[Paper Review] Robust Integration of High-level Dispatchable Renewables in Power System Operation

Hongxing Ye, Jianhui Wang+1 more|arXiv (Cornell University)|Dec 18, 2015

Electric Power System Optimization20 references3 citations

TL;DR

This paper proposes a two-stage robust unit commitment model that treats dispatchable renewable energy sources (RES) as flexible resources in high-penetration renewable power systems. By modeling RES as market participants capable of bidding and controlling output up to their maximum capacity, the approach directly identifies the worst-case scenario without iterative subproblem solving, ensuring robustness with only one additional scenario. The method reduces computational burden and enables higher RES integration while lowering system costs compared to traditional robust UC models.

ABSTRACT

The increasing penetration of Renewable Energy Sources (RES) requires more Flexibility Resources (FR), generally thermal units and storages, must be kept in the system to accommodate the uncertainties from RES. The challenge is how the system can survive when the RES level is very high. In this paper, RESs are considered as full-role market participants. They can bid in the day-ahead market, and the powers they deliver to the market are controllable up to their maximum available powers. Therefore, RESs are effectively dispatchable and can function as FR providers. To integrate dispatchable renewables, a two-stage robust Unit Commitment (UC) and dispatch model is established. In the first stage, a base UC and dispatch is determined. In the second stage, all FRs including RESs are used to accommodate the uncertainties, which is a Mixed-Integer Programming (MIP) problem. It is proved that the solution to the max-min problem can be identified directly whether the strong duality holds or not for the inner minimization problem. The solution robustness is guaranteed by including only one extra scenario. Numerical results show the effectiveness of the proposed model and its advantages over the traditional robust UC model with high level RES penetration.

Motivation & Objective

• To address the challenge of integrating high levels of renewable energy sources (RES) into power systems while maintaining system security and flexibility.
• To overcome the over-conservativeness and high computational cost of traditional robust SCUC models with non-dispatchable RES.
• To enable RES to act as flexible resources by modeling them as dispatchable market participants capable of controlling output up to their maximum capacity.
• To develop a computationally efficient robust optimization framework that guarantees solution robustness without iterative Benders or column generation schemes.
• To demonstrate that dispatchable RES can provide flexibility and reduce total system cost, especially under high uncertainty levels.

Proposed method

• A two-stage robust unit commitment (UC) and dispatch model is formulated, where the first stage determines a base UC and dispatch, and the second stage adjusts all flexible resources—including dispatchable RES—to accommodate uncertainty.
• The worst-case scenario for the second-stage re-dispatch problem is directly identified using duality theory, without requiring strong duality to hold, ensuring robustness.
• The robustness is guaranteed by including only one additional scenario (the worst-case scenario), eliminating the need for iterative Benders or column generation methods.
• Dispatchable RES are modeled as market participants that bid in the day-ahead market and can deliver power up to their maximum available output, effectively acting as flexible regulation resources.
• The model is formulated as a mixed-integer program (MIP), and the solution approach avoids solving non-convex max-min subproblems by leveraging duality-based identification of worst-case uncertainty.
• Numerical validation is performed on the IEEE 118-bus system under varying uncertainty levels, RES bid prices, and fast-startup unit configurations.

Experimental results

Research questions

• RQ1 Can dispatchable renewable energy sources be effectively modeled as flexible resources in robust unit commitment under high penetration?
• RQ2 How can the worst-case uncertainty scenario be identified directly without iterative subproblem solving or duality assumptions?
• RQ3 What is the impact of RES dispatchability on system cost, RES procurement, and system flexibility under high uncertainty?
• RQ4 How does the inclusion of fast-startup units affect RES integration and system operational cost?
• RQ5 Can the proposed model achieve robustness with only one additional scenario, and how does it compare computationally to existing robust UC methods?

Key findings

• The proposed model reduces total system cost by 9.58% when RES energy procurement is optimized under a 30% uncertainty level, indicating that relying on thermal units for reserve is more economical than procuring full RES energy.
• With a $5/MWh bid offer, RES energy procurement drops from 91.93% to 80.16% when the weight factor for worst-case cost increases from 0 to 1, showing that over-optimizing for worst-case scenarios reduces RES utilization.
• When fast-startup units are introduced, RES energy procurement increases to 98.57% (from 91.06%) with a $5/MWh bid, demonstrating that flexible resources enhance the system’s ability to absorb more renewable energy.
• The model achieves solution within 2 seconds on the IEEE 118-bus system, significantly outperforming existing robust UC methods that fail to converge within 2 hours without acceleration techniques.
• The worst-case scenario can be identified directly via duality, even without strong duality, enabling robustness with only one extra scenario and eliminating iterative Benders or column generation processes.
• The traditional robust UC model becomes infeasible at high RES penetration levels when RES are non-dispatchable, but the proposed model maintains feasibility and robustness through dispatchable RES.