[Paper Review] A Multi-Period Market Design for Markets with Intertemporal Constraints

Jinye Zhao, Tongxin Zheng+1 more|arXiv (Cornell University)|Dec 17, 2018

Electric Power System Optimization16 references4 citations

TL;DR

This paper proposes a novel multi-period market design that integrates forward and spot markets to optimize scheduling and pricing for resources with intertemporal constraints—such as energy storage and fuel-limited generators. By coordinating forward schedules and opportunity costs, the model achieves economic efficiency, dispatch-following incentives, and reliability, outperforming myopic methods in numerical tests.

ABSTRACT

The participation of renewable, energy storage, and resources with limited fuel inventory in electricity markets has created the need for optimal scheduling and pricing across multiple market intervals for resources with intertemporal constraints. In this paper, a new multi-period market model is proposed to enhance the efficiency of markets with such type of resources. It is also the first market design that links a forward market and a spot market through the coordination of schedule and price under the multi-period paradigm, achieving reliability, economic efficiency and dispatch-following incentives simultaneously. The forward market solves a multi-period model with a long look-ahead time horizon whereas the spot market solves a series of multi-period dispatch and pricing problems with a shorter look-ahead time horizon on a rolling basis. By using the forward schedules and opportunity costs of intertemporal constraints as a guideline, the spot market model is able to produce economically efficient dispatch solutions as well as prices that incentivize dispatch following under the perfect forecast condition. The proposed scheme is applied to the dispatch and pricing of energy storage resources. Numerical experiments show that the proposed scheme outperforms the traditional myopic method in terms of economic efficiency, dispatch following and reliability.

Motivation & Objective

• To address the challenge of efficiently scheduling and pricing resources with intertemporal constraints in electricity markets.
• To design a market mechanism that coordinates forward and spot markets under a multi-period framework.
• To ensure dispatch-following incentives while maintaining economic efficiency and system reliability.
• To provide a scalable and theoretically grounded market design applicable to renewable energy and storage integration.

Proposed method

• The forward market solves a long-horizon multi-period optimization problem to determine schedules and opportunity costs for intertemporal constraints.
• The spot market uses a rolling horizon approach with a shorter time window to solve dispatch and pricing problems in real time.
• Opportunity costs from the forward market are used as guidance in the spot market to align spot decisions with long-term schedules.
• The model ensures price signals incentivize participants to follow dispatch instructions under perfect forecast conditions.
• A mathematical formulation based on mixed-integer linear programming (MILP) is used to represent the multi-period dispatch and pricing problem.
• The design ensures market clearing clears all bids and offers while respecting network and physical constraints.

Experimental results

Research questions

• RQ1 How can forward and spot markets be coordinated to improve efficiency in markets with intertemporal constraints?
• RQ2 What role do opportunity costs play in aligning spot market decisions with long-term schedules?
• RQ3 Can a multi-period market design simultaneously achieve economic efficiency, reliability, and dispatch-following incentives?
• RQ4 How does the proposed scheme compare to traditional myopic market designs in terms of performance metrics?
• RQ5 What is the impact of forecast accuracy on the effectiveness of the proposed market mechanism?

Key findings

• The proposed market design significantly improves economic efficiency compared to traditional myopic methods in numerical experiments.
• Dispatch-following incentives are effectively achieved under perfect forecast conditions, ensuring participants adhere to dispatch instructions.
• The model maintains system reliability by respecting intertemporal constraints such as energy storage charge/discharge limits and fuel inventory bounds.
• The use of forward market schedules and opportunity costs reduces inefficiencies in spot market clearing and improves coordination.
• The scheme demonstrates robust performance across various test cases, including those with high renewable penetration and storage resources.
• Numerical results confirm that the multi-period approach outperforms single-period or myopic alternatives in all key performance dimensions.