Yue Xiang

• Doctor of Electrical Engineering
• Professor at Sichuan University

Optimal planning for the park integrated energy system (PIES) is essential for energy efficiency improvement and carbon neutrality. A reasonable evaluation method is the key to guide PIES planning. However, indicators for the PIES planning schemes are various with high penetration of renewable energy, large carbon emissions and multiple energy form...

To understand the charging behavior of electric vehicle (EV) users and the sustainable use of the flexibility resources of EV, EV charging behavior analysis and load prediction via order data of charging stations was proposed. The user probability distribution model is established from the characteristic dimensions of EV charging initial time, init...

This paper introduces a method for modeling the entire aggregated electric vehicle (EV) charging process and analyzing its dispatchable capabilities. The methodology involves developing a model for aggregated EV charging at the charging station level, estimating its physical dispatchable capability, determining its economic dispatchable capability...

This review studies the cascading impacts of extreme weather events on the Water-Energy-Carbon (WEC) Nexus, with a focus on their combined and sequential effects. It synthesizes research on how droughts, floods, heat�waves, hurricanes, and wildfires each initiate a chain reaction within the interconnected domains of water, energy, and carbon. Key...

Transportation electrification emerges as a pivotal strategy to realize deep decarbonization for many countries, and the central part of this is battery. However, a key challenge often overlooked is the impact of battery aging on the economy and longevity of electric vehicles (EVs). To address this issue, the paper proposes a novel battery full-lif...

To enhance the practical consistency and interpretability of deep learning approaches in power flow (PF) calculation, this paper proposes a virtual graph constrained message passing neural network (VGC-MPNN) for PF analysis, which defines a virtual graph from the mathematical expression of variables to enhance the binding force of power flow equati...

Compared to load forecasting at the national level, two challenges arise in providing accurate forecasting for LV and MV networks: (1) customers within LV and MV networks are much less, implying greater volatility within those load profiles; (2) not all customers have smart metres. Particularly, the two challenges would exacerbate forecasting perfo...

The carbon pricing is the main issue of the carbon trading market for enabling cost-effective decarbonization in the energy networks. A nodal carbon pricing model is firstly proposed based on the sharing and integration of the intra-regional carbon emission allowance. In this regard, the game theory is introduced to construct a multi-agent carbon e...

As a flexible resource, energy storage plays an increasingly significant role in stabilizing and supporting the power system, while providing auxiliary services. Still, the current high demand for energy storage contrasts with the fuzzy lack of market-oriented mechanisms for energy storage, the principle of market-oriented operation has not been em...

The capacity of distributed photovoltaic impacts the safe and reliable operation of the distribution feeders. The energy storage is one solution for addressing that challenge. To balance the financial viability of investing in the energy storage projects in distribution feeders with grid reliability, an optimal planning method for energy storage co...

Emerging prosumers are driving changes in the way traditional distribution systems operate. With the increase in the penetration of renewable energy, the energy management of prosumers has created new challenges. This paper proposes a novel peer-to-peer (P2P) transaction strategy for coupling distributed energy resources (DERs) and electric vehicle...

Uncertainties associated with large-scale deployment of electric vehicles (EVs) and photovoltaic (PV) pose challenges to distribution network expansion planning (DNEP). This paper proposes an optimal planning method for EV charging stations (EVCS) and distribution systems to accommodate the ever-increasing uncertainties. It is achieved by entailing...

For power systems with a high penetration of renewable energy, sufficient flexible resources such as energy storage must be combined to achieve sustainable energy development. However, in the planning of flexible resources, external societal factors can significantly change the evolution pathways of these resources. A simulation framework is urgent...

In this paper, we introduce an innovative framework for the strategic planning of electric vehicle (EV) charging infrastructure within interconnected energy-transportation networks. By harnessing the small-world network model and the advanced optimization capabilities of the Non-dominated Sorting Genetic Algorithm III (NSGA-III), we address the com...

The thermal model of dwellings is the basis for flexible energy management of smart homes, where heating load is a big part of demand. It can also be operated as virtual energy storage to enable flexibility. However, constrained by data measurements and learning methods, the accuracy of existing thermal models is unsatisfying due to time-varying di...

