Qinglai Guo's research while affiliated with Tsinghua University and other places
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Publications (84)
Transmission interface power flow adjustment is a critical measure to ensure the security and economy operation of power systems. However, conventional model-based adjustment schemes are limited by the increasing variations and uncertainties occur in power systems, where the adjustment problems of different transmission interfaces are often treated...
The growing development of the fast charging of electric vehicles has strengthened the interdependence between urban transportation networks(UTN) and power distribution networks(PDN). Through cooperative price guidance of UTN operator and PDN operator, the performance of the above networks can be improved coordinately. However, vehicle travelers ma...
Currently, the rapid development of Internet of Things (IoT) technology is promoting the development of smart grids. However, because of the numerous loads present and the surge of data in smart grids, network congestion, transmission delay and insufficient channel resources pose pressing challenges for accurate, real-time transmission in load cont...
In this paper, a deep reinforcement learning (DRL)-based electric vehicles (EVs) management strategy is proposed to achieve peak shaving and regulate the voltage violations in distribution networks. We present a new approach for modeling the EV user willingness considering the effect of multi-attribute attitudes and price incentives on user’ behavi...
High-quality demand-side management requires an abundance of load profiles to support decision-making processes. However, customer energy consumption data often contains sensitive personal information, and service providers face significant challenges in accessing a substantial amount of energy consumption data. To generate a large volume of custom...
For high wind power-penetrated power systems, the multiple renewable energy station short-circuit ratio (MRSCR) is often insufficient due to weak grid structures. Additionally, transient voltage sag/overvoltage issues may cause trip faults of wind turbines (WTs). Due to the time delay in WTs' controllers, it is difficult for WTs alone to meet the r...
With the development of Internet of Things (IoT) and big data technology, the data value is increasingly explored in multiple practical scenarios, including electricity transactions. However, the isolation of IoT data among several entities makes it difficult to achieve optimal allocation of data resources and convert data resources into real econo...
Automation, sharing, and electrification will be the important development trend for automobile and transportation systems in the future and will have a profound impact on the energy system. With the population of electrified autonomous mobility-on-demand systems in future cities, the charging loads of shared electric vehicles will be an important...
Uncertainty is ubiquitous in power systems, and it will probably harm the stability of power systems. However, the uncertainty should be quantized to better understand and avoid its negative effect. To quantize the uncertainty, electricity transactions are selected as the main scenario for further research, because the uncertainty is highly relevan...
Big data has been advocated as a dominant driving force to unleash the great waves of the next-generation industrial revolution. While the ever-increasing proliferation of heterogeneous data contributes to a more sustainable energy system, considerable challenges remain for breaking down the barrier of data sharing across monopolistic sectors and f...
Transmission interface power flow adjustment is a critical measure to ensure the security and economy operation of power systems. However, conventional model-based adjustment schemes are limited by the increasing variations and uncertainties occur in power systems, where the adjustment problems of different transmission interfaces are often treated...
The aggregation of electric vehicles (EVs) has been advocated as an effective means to manage and control large-scale plug-in EVs. However, the efficient aggregation is challenging due to the heterogeneity and uncertainty of individual EVs. To cope with this challenge, this paper puts forth a fast polytope-based aggregation approach, which could de...
The traffic network (TN) and the power distribution network (PDN) are major contributors to urban carbon emissions. The prevalence of electric vehicles interconnects the two networks, which leads to the emergence of a vehicle-traffic-power nexus. This physical interdependency compromises the traditional separative scheduling method, where price sig...
This paper concerns the pricing strategy for real-time distribution network congestion management, aiming at maximizing the total social welfare while eliminating congestion. The difficulty lies in dealing with the complex time-varying relationship between price and charging demand in the integrated power system and transportation network, and ensu...
With more energy networks being interconnected to form integrated energy systems (IESs), the optimal energy flow (OEF) problem has drawn increasing attention. Extant studies on OEF models mostly utilize the finite difference method (FDM) to address partial-differential-equation (PDE) constraints related to the dynamics in natural gas networks (NGNs...
With the increasing development of smart grid, multi-party cooperative computation between several entities has become a typical characteristic of modern energy systems. Traditionally, data exchange among parties is inevitable, rendering how to complete multiparty collaborative optimization without exposing any private information a critical issue....
