracy and efficiency of energy trading in distribution systems?
• RQ3 Can a three-stage framework that integrates AC OPF, profit maximization, and fairness-based incentive allocation lead to improved system-wide welfare and balanced cash flows?
• RQ4 How does the benefit allocation algorithm affect the profit per unit of energy traded for producers and consumers across different time periods?
• RQ5 To what extent does the proposed framework reduce overall energy costs and improve participation incentives for DER owners?

Key findings

• The proposed framework ensures that all participants, including those with high DER output, receive fair incentives, with profit per unit energy transacted becoming uniform after benefit allocation.
• At time t=23, producers exporting over 1,000 kWh earned only $0.92 and $2.80 respectively, highlighting the need for fairness mechanisms to prevent discouragement of participation.
• After applying the benefit allocation algorithm, profit per unit energy transacted became equal for all producers and consumers, achieving fairness across all time steps.
• The optimal transaction price was found to be higher than the utility’s selling price and lower than the utility’s buying price, ensuring mutual benefit for all participants.
• The system achieved full compliance with network constraints, including thermal limits and voltage profiles, through the use of full AC OPF in the optimization process.
• Simulation results showed a reduction in overall energy cost for participants and balanced cash flows, demonstrating improved system-wide economic efficiency.