The high percentage of renewable energy sources presents unprecedented challenges to the flexibility of power systems, and planning for the system's flexibility resources has become a necessary research area. Thus, this study constructs a flexibility quota mechanism and a two-stage model for the optimal configuration of multienergy system coupling equipment to satisfy the growing demand for flexibility in city-level electricity-gasheat-storage coupling systems. First, it examines the relationship between supply and demand for system flexibility, leading to the design of a flexibility quota mechanism. Subsequently, the power supply method for communication base stations shifts from direct networking to a hydrogen fuel cell supply. This flexibility quota mechanism encourages communication operators to actively engage in flexibility quota trading. Simultaneously, the safety constraints of heterogeneous energy-flow subsystems are considered while conducting comprehensive capacity planning for the coupling equipment of a multi-energy system. Finally, an optimisation strategy is proposed under the established capacity planning scheme for determining the siting and capacity of energy storage plants to address the potential transmission blockage risk in the power network. The case study employs the IEEE 14-bus power grid, a 7-node gas network, and an 8-node heat network test system to evaluate the optimal configuration of a city-level multi-energy coupled system model. The analysis considers four typical days to achieve this optimal configuration. By implementing a flexibility quota mechanism, the system's flexibility margin is increased by 7500 MW. Additionally, the proposed energy storage siting and capacity determination method reduces the risk of transmission congestion by 5-10 % compared to traditional methods. This approach also results in a reduction of the total cost by & YEN;2.87 million. Moreover, the integration of communication base station power supply modifications and participation in market trading further enhances system flexibility, increasing it by an additional 10,563 MW.

Aiming at the problems of new energy absorption and inter-subject interest conflict in the integrated community energy system, this study proposed an integrated energy pricing strategy that considered the interconversion of various energy sources and built a two-layer optimisation model of the electric-gas-heat‑hydrogen interconnection integrated community energy system. The upper-layer operator model maximises the revenue by setting energy price and selling energy to users. The lower-layer users model minimises the energy cost by actively adjusting energy usage strategy according to energy price. The two sides rationally pursue the maximisation of their respective interests, and the process of bargaining can be described by Stackelberg game. The model is also considered for combining the characteristics of elastic load and vehicle-to-grid on the demand side and operates jointly with the bus battery swapping station and two-stage power-to-gas for optimizing system operation. Through theoretical derivation, it is proved that there is a unique Stackelberg equilibrium solution for the proposed game model. Further, the two-layer optimisation model is transformed into a mixed integer quadratic programming problem by applying the Karush-Kuhn-Tucher optimal condition, linear relaxation technique, and duality theorem. Finally, the global optimal energy price is obtained by solving the converted model. The optimisation results in different scenarios show that the proposed model and method not only protect the interests of the operator and users but also improve the wind power absorption capacity of the community and reduce the load fluctuation.

State estimation provides a data foundation for the integrated energy management system and is the key to ensuring the safe and efficient operation of the system. The measurement frequency and accuracy on the power system side is usually higher for combined heat and power system. It is meaningful to leverage the boundary measurement further to improve state estimation accuracy on the heating network side. In this paper, we additionally combine federated learning and the Paillier cryptosystem to achieve the combined estimation with data remaining local. The proposed method demonstrates improved accuracy in the heating network state estimation through case studies while preserving privacy.

在城市综合能源系统中,热网状态估计针对慢动态系统,存在计算精度低、参数不准确、量测不完备的特点.基于物理信息神经网络(PINNs),将含偏微分方程约束的热网动态状态估计问题转化为自动满足偏微分方程约束的神经网络训练问题,并基于损失函数对参数的梯度下降完成热网参数的在线辨识;再将其应用于滚动时间窗中进行在线训练,实现了状态量的动态追踪;进一步基于PINNs对未来时间窗的预测能力提出了一种新的坏数据辨识方法;最后在5节点和27节点热网算例中验证了所提方法的有效性.

As massive distributed energy resources are connected to the distribution networks, the distribution networks are gradually transforming into active distribution networks, and the transmission and distribution networks become more coupled. To make the most of these distributed energy resources and improve the safety of the coupled power system, coordinated real-time power dispatch is indispensable. And for privacy protection and actual engineering needs, the real-time power dispatch problem should be optimized in a decentralized manner by different control centers. In this paper, we decompose the global objective function into local ones, which can be locally optimized by control centers of transmission and distribution networks. The coordination is then realized by introducing the alternating direction method of multipliers (ADMM). Based on the decomposition, we design a novel communication architecture, in which only the boundary variables are exchanged, effectively protecting private information. Additionally, in the real power system, the transmission networks have credible models, while the maintenance of accurate models for distribution networks is usually unaffordable. Therefore, this paper also proposes a hybrid real-time power dispatch method: a model-based optimization method for the transmission network and model-free deep reinforcement learning for each subordinate distribution network. This hybrid method not only overcomes the model incompleteness of the distribution networks but also accelerates and stabilizes the learning process. Numerical test results on three different cases justify the effectiveness of the proposed communication architecture and hybrid real-time power dispatch method.

