Qixin Chen

Qixin Chen
Tsinghua University | TH · Department of Electrical Engineering

Doctor of Philosophy

About

222
Publications
72,638
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
5,346
Citations
Citations since 2016
147 Research Items
4806 Citations
201620172018201920202021202202004006008001,000
201620172018201920202021202202004006008001,000
201620172018201920202021202202004006008001,000
201620172018201920202021202202004006008001,000
Additional affiliations
December 2012 - September 2015
Tsinghua University
Position
  • Research Associate

Publications

Publications (222)
Article
Full-text available
The virtual power plant (VPP) has the potential to provide frequency regulation services by aggregating demand-side distributed energy resources (DERs). Cellular communication networks are commonly utilized for connecting DERs. Nevertheless, conventional cellular networks prior to 5G were unreliable, while private cellular networks incur huge inves...
Article
Full-text available
The rapid development of distributed photovoltaic (PV) systems poses great challenges to the integration capability of distribution networks. Traditionally, the transfer capacity of power distribution equipment is calculated as the maximum loading that prevents overheating under the assumption of extreme weather conditions. Dynamic thermal rating (...
Article
Full-text available
Equilibrium analysis has been widely studied as an effective tool to model gaming interactions and predict market results. However, as competition modes are fundamentally changed by the decarbonization and decentralization of power systems, analysis techniques must evolve. This article comprehensively reviews recent developments in modelling method...
Article
Sizeable lithium-ion battery (LIB) sources in the transportation and power sectors provide a promising approach to alleviate the increasing volatility in energy systems. To dispatch LIBs durably and safely, operators need to estimate the battery power characteristics, which are commonly derived from external states of the battery obtained by empiri...
Article
With the increasing penetration of electric vehicles (EVs), uncoordinated EV charging and the resulting chaos, disorder, and long waiting times at EV charging stations (EVCSs) will no longer be tolerable. An EV charging right (CR) is the right to reserve a predefined charging service. By purchasing CRs, EVs can reduce their charging waiting time, a...
Preprint
Full-text available
Lithium-ion batteries (LIBs) play an essential role in the energy sector and have been widely deployed in recent years. Generally, LIBs are managed in model-driven manners, leading to the need for parameter identification. However, as an electrochemical system, the battery contains various parameters while the measurements are mainly the current an...
Chapter
In the original version of the book, the following belated corrections have been made
Article
With the increasing penetration of renewables, energy storage systems (ESS) are becoming growingly important due to its peak-shaving ability. However, the current market mechanism is not well prepared for the participation of the ESSs. Firstly, the current bidding structure requires the ESSs to submit separate parameters for charging and dischargin...
Article
With the worldwide restructuring of power markets, it is more meaningful to analyze the bidding behaviors of generation companies (GENCOs). A realistic bidding behavior model can help to design better power market mechanisms. However, most existing studies usually use strong assumptions, where all GENCOs behave perfectly rationally when participati...
Article
For electricity market participants, proper information on the current grid topology is helpful for applications such as locational marginal price (LMP)/congestion forecasting, valuation of electricity derivatives, and operation of generation/distribution assets. However, in many markets, the publication of the grid topology is usually untimely or...
Article
This paper studies the pool strategy for price-makers under imperfect information. In this occasion, market participants cannot get essential transmission parameters of the power system. Thus, price-makers should estimate the market results with respect to their offer curves using available historical information. The linear programming model of ec...
Article
The penetration of lithium-ion batteries (LIBs) in transport, energy, and communication systems is increasing rapidly. A meticulous but simplified LIB model for non-uniform internal state monitoring and online control is sought in practice. Based on the pseudo-two-dimensional (P2D) model, a simplified electro-chemical model for LIBs is proposed. Sp...
Article
The shortage of inertia and primary frequency response (IPFR) will be more severe in future power systems since conventional fossil-based synchronous generators are gradually being replaced by variable renewable energy (VRE) generators. To relieve the shortage of IPFR, corresponding market mechanisms should be designed and incorporated to motivate...
Preprint
Full-text available
The penetrations of lithium-ion batteries in transport, energy and communication systems are increasing rapidly. A meticulous model applicable for precise in-situ monitoring and convenient online controlling is in sought to bridge the gap between research and applications. This paper proposes a simplified electro-chemical model and its discrete-tim...