Recently, the ever-increasing development of distributed energy resources has created new opportunities for active distribution networks. In particular, peer-to-peer (P2P) energy management systems facilitate the coordination of prosumers for higher efficiency and flexibility. However, in distributed P2P energy management problems, Byzantine attack...
In this paper, a day-ahead optimal scheduling strategy for the DSO based on EV aggregation is proposed. Generally, the uncertain parameters of EVs,
i.e.
, arrival and departure times as well as the charging demands, can be effectively modeled by a Gaussian mixture model (GMM) with historical charging records. The empirical data of net load error,...
An in-depth analysis of linearized branch flow (LBF) model considering current injection and absolute value of impedance is proposed in this paper. The form of LBF model is based on two equations: the current injection to meet KCL and the voltage drop to meet KVL. By representing the absolute value of complex load power with the current injection,...
The optimal dispatch of electric vehicles (EVs) aims to minimize the system operation cost while satisfying the requirements for peak shaving, congestion management and voltage regulation. However, the stochastic mobility of EVs makes dispatch difficult and requires modeling the spatial and temporal distribution of EV availability. In this paper, a...
Preventive transient stability control is an effective measure for the power system to withstand high-probability severe contingencies. It is mathematically an optimal power flow problem with transient stability constraints. Due to the constraints involved the differential algebraic equations of transient stability, it is difficult and time-consumi...
With the increasing development of smart grid, multiparty cooperative computation between several entities has become a typical characteristic of modern energy systems. Traditionally, data exchange among parties is inevitable, rendering how to complete multiparty collaborative optimization without exposing any private information a critical issue....
With the increasing development of smart grid, multiparty cooperative computation between several entities has become a typical characteristic of modern energy systems. Traditionally, data exchange among parties is inevitable, rendering how to complete multiparty collaborative optimization without exposing any private information a critical issue....
Deep learning is considered to be a promising method for total transfer capability (TTC) evaluation due to its high speed and accuracy for nonlinear and complicated problems. However, the operating scenarios of power systems are complex and ever changing. It is difficult to train a single deep model using an overly complex dataset containing operat...
Owing to the potential higher energy supply efficiency and operation flexibility, integrated energy system (IES), which usually includes electric power, gas and heating/cooling systems, is considered as one of the primary forms of energy carrier in the future. However, with the increasing complexity of multiple energy devices and systems integratio...
Large‐scale fast charging of electric vehicles inextricably entwines the operation of power and transportation systems. This study examines the integrated pricing of electricity and roads to maximise the social welfare associated with the coupled systems, i.e. minimising the total travel time and energy generation costs. While electric demand and t...
The increasing penetration of electric vehicles is tightly coupling the operation of power and transportation systems. The representation of the dynamics of network flows in response to real-time information and control strategies is a problem of considerable practical significance. However, most of work considers static network models that are onl...
The increasing deployment of fast charging infrastructure is coupling the operation of power and transportation systems. However, how to evaluate the coupling relationship between these two systems is less studied. This study proposes a look-ahead decentralised framework to solve the integrated power-traffic flow problem using the optimality condit...
Using thermal inertia in district heating systems (DHSs) to improve the dispatch flexibility and economy of integrated heat and electricity systems (IHESs) is a research hotspot and difficulty. In most existing studies, the partial differential equations (PDEs) of thermal inertia are approximated by discrete-time models, making it difficult to accu...
Using thermal inertia in district heating systems (DHSs) to improve the dispatch flexibility and economy of integrated heat and electricity systems (IHESs) is a research hotspot and difficulty. In most existing studies, the partial differential equations (PDEs) of thermal inertia are approximated by discrete-time models, making it difficult to accu...
The increasing number of gas-fired units has significantly intensified the coupling between power and gas networks. Traditionally, the nonlinearity and nonconvexity in gas flow equations, together with renewable-induced stochasticity, result in a computationally expensive model for unit commitment in electricity-gas coupled integrated energy system...
The installation of combined heat and power (CHP) units has rapidly increased due to their energy efficiency and environmental advantages. The broad application of CHP units requires the joint dispatch of power and heating systems, in which the modeling of CHP units plays a pivotal role. However, existing CHP models face the contradiction between a...