In order to improve the enthusiasm of society to consume renewable energy power, in this paper, a weight allocation method of renewable energy consumption responsibility based on subjective and objective comprehensive decision-making is proposed. Based on various factors such as total electricity consumption, renewable energy consumption and profitability, this method adopts the combination of objective calculation and subjective evaluation to determine the weight index of consumption responsibility of various responsibility subjects, which provides a new realization approach and calculation basis for the allocation of consumption responsibility in provincial regions. The proposed method is verified by an example based on the registered market players of a provincial power grid.

Based on the dynamic process modeling of heat loads, this paper puts forward a flexibility evaluation method for thermal storage electric heating (TSEH) load clusters. Firstly, heat load demand model is established. Then, the heat load demand power in different periods is calculated based on the temperature data from numerical weather prediction (NWP) at different periods of the next day. A dynamic model is established for the storage state of heat storage equipment. Under a peak-valley electricity price curve, an optimization model of heating equipment operation is established. Flexibility evaluation indexes are proposed for heat storage electric heating loads, including cross-period energy shift and real-time power flexibility. These indexes can be obtained through simulation. Case studies shows that the peak-valley electricity price can guide the TSEH load to shift from the peak load period to the valley load period, which alleviates the peak regulation pressure of traditional units. The upward and downward power regulation capacity of TSEH load can provide ancillary services such as automatic generation control (AGC), reserve to the power system, which is in favor to balance the power fluctuation of new energy generation.

With increasing penetration of renewable energy, the need for system flexibility is growing. Electric heating loads, excellent demand response resources, are a profitable means to improve system operational flexibility. However, there is not yet an effective market mechanism to manage electric heating users to interact with new energy power generation enterprises. In this paper, a multi-time standard market transaction mechanism for electric heating market based on blockchain is proposed. First, considering the characteristics of each distributed entity in the market, we establish a blockchain-based architecture enabling traceability and fairness of transactions. The combination with blockchain not only enables efficient interaction, but also facilitates the credible verification by supervision department. On basis, a multi-time standard coordinated optimization model consisting of day-ahead, intra-day and real-time is developed. With respect to the distribution characteristics of participating parties, an optimal smart contract with the objective of maximizing multiple subjects' benefits is presented. Finally, the feasibility of the proposed mechanism is demonstrated by the simulation results.

Recently, wind power generation in China developed rapidly. However, its characteristics of low inertia and operating according to the maximum power tracking mode will lead to the lack of the inertia and the decline of the frequency regulation ability of the system to a certain extent. Based on the frequency response model of Doubly Fed Induction Generator (DFIG), this paper analyzes the influence of Phase Locked Loop (PLL) control parameters on the inertia response of DFIG, and evaluates the inertia characteristics of DFIG. Finally, a time-domain simulation example system is built to verify the effectiveness of the theoretical analysis.

With the rapid development of new energy and DC, new technologies such as energy storage are emerging, and the characteristics of power grids are becoming more and more complex. The traditional dispatching mode of "source following load" has been difficult to deal with this situation. Considering the characteristics of the existing domestic power grid automation and information systems, a coordinated and optimized structure of source-network-load-storage integration of power information and physical integration is proposed, and then a technical solution based on the "State Grid Cloud Platform + Data Center" system architecture is formed, and compared with the traditional smart grid-based dispatch control system function expansion plan, Pros and cons of the plan are analyzed from the three aspects of system operation safety, inputoutput ratio and system maintenance cost. Two key technologies are given for multi-dimensional aggregation model construction and ubiquitous coordination and optimization of source-networkload-storage interaction. The developed ubiquitous dispatching control system with multiple coordinated source, grid, load and storage was put into operation in the East China Electric Power Control Sub-center of State Grid. The construction cost is relatively small, the effect of renewable energy consumption is obvious, and the grid operation is safe and reliable. The scheme has important reference significance for the coordination and optimization construction of the multiple coordination of the source network