Shengfei YinLawrence Berkeley National Laboratory | LBL · China Energy Group
Shengfei Yin
Doctor of Philosophy in Electrical Engineering
Applied Optimization, Machine/Deep Learning, Electricity Market, Power System Operation
About
18
Publications
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Introduction
Gabriel (Shengfei) is currently a Postdoctoral Research Fellow at Lawrence Berkeley National Lab, specializing in applications of operations research, mathematical optimization and machine/deep learning on electricity market and power system operation.
Skills and Expertise
Publications
Publications (18)
Dramatic reductions in solar, wind, and battery storage costs create new opportunities to reduce emissions and costs in China’s electricity sector, beyond current policy goals. This study examines the cost, reliability, emissions, public health, and employment implications of increasing the share of non-fossil fuel (“carbon free”) electricity gener...
Renewable energy is poised to play a major role in achieving China's carbon neutrality goal by 2060; however, reliability and flexibility is a big concern of a renewable-dominant power system. Various strategies of enhancing flexibility are under discussion to ensure the reliability of such a system, but no detailed quantitative analysis has been r...
Dramatic reductions in solar, wind, and battery storage costs create new opportunities to reduce emissions and costs in China’s electricity sector, beyond current policy goals. This study examines the cost, reliability, emissions, public health, and employment implications of increasing the share of non-fossil fuel (“carbon free”) electricity gener...
The cross impacts between transmission and distribution systems have drawn extensive attention, where multi-energy carriers become increasingly dominant in local market operations. Local energy hubs, integrated with multi-energy carriers, e.g., electricity, gas, heat, present great potentials to provide adequate power and reserve support for the tr...
Customer baseline load (CBL) reconstruction is a critical problem in residential demand response (DR). The difficulty of residential CBL lies in the variability of both irregular consumption and on-site distributed energy resources (DERs). Targeting the CBL reconstruction of residential prosumers, a regression-based estimation scheme is proposed us...
Renewable energy is poised to play a major role in achieving China's carbon neutrality goal by 2060; however, reliability and flexibility are a big concern of a renewable-dominant power system. Various strategies of enhancing flexibility are under discussion to ensure the reliability of such a system, but no detailed quantitative analysis has been...
This paper proposes a three-stage unit commitment model for the market operation of transmission and distribution coordination under the uncertainties of renewable generation and demand variations. The first stage is for the independent system operator (TSO) that determines the commitment decisions of the transmission-level generators and the distr...
With the accelerating penetration of solar energy in energy systems, market operations concerning the solar associated intermittency are widely discussed. How to correctly model the solar generation in the market and solve the uncertainty-based operation problems call for solutions. Unlike other renewable resources, solar power can be more easily a...
This paper proposes a novel modeling framework and decomposition-based solution strategy combining stochastic programming (SP) and robust optimization (RO) to deal with multiplex uncertainties in coordinated mid- and long-term power system planning. The problem is formulated as a multi-year generation and transmission planning problem from an indep...
With penetration levels of photovoltaic (PV) generation substantially increasing, electric power systems need more flexible resources that can provide ancillary services to mitigate the variability and uncertainty of the PV. On one hand, the increase in PV generation necessitates more flexible resources; on the other hand, because of its low operat...
Unexpected large power surges will cause instantaneous grid shock, and thus emergency control plans must be implemented to prevent the system from collapsing. In this paper, by the aid of reinforcement learning (RL), novel model-free control (MFC)-based emergency control schemes are presented. Firstly, multi-Q-learning-based emergency plans are des...
Discussions about the future decentralized electricity market include concepts such as transactive energy, energy hub, transmission & distribution coordination, and distributional market pricing. As the advent of the smart grid approaches, the design of a realizable market paradigm that can integrate the wholesale market with the retail market and...
Since the Ukraine blackout in 2015, coordinated cyber physical attacks (CCPAs) have been emerging and are used to mask line outages in the smart grid. In this paper, we investigate the features of CCPAs and constitute the mathematic formulation with respect to topologies and electric parameters of a power grid before and after attacks. With the obj...
In this paper, optimal attack schemes against load frequency control (LFC) are studied by considering coordinated attack. By attacking sensor measurement (load) simultaneously, the attacker disrupts the normal operation of LFC, thus causing excess system frequency/generation excursions. From the perspective of the attacker, LFC system information a...