Massive adoptions of combined heat and power (CHP) units necessitate the coordinated operation of power system and district heating system (DHS). Exploiting the reconfigurable property of district heating networks (DHNs) provides a cost-effective solution to enhance the flexibility of the power system by redistributing heat loads in DHS. In this pa...
The problem of optimal planning of plug-in electric vehicle (PEV) charging stations is studied. Different from many other works, we assume the station investor to be a new private entrant into the market who intends to maximize its own profit in a competitive environment. A modified Huff gravity-based model is adopted to describe the probabilistic...
Increasing number of drivers are switching to electric vehicles (EV) for higher efficiency, lower environmental impact and less maintenance cost. To promote the EV revolution, charging issues of EVs needs to be well addressed. Since the traffic flow of the transportation network and the operating conditions of the power systems are time-varying, it...
This paper establishes a systematic framework to analyze the joint charging and routing behavior of electric vehicles (EVs) and how they affect both the power and transportation systems. Fast charging enables EVs to recharge at public charging stations during a trip, thereby redistributing the charging load and traffic flow at the same time. Findin...
As a newly-emerged intangible asset, information plays an important role in more and more fields and environments, and its value is increasingly analyzed and explored. In the power industry, there are severe uncertainties in electric load, output power and electricity market price, which may lead to economic loss of corresponding market entities. T...
In this paper, we review the emerging challenges and research opportunities for voltage control in smart grids. For transmission grids, the voltage control for accommodating wind and solar power, fault-induced delayed voltage recovery (FIDVR), and measurement-based Thévenin equivalent for voltage stability analysis are reviewed. For distribution gr...
As an intangible asset, data contain profound value. However, unlike common commodities, the value of data is unpredictable before purchase and use. Before data are used, analyzed and exploited, it is difficult to evaluate the data value accurately. This hinders the data’s potential of value realization. In order to evaluate the value of data and l...
Power system security assessment is an important and challenging problem. Large variations in loads and power generation present increased risks to the secure operation of power systems. This study proposes a distributed deep network structure for power system security knowledge discovery based on multitask learning to monitor and control power gri...
Coupling between electricity systems and heating systems are becoming stronger, leading to more flexible and more complex interactions between these systems. The operation of integrated energy systems is greatly affected, especially when security is concerned. Steady-state analysis methods have been widely studied in recent research, which is far f...
With the technological advancement in the fields of advanced metering infrastructure (AMI), a massive amount of customers’
electricity consumption data is collected. Meanwhile, the energy providers need to make informed decisions based on power
consumption strategy of demand side to reduce overall operational cost. So how to generate demand side lo...
With the rapid increase in the proportion of natural gas for power generation, the operations of the power system are increasingly relevant to the supply of natural gas. To improve the reliability of power generation, some additional gas storage equipment should be set up in gas power plants. This paper considered different constraints, objective f...
Considering the capacitor banks and on-load tap changer (OLTC) applied in the voltage-source-converter-based high-voltage direct-current (VSC-HVDC) systems with large-scale wind farm integration, this study presents a day-ahead voltage scheduling method to avoid frequent adjustment of the slow discrete devices. Using this method, the AC side voltag...
Power systems depend on discrete devices, such as shunt capacitors/reactors and on-load tap changers, for their long-term reliability. In transmission systems that contain large wind farms, we must take into account the uncertainties in wind power generation when deciding when to operate these devices. In this paper, we describe a method to schedul...
With the deregulation of power industry, large power users can buy electricity directly from power producers. For trades between different regional markets, it is necessary to research on the method to find the cheapest route for power exchanging. Moreover, as there exists no coordinator above regional markets, the power routing problem must be sol...
Accommodating greater levels of penetration of renewable energy sources is an important feature of smart grids. Currently, wind energy is one of the most popular and promise renewable energy sources, and significant wind power integration
has already been achieved in electricity grids in a number of countries across the globe.
With the growing application of electric vehicles (EVs), it is of great significance to have a deep understanding of EV users driving and charging patterns for charging forecasting. However, the rapid growth scale of EV taxis with charging patterns that are closely coupled with human behaviours of temporal-spatial charging choices was not compatibl...
Power plants in the competitive market will face volatile generation cost and volatile spot price, and risk management will become crucial. We address quantity risk faced by power plants with quadratic cost, which produce electricity with variable cost and sell it at spot price. By innovatively modifying existing models that provide optimal quantit...
