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A chef occupied by research works (also a barista terrible at latte art).
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portfolio
My photographic works
A photographer records memorable moments in life. 
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A cat-dad needs Bubble Tea badly for emotional support. Bubble is a cat that master in fetching and high-five! His Instagram.
publications
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
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
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
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
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
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
talks
State-of-Charge Dependent Energy Storage Market Model
Published:
This talk introduces a new state-of-charge dependent makret model to incorporate energy storage into real-time power system economic dispatch. Sildes here
Integrating Physical Model with Machine Learning for Energy Storage Control
Published:
This talk will present a new approach to ccontrol energy storage to provide grid services by combining a physical model with machine learning based on the opportunity value. Sildes here
teaching
Environmental Health Enginnering System Design
Teaching Assistant, Johns Hopkins University, Environmental Health Enginnering, 2019
A collection of systems analytic techniques which are frequently used in the study of public decision making is presented. Emphasis is on mathematical programming techniques. Including linear programming, duality, integer and mixed-integer programming, multiobjective programming, dynamic programing, and stochastic programing.
Risk and Decision Analysis
Teaching Assistant, Johns Hopkins University, Environmental Health Enginnering, 2019
This class introduces the decision analysis approach to making decisions under risk and uncertainty. Topics covered include decision trees, Bayes law, value of information analysis, elicitation of subjective probabilities, multiattribute utility, and their applications to environmental and energy problems. Textbook: R.T. Clemen, Making Hard Decisions, 2014. Recommended Course Background: introductory statistics and probability.
EAEE4257 ENVIR DATA ANALYSIS & MODELING
Teaching Assistant, Columbia University, Earth and Environmental Enginnering, 2022
Introduction parametric and non-parametric statistical models applied to climate and environmental data analysis. Time and space data analysis methods will be focused, including clustering, autoregressive models, trend analysis, Bayesian analysis, missing data imputation, geostatistics, principal components analysis. Application to problems of climate variation and change; hydrology; air, water and soil pollution dynamics; disease propagation; ecological change; and resource assessment. The class requires the use of R with hands-on programmings and a term project applied to a current environmental data analysis problem.
EEEL4257 Energy System Economics and Optimization
Teaching Assistant, Columbia University, Earth and Environmental Enginnering, 2022
Fundamental of power system economics over which the current electricity markets are designed. Formulation of unit commitment and economic dispatch as mathematical optimization. Modeling of thermal generators, renewable generators, energy storage, and other grid resources in power system optimization. Introduction of equilibriums in electricity markets. Introduction of ancillary service markets. Overview of current energy system research topics.