Article
Full-text available
In virtual power plants (VPPs), distributed devices (such as residential appliances, energy storage, and electric vehicles) communicate with control centers via wireless access points (APs). Nevertheless, with a massive number of devices connected to APs, VPPs would be adversely affected by packet loss and consequently suffer from revenue reduction...
Chapter
Massive and various bad data may be introduced to load profiles in the process of data acquisition, transmission, and storage deliberately or accidentally due to cyber attacks and equipment failures. The bad data may result in bias for load forecasting and other data analytic applications. This chapter proposes a novel bad data identification and r...
Chapter
Myriad studies have been conducted on bidding behaviors following a worldwide restructuring of the electric power market. The common theme in such studies involves idealized and theoretical economic assumptions. However, practical bidding behaviors could deviate from that based on theoretical assumptions, which would undoubtedly limit the effective...
Chapter
One of the key steps for optimal bidding in power markets is to estimate the rivals’ bidding behaviors. However, for most participants, it would be difficult to directly forecast the rivals’ individual bids due to the information privacy and volatile characteristics of individual bidding behaviors. From another point of view, the aggregation of ind...
Chapter
Short-term locational marginal price (LMP) forecasting is the traditional problem of market participants and other institutions maximizing their profit. Most electricity market organizers in the world release the data of LMP along with its three components, i.e., the energy, congestion, and loss components. The series of the three components have t...
Chapter
Economic growth has greatly fluctuated around the world in recent years, and external economic factors (EEFs) have imposed more obvious effects on electricity consumption. To improve the accuracy and applicability of mid-term, especially monthly, electricity consumption forecasting, a novel monthly electricity consumption forecasting framework (den...
Chapter
Due to the restructuring of power markets worldwide, market simulation methods have attracted increasing attention. To address the limitations of the current commonly used methods, which are equilibrium analysis and agent-based simulation, a data-driven bottom-up power market simulation framework is proposed based on learning from individual offeri...
Chapter
Having a better understanding of how locational marginal prices (LMPs) change helps in price forecasting and market strategy making. This chapter investigates the fundamental distribution of the congestion part of LMPs in high-dimensional Euclidean space using an unsupervised approach. LMP models based on the lossless and lossy DC optimal power flo...
Chapter
Probabilistic load forecasting (PLF) has been extensively studied recently to characterize the uncertainties of future loads. Traditional PLF is implemented based on the historical load data itself and other relevant factors. However, the prevalence of smart meters provides more fine-grained consumption information. This chapter proposes a novel pr...
Chapter
Probabilistic load forecasting (PLF) is able to present the uncertainty information of the future loads. It is the basis of stochastic power system planning and operation. Recent works on PLF mainly focus on how to develop and combine forecasting models; while the feature selection issue has not been thoroughly investigated for PLF. This chapter fi...
Chapter
The market deregulation of the power industry based on the principle of “bid-based, security-constrained economic dispatch (SCED)" has resulted in dramatic changes for system operators, generation companies, and electricity consumers. The operation of power markets constantly produces valuable market data which can support the decision of both mark...
Chapter
Due to the deregulation of power systems worldwide, bidding behavior simulation research has gained prominence. One crucial element in these studies is accurately defining the individual reward function (or objective function). Considering the information barriers between market participants and researchers, the common way is to develop reward func...
Chapter
This chapter studies the financial transmission right (FTR) portfolio construction problem from the perspective of a speculator. Such problem is modeled as a stochastic programming problem in which uncertainty comes from the price spread across different pricing nodes over a certain holding period. Since it is difficult to model and forecast the jo...
Chapter
Electricity price forecasting is very important for market participants in a deregulated market. However, only a few literatures have investigated the impact of forecasting errors on the market participants’ behaviors and revenues. In this chapter, a general formulation of bidding in the electricity market is considered and the participant is assum...
Article
This work investigates a distribution locational marginal price (DLMP) scheme for promoting the market penetration of small-scale prosumers/consumers connected at distribution level and boosting their potential of demand response. In the distribution market, the distribution market operator (DMO) negotiates with each participant a node-specific DLM...
Article
Full-text available
The continuous growth of renewable generation in power systems brings serious challenges to electricity markets due to their characteristics different from conventional generation technologies. These challenges come from two dimensions, including short‐term (energy and ancillary service markets) and long‐term (long‐term bilateral and capacity marke...
