Publications

Energy Storage State-of-Charge Market Model

Published in IEEE Transactions on Energy Markets, Policy and Regulation, 2022

This paper introduces and rationalizes a new model for bidding and clearing energy storage resources in wholesale energy markets. Charge and discharge bids in this model are dependent on the storage state-of-charge (SoC).

Recommended citation: N. Zheng, X. Qin, D. Wu, G. Murtaugh and B. Xu, "Energy Storage State-of-Charge Market Model," in IEEE Transactions on Energy Markets, Policy and Regulation, doi: 10.1109/TEMPR.2023.3238135. https://ieeexplore.ieee.org/abstract/document/10021874

Impact of Bidding and Dispatch Models over Energy Storage Utilization in Bulk Power Systems

Published in IREP 11th Bulk Power Systems Dynamics and Contorl Symposium, 2022

This paper analyzes how different dispatch models and bidding strategies would affect the utilization of storage with various durations in deregulated power systems.

Recommended citation: N. Zheng and B. Xu, “Impact of Bidding and Dispatch Models over Energy Storage Utilization in Bulk Power Systems.” IREP 11th Bulk Power Systems Dynamics and Contorl Symposium, 2022. https://www.wise-irep2022.org/programme

Demand response model identification and behavior forecast with OptNet: a gradient-based approach

Published in the Thirteenth ACM International Conference on Future Energy Systems, 2022

In this work, we propose a novel data-driven approach that incorporates prior model knowledge for predicting the behaviors of price-responsive demand resources. We propose a gradient-descent method to find the model parameters given the historical price signals and observations.

Recommended citation: [1] Y. Bian, N. Zheng, Y. Zheng, B. Xu, and Y. Shi, “Demand response model identification and behavior forecast with OptNet: a gradient-based approach,” in Proceedings of the Thirteenth ACM International Conference on Future Energy Systems, Virtual Event, Jun. 2022, pp. 418–429. doi: 10.1145/3538637.3538871. https://dl.acm.org/doi/abs/10.1145/3538637.3538871

Arbitraging Variable Efficiency Energy Storage Using Analytical Stochastic Dynamic Programming

Published in IEEE Transactions on Power System, 2022

This paper presents a computation-efficient stochastic dynamic programming algorithm for solving energy storage price arbitrage considering variable charge and discharge efficiencies. We formulate the price arbitrage problem using stochastic dynamic programming and model real-time prices as a Markov process.

Recommended citation: N. Zheng, J. J. Jaworski, and B. Xu, “Arbitraging Variable Efficiency Energy Storage using Analytical Stochastic Dynamic Programming,” IEEE Trans. Power Syst., pp. 1–1, 2022, doi: 10.1109/TPWRS.2022.3154353. https://ieeexplore.ieee.org/abstract/document/9721005

Crediting Variable Renewable Energy and Energy Storage in Capacity Markets: Effects of Unit Commitment and Storage Operation

Published in IEEE Transactions on Power Systems, vol. 37, no. 1, pp. 617–628, 2021

In this paper we propose a definition of capacity credit (CC) for valuing adequacy contributions of these resources based on their marginal capability to reduce expected unserved energy. We show that such marginal credits can incentivize system-optimal investments in markets with installed capacity requirements and energy price caps. We simulated such markets using a LP-based capacity expansion planning model with convexified unit commitment (UC) constraints and ES.

Recommended citation: S. Wang, N. Zheng, C. D. Bothwell, Q. Xu, S. Kasina, and B. F. Hobbs, “Crediting Variable Renewable Energy and Energy Storage in Capacity Markets: Effects of Unit Commitment and Storage Operation,” IEEE Trans. Power Syst., vol. 37, no. 1, pp. 617–628, Jan. 2022, doi: 10.1109/TPWRS.2021.3094408. https://ieeexplore.ieee.org/abstract/document/9473022

Market Power Challenges and Solutions for Electric Power Storage Resource

Published in Carnegie Mellon Electricity Industry Center Working Papers, 2021

Pivotal suppliers with energy storage resources (ESRs) can achieve supernormal profits when allowed to fully participate and set clearing prices in wholesale electricity markets. We classify three strategies identified by our bi-level model for achieving additional strategic profits: (1) increased ESR discharge bids, (2) decreased ESR charge bids, and (3) cross-product manipulation to benefit other resources owned by the pivotal ESR supplier.

Recommended citation: L. Lavin, Z. Ningkun, and J. Apt, “Market Power Challenges and Solutions for Electric Power Storage Resources,” Carnegie Mellon Electricity Industry Center Working Papers, 2021. https://www.cmu.edu/ceic/research-publications/ceic_21_02-esr-policy.pdf

Ningkun (Nik) Zheng