Large-scale wind power centralized integration is the major way of wind energy utilization in China. With the increasing scale of wind power integration, voltage security and active power loss of wind farms can't be ignored, thus it is essential to realize economical operation inside wind farms in security. Considering the typical radial feeder net...
Citations
... The system operator uses unit commitment models prepared with information prior to the effective operating day. Unit commitment allows the mitigation of demand deviations, frequency variations due to the uncertainty of renewable generation and other externalities such as generation restrictions due to high emissions from fossil fuel power plants [2,3]. The problem for the system operator is the real-time operation where mismatch scenarios occur in the generation, transmission, and demand system that are not foreseen in the unit commitment model, leaving the unit commitment model expired and unable to support the system operator s decisions. ...
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... An effective charging pricing strategy should aim to achieve four objectives, namely, guiding EV users to charge in an orderly manner, increasing the profits of operators, improving the utilization rate of charging piles, and reducing the load peak-valley difference (Yang et al., 2021;Zhou et al., 2022). Considering the willingness of the users (CA et al., 2022;Khan et al., 2022), the demand-side response (Shinde and Shanti, 2018;Lai et al., 2023), and the complex time-varying relationship between the charging price and charging demand Yang et al., 2023), various models have been proposed to formulate a real-time pricing strategy. However, the existing literature often neglects the impact of a dynamic charging price on the market division, resulting in no changes in service scope. ...
... A virtual power plant (VPP) is a system that uses information technology to aggregate and coordinate resources such as distributed generators, energy storage, and interruptible load to enhance the stability and security of the power grid. The global energy system is accelerating its transition to renewable energy (Zhong et al., 2023a;Sarantakos et al., 2023;Wang et al., 2023). As a crucial energy structure for the future, multi-energy flow systems have the capacity to interconnect different types of energy (electricity, heat, gas, etc.); unify the planning, operation, and dispatch of various energy devices; and achieve efficient energy utilization (Chen et al., 2020;Wang et al., 2020). ...
... However, the widespread adoption of PVs has introduced greater variability and intermittency in power generation, thereby exacerbating the voltage fluctuations and posing challenges to the reliability and stability of power systems [9]. Thus, modern PDNs necessitate advanced Active Voltage Control (AVC) schemes that can dynamically adapt to rapid changes in PV generation and load conditions, ensuring voltage profiles within permissible limits using the controllable apparatuses (e.g., PV inverters and static var compensators) [3,18,30]. ...
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... The advent of self-driving vehicles promises to revolutionize sustainable urban transportation systems [10][11][12], yet it also carries the risk of undermining the efficacy and 1. ...
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... This data-driven approach offers high efficiency in calculating an approximated aggregate flexibility set, however the method here does not have theoretical probabilistic guarantees. In [9] the uncertainties of EVs are modelled under a distributionally robust joint chance-constrained programming framework. However, the uncertainty set constructed there is not tight due to strict constraints on expectation and variance and their use of inner approximations in the nonstochastic setting. ...
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... The online centralized scheduling system can well cope with the dynamic changes in real situations, but it is difficult to achieve good performance in large-scale charging scenarios. [23] proposes a bi-level optimization framework to maximize the charging revenue of MCSs. The upper level mainly solves the routing problem for MCSs, and the lower level mainly solves the scheduling problem of the energy service stations. ...
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... In the smart energy grid, smart metering devices and the prospect of small-scale renewable integration generate data processing and decisionmaking challenges for ensuring security in energy delivery and balancing the demand with the supply [2]. By connecting many IoT devices, a large quantity of data are fed and need to be considered in energy management processes that may be controlled and coordinated from a central location in the cloud [3]. ...
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... Study [25] proposes a fully distributed OPF algorithm based on partially homomorphic encryption. In [26], a fully distributed algorithm based on secret sharing preserves privacy in multiarea economic dispatch. However, these studies assume that participants honestly follow the proposed algorithms, which brings limitations in practice. ...
... However, the intermittency of renewable energy resources (RESs) and uncoordinated energy consumptions might impose negative impacts on the stable operation of ADNs. One promising way to address this problem is to apply coordinated charging of electric vehicles (EVs) [4]. ...