Article
One of the key steps for optimal bidding in power markets is to estimate the rivals bidding behaviors. However, for most participants, it would be difficult to directly forecast the rivals individual bids due to the information privacy and volatile characteristics of individual bidding behaviors. From another point of view, the aggregation of indiv...
Article
Due to the deregulation of power systems worldwide, bidding behavior simulation research has gained prominence. One crucial element in these studies is accurately defining and modelling the individual reward function (or objective function). Considering the ubiquitous information barriers between market participants and researchers, the common way...
Article
Last decade has witnessed a booming development in renewables and significant changes in the generation mix around the world. Given their relatively low variable costs, renewables are expected to be cleared first in the electricity market and earn profit margins under a marginal pricing mechanism to recover their fixed costs. However, some strategi...
Book
This book aims to solve some key problems in the decision and optimization procedure for power market organizers and participants in data-driven approaches. It begins with an overview of the power market data and analyzes on their characteristics and importance for market clearing. Then, the first part of the book discusses the essential problem of...
Article
Full-text available
Smart grids (SGs) are reforming towards utilizing massive data for operations and services. During this reform, the information and communication technologies (ICTs) play a critical role, especially for the computing model, which determines how data analytics in SG can be executed. Edge computing (EC), a novel computing paradigm innovation, has hig...
Article
Full-text available
Electricity price forecasting is very important for market participants in a deregulated market. However, only a few papers investigated the impact of forecasting errors on the market participants' behaviours and revenues. In this study, a general formulation of bidding in the electricity market is considered and the participant is assumed to be a...
Article
Full-text available
With the increasing penetration of renewables, power systems have to operate in a more flexible way to address the uncertainties of renewable output. This paper develops an uncertainty locational marginal price (ULMP) mechanism to price these uncertainties. They are denoted as box deviation intervals as suggested by the market participants. The ULM...
Article
Battery storage is expected to play a crucial role in the low-carbon transformation of energy systems. The deployment of battery storage in the power grid, however, is currently limited by its low economic viability, which results from not only high capital costs but also the lack of flexible and efficient utilization schemes and business models. M...
Article
Full-text available
Under the high penetration of distributed photovoltaic (PV) resources, distribution networks face great transfer capacity and voltage rise challenges, which drives the transformation to active distribution networks (ADNs). Transformers are critical and costly components that are generally hard to reinforce or replace. Dynamic thermal rating (DTR) i...
Article
China's electricity demand has grown rapidly over only two decades and is currently the largest in the world. This was largely owing to a framework of regulation in which governments regulated prices and quantities, and there was ample incentive for investment. As the growth in electricity demand has slowed and the use of renewable energy has been...
Preprint
Battery storage is expected to play a crucial role in the low-carbon transformation of energy systems. The deployment of battery storage in the power gird, however, is currently severely limited by its low economic viability, which results from not only high capital costs but also the lack of flexible and efficient utilization schemes and business...
Article
Full-text available
Having a better understanding of how locational marginal prices (LMPs) change helps in price forecasting and market strategy making. This paper investigates the fundamental distribution of the congestion part of LMPs in high-dimensional Euclidean space using an unsupervised approach. LMP models based on the lossless and lossy DC optimal power flow...
Article
Full-text available
With rapid growth of distributed renewable genera-tion, the establishment of electricity distribution markets has attracted widespread concerns. Different from existing transmis-sion grid-scale electricity markets, an electricity distribution market is featured by numerous small-scale prosumers, and zero marginal cost and intermittency of renewable...
Article
Full-text available
Short-term locational marginal price (LMP) forecasting is the traditional problem of market participants and other institutions maximizing their profit. Most electricity market organizers in the world release the data of LMP along with its three components, i.e., the energy, congestion, and loss components. The series of the three components have t...
Book
Full-text available
This book aims to make the best use of fine-grained smart meter data to process and translate them into actual information and incorporated into consumer behavior modeling and distribution system operations. It begins with an overview of recent developments in smart meter data analytics. Since data management is the basis of further smart meter dat...
Article
Full-text available
With the growing penetration of renewable energy in the smart grid, the uncertainties of power system performance are increasing. Probabilistic power flow (PPF) introduces statistical methods into the power flow calculation process, enabling fast and efficient power system operation state assessment and prediction uncertainty. The need of PPF for r...
Chapter
Due to the technical limitations of metering and privacy concerns of customers, the large-scale and real-time collection of residential load data still remains a big challenge. To address the problem, we use the generative adversarial networks (GANs) to produce synthetic residential loads as an alternative. Different from existing load generation m...