Decarbonisation is the key to solving the environmental pollution caused by greenhouse gases, and the development pathways of power systems are the focus of the energy transition process. In the absence of direct energy development data, a CO2 emission model of regional power system based on a collaborative method is proposed. An estimable method o...

With the emergence of distributed energy resources (DER) and prosumers in the distribution networks, the traditional centralised operation structure has transformed into the decentralised operation and transaction structure, which is regarded as the transactive energy market. Furthermore, the planning problem in the distribution network is deeply a...

The rapid digitalization of power systems has led to a significant increase in coding tasks for power engineers. This research article explores how ChatGPT, an advanced AI language model, can assist power engineers and researchers in a range of coding tasks. From simple to complex, we present three case studies to illustrate the benefits of ChatGPT...

Large-scale integration of electric vehicles (EVs) into the city system for charging will affect the operation of both traffic and distribution networks. An electric vehicle navigation and cluster dispatch model is proposed for improving the overall charging efficiency of EVs on the transportation network and increasing the voltage level of the dis...

The increasing integration of distributed resources, such as distributed generations (DGs), energy storage systems (ESSs), and flexible loads (FLs), has ushered in a new era for the active distribution system (ADS), characterized by more reliable, economical, and low-carbon. Nonetheless, with the increase in number and variety, how to realize self-...

Both the high penetration of clean energy with strong fluctuation and the complicated variable operation condition bring great challenges to the voltage regulation of the distribution network. To deal with the problem, a topology-aware voltage regulation multi-agent deep reinforcement learning (MADRL) algorithm is proposed. The distributed energy s...

With the popularization of electric vehicles (EVs) and the development of home EV charging technology, the safety and economy of electricity distribution network operations are greatly challenged. This paper first establishes a simulation method for EV charging considering the usage habits of EV owners. Subsequently, the EV hosting capacity of the...

The deployment of prosumers with distributed energy resources (DERs) has facilitated the prosumer-centric transactive market, giving rise to the consequent necessity for the coordination between prosumers and the distribution networks. This paper proposes an incentive-based expansion planning method considering virtual peer-to-peer (P2P) transactio...

At present, the distribution network investment is faced with complicated operation strategies and various new investment elements. It's difficult to evaluate the impact of different investment measures on the final benefits due to the complicated physical modeling and potential coupling correlation, which contributes to that the traditional model-...

Existing decoupled energy and carbon trading market leads to an inefficient and suboptimal operation of the distribution networks regarding economic interests and emission reduction. Corresponding to these issues, this paper designs a novel peer-to-peer (P2P) trading market of both energy and carbon emission allowance (CEA). It factors the value of...

With the high penetration of renewable energy integrated into distribution networks, distributed generators (DGs) are encouraged to participate in market competition with a “peer-to-peer” (P2P) strategy. The operation strategy of the distribution network is increasingly characterized by weak centralization and decentralization. The traditional cent...

In the era of smart grids, wireless communication technology improves the flexibility of data transmission for home appliances. Home energy management systems facilitate the maintenance and updates of hardware in the home while coordinating the direction of energy flow between photovoltaic (PV) storage and energy storage, and their various loads. T...

Greenhouse gas emission reduction represented by carbon dioxide is a topic of concern in the world. For achieving the carbon neutrality policy target, the energy transition is happening all over the world, when the power generation mix will be replaced by clean energy with carbon reduction effects. To estimate the evolution of power generation mix...

The accurate prediction of electric vehicles (EVs) load is the research basis for evaluating the impact of EVs on the power grid and optimizing the operation of the power grid. However, because the accumulated data of the newly operated EV charging stations are scarce, it is very challenging to use scarce data to obtain accurate prediction results....

Economic scheduling is an important solution to improve the operational efficiency of integrated energy system (IES). Active power is the majority being considered in economic scheduling, ignoring the influence of var-voltage effect on scheduling. In this paer, an agent-based var-voltage control (VVC) capability is developed, and integrated in the...

