Market-Driven Flexibility Provision: A Tri-Level Optimization Approach for Carbon Reduction

TL;DR

This work tackles the mismatch between real-time electricity prices and carbon intensity in high-renewables grids by coupling an incentive-based tariff with a tri-level optimization that engages demand-side flexibility. The methodology links a Market Operation Platform (MOP), flexibility prosumers, and market clearing to promote carbon-aware consumption while maximizing revenues, using a dynamic tariff and day-ahead/real-time bidding. Key contributions include the design of a tolerance-enabled incentive function within a dynamic optimal range $[E^L_{i,t}, E^U_{i,t}]$, a tri-level framework that coordinates system-wide net-zero aims with prosumer revenues, and validation on a modified IEEE-33 bus with ENOWA data under two RES scenarios. The results demonstrate that the approach can effectively steer loads toward lower-carbon periods, enhance participation in flexibility markets, and provide a feasible path toward 100% RES-enabled operation with practical market mechanisms.

Abstract

The integration of renewable energy resources (RES) in the power grid can reduce carbon intensity, but also presents certain challenges. The uncertainty and intermittent nature of RES emphasize the need for flexibility in power systems. Moreover, there are noticeable mismatches between real-time electricity prices and carbon intensity patterns throughout the day. These discrepancies may lead customers to schedule energy-intensive tasks during the early hours of the day, a period characterized by lower electricity prices but higher carbon intensity. This paper introduces a novel and comprehensive framework aimed at encouraging customer participation in electricity markets and aligning their flexibility with carbon intensity trends. The proposed approach integrates an incentive-based tariff with a tri-level optimization model, where customers are motivated to submit flexibility bids and, in return, receive financial rewards based on their contributions. The tri-level model ensures a dynamic interaction between the market operation platform (MOP) and end-users. Simulations are performed on a modified IEEE-33 bus system, supported by two scenarios with different RES generations and customer behaviors. Results demonstrate the effectiveness of the proposed framework in guiding the customers' consumption behaviors towards low carbon intensity.

Figures (14)

• Figure 1: Real-time price RTPCali and carbon intensity CarbonIntensityCali of a typical day in California.
• Figure 2: An illustrative example of the incentive-based tariff.
• Figure 3: The tri-level optimization for maximizing the flexibility revenues.
• Figure 4: Timeline diagram of the market operation platform (MOP) interactions with flexibility prosumers.
• Figure 5: The modified IEEE 33-bus test system.