Chapter
The widespread popularity of smart meters enables an immense amount of fine-grained electricity consumption data to be collected. Meanwhile, the deregulation of the power industry, particularly on the delivery side, has continuously been moving forward worldwide. How to employ massive smart meter data to promote and enhance the efficiency and susta...
Chapter
Household energy behavior is a key factor that dictates energy consumption, efficiency, and conservation. In the past, household energy behavior was typically unknown because conventional meters only recorded the total amount of energy consumed by a household over a significant period of time. The rollout of smart meters enables real-time household...
Chapter
With the prevalence of smart meters, fine-grained sub-profiles reveal more information about the aggregated load and further help improve forecasting accuracy. This chapter proposes a novel ensemble approach for aggregated load forecasting. An ensemble is an effective approach for load forecasting. It either generates multiple training datasets or...
Chapter
In a competitive retail market, large volumes of smart meter data provide opportunities for load-serving entities (LSEs) to enhance their knowledge of customers’ electricity consumption behaviors via load profiling. Instead of focusing on the shape of the load curves, this chapter proposes a novel approach for the clustering of electricity consumpt...
Chapter
As the problem of electricity thefts via tampering with smart meters continues to increase, the abnormal behaviors of thefts become more diversified and more difficult to detect. Thus, a data analytics method for detecting various types of electricity thefts is required. However, the existing methods either require a labeled dataset or additional s...
Chapter
Designing customizing prices is an effective way to promote consumer interactions and increase customer stickiness for retailers. Fueled by the increased availability of high-quality smart meter data, this chapter proposes a novel data-driven approach for incentive-compatible customizing time-of-use (ToU) price design based on massive historical sm...
Chapter
Massive amounts of data are being collected owing to the popularity of smart meters. Two main issues should be addressed in this context. One is the communication and storage of big data from smart meters at a reduced cost which has been discussed in Chap. 3. The other one is the effective extraction of useful information from this massive dataset....
Chapter
Information acquisition devices such as smart meters are gaining popularity in recent years. The “cyber-physical-social” deep coupling characteristic of the power system becomes more prominent. Breakthroughs are needed to analyze the electricity consumer. In this situation, combining physical-driven and data-driven approaches is a significant trend...
Chapter
The installation of smart meters enables the collection of massive fine-grained electricity consumption data and makes individual consumer level load forecasting possible. Compared to aggregated loads, load forecasting for individual consumers is prone to non-stationary and stochastic features. In this chapter, a probabilistic load forecasting meth...
Chapter
This chapter investigates how such characteristics can be inferred from fine-grained smart meter data. A deep convolutional neural network (CNN) first automatically extracts features from massive load profiles. A support vector machine (SVM) then identifies the characteristics of the consumers. Comprehensive comparisons with state-of-the-art and ad...
Chapter
Although smart meter data analytics has received extensive attention and rich literature studies related to this area have been published, developments in computer science and the energy system itself will certainly lead to new problems or opportunities. In this chapter, we discuss some research trends for smart meter data analytics, such as big da...
Chapter
The huge amount of household load data requires highly efficient data compression techniques to reduce the great burden on data transmission, storage, processing, application, etc. This chapter proposes the generalized extreme value distribution characteristic for household load data and then utilizes it to identify load features, including load st...
Article
Myriad studies have been conducted on bidding behaviors following a worldwide restructuring of the electric power market. The common theme in such studies involves idealized and theoretical economic assumptions. However, practical bidding behavior could deviate from that based on theoretical assumptions, which would undoubtedly limit the effectiven...
Article
In the recent years, the electricity market deregulation reforms are prevalent in many countries, bringing about the problem of market power abuse. As a typical property right structure transformation approach, the vertical integration has rarely been considered and analyzed as a countermeasure towards market power abuse problem. Facing the divergi...
Article
Full-text available
During the operation of a distribution network, the meteorological factors (e.g., the wind speed, wind direction, ambient temperature and solar radiation) affect not only the maximum available output of the photovoltaic (PV) plant but also the parameters of the overhead line, such as the resistance and thermal rating. Since the degree to which the...
Article
Renewable energy will become a normal energy source and will be required to participate in the market. The renewable portfolio standards (RPS) together with tradable green certificates (TGC) are considered as an appropriate market mechanism to help recover renewable energy investments. The strategic offering behaviors of renewable energy should be...