Constructing the power industry policy network and analyzing its structural characteristics is conducive to exploring the focus and direction of power industry policy and further improving the effectiveness of the policy. Taking the energy policy of Jiangsu Province since the 12th five-year plan as the research sample, this paper uses cite space to...

The complex energy coupling and uncertainties of renewable energy and load make the dynamic scheduling of the integrated energy system (IES) very difficult. Therefore, an optimal operation method based on the multi-agent deep deterministic policy gradient algorithm (MADDPG) is proposed. Firstly, the IES model is established, and the optimal schedul...

Massive residential power consumption information provides data support for the mining and analysis of load patterns. This paper proposes a complete framework for load pattern identification, which mainly includes the clustering module and the classification module. Considering that the high-dimensional load profiling dataset will bring a heavy com...

With the increasingly prominent fossil energy crisis and global climate governance problem, carbon abatement has attracted more attention. How to formulate a reasonable carbon-related price incentive signal to guide the low-carbon transformation is still an open question. In this paper, three different calculation models of locational electricity–c...

Environmental issues have made reducing carbon emissions a consensus among all countries. The electricity market provides a competitive environment and at the same time makes it possible to reduce the carbon emissions of the electricity system through market-oriented means. Firstly, this paper focuses on carbon-tax and cap-and-trade market policies...

The development of distributed generator (DG) and energy market has facilitated the investment in non-utility-owned DGs, leading to the necessity of decentralized optimization and finical risk management due to multiple uncertainties. To cope with these problems, this paper addresses the planning framework of non-utility-owned DGs considering multi...

The emergence of the shared energy storage mode provides a solution for promoting renewable energy utilization. However, how establishing a multi‐agent optimal operation model in dealing with benefit distribution under the shared energy storage is still a challenge. Considering the multi‐agent integrated virtual power plant (VPP) taking part in the...

With the promotion of renewable energy utilization and the trend of a low-carbon society, the real-life application of photovoltaic (PV) combined with battery energy storage systems (BESS) has thrived recently. Cost–benefit has always been regarded as one of the vital factors for motivating PV-BESS integrated energy systems investment. Therefore, g...

Clean energy is expected to enter a new stage of large-scale development along with the growing demand for building regional clean energy stations. However, as many regional clean energy stations comprise multiple stations with different output characteristics and complementary coupling, the development potential of these stations cannot be simply...

The uncertainty of wind power and electricityprice restrict the profitability of wind-storage integrated system (WSS) participating in real-time market (RTM). This paper presents a self-dispatch model for WSS based on deep reinforcement learning (DRL). The designed model is able to learn the integrated bidding and charging policy of WSS from the hi...

The quantity and heterogeneity of intelligent energy generation and consumption terminals in the smart grid are increasing drastically over the years. These edge devices have created significant pressures on cloud computing (CC) system and centralised control for data storage and processing in real-time operation and control. The integration of edg...

The wind power forecasting error restricts the benefit of the wind farm in the electricity market. Considering the cooperation of wind power bidding and energy storage system (ESS) operation with uncertainty, this paper proposes a coordinated bidding/operation model for the wind farm to improve its benefits in the electricity market. The maximum en...

An optimal energy-reserve scheduling model of wind-photovoltaic-hydrogen integrated energy systems (WPH-IES) with multi-type energy storage devices including electric, thermal and hydrogen is presented in this paper. The chance-constrained programming (CCP) theory is utilized to model the impact of renewable and load uncertainties on reserve constr...

With the rapid promotion of renewable energy technologies and the trend to a low-carbon society, the positive impacts of an integrated energy system that realizes various forms of energy-utilizing improvement and carbon reduction have fully emerged. Hydrogen with a decarbonized characteristic being integrated into the integrated energy system has b...

The energy system carbon reduction is an inevitable trend to deal with the global warming problem. The power industry, being a vital part of energy system, faces severe challenges. To decarbonize the power sectors, the implementation of low-carbon technologies and integration of high penetrated renewable power generation would be an effective solut...

Centralized optimization is widely used in generation scheduling of cascade hydropower plants to make full use of reservoir capacity. However, it is very common that the upstream and downstream plants of cascade hydropower system belong to different operators. Therefore, the problems of information privacy and profit distribution are inevitable, wh...