Locational Energy Storage Bid Bounds for Facilitating Social Welfare Convergence

2025-02-25

AI Summary

This paper addresses the lack of risk-awareness and spatial heterogeneity in energy storage bidding caps within electricity markets. We propose a risk-aware multi-period chance-constrained economic dispatch model to derive location-specific storage bidding limits. Innovatively integrating system uncertainty and operator risk preferences, we derive analytical, statistically guaranteed bidding boundaries—explicitly characterizing their dependence on state-of-charge, net-load uncertainty, and risk parameters. By coupling chance-constrained optimization, risk-aware dispatch, and locational marginal pricing (LMP) mechanisms, we conduct proxy-based bidding simulations on the ISO-NE 8-bus system (30% renewable penetration, 20% storage penetration). Results demonstrate a 0.17% reduction in total system cost and a 10.16% increase in storage profit; moreover, these benefits scale positively with storage capacity.

Technology Category

• Reasoning under Uncertainty: Stochastic Optimization
• Planning, Routing, and Scheduling: Scheduling under Uncertainty
• Constraint Satisfaction and Optimization: Mixed Discrete/Continuous Optimization

Application Category

• Economics, Online Markets and Human Computation: Cost models of using LLMs in production systems
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

This paper proposes a novel method to generate bid ceilings for energy storage in electricity markets to facilitate social welfare convergence and regulate potential market power exercises. We derive the bid bounds based on a tractable multi-period economic dispatch chance-constrained formulation that systematically incorporates the uncertainty and risk preference of the system operator. The key analytical results verify that the bounds effectively cap the truthful storage bid across all uncertainty scenarios with a guaranteed confidence level. And the cleared storage bids should be bounded by the risk-aware locational marginal price. We show that bid bonds decrease as the state of charge increases but rise with greater net load uncertainty and risk preference. We test the effectiveness of the proposed pricing mechanism based on the 8-bus ISO-NE test system, including agent-based storage bidding models. Simulation results show that the bid bounds effectively adjust storage bids to align with the social welfare objective. Under 30% renewable capacity and 20% storage capacity, the bid bounds contribute to an average reduction of 0.17% in system cost, while increasing storage profit by an average of 10.16% across various system uncertainty scenarios and bidding strategies. These benefits scale up with increased storage capacity withholding and storage capacity.

Problem

• Bid bounds for energy storage to reduce system costs
• Incorporating uncertainty and risk in economic dispatch
• Aligning storage bids with social welfare objectives

Innovation

• Chance-constrained economic dispatch for bid bounds
• Bid bounds cap storage offers across uncertainties
• Agent-based testing shows cost and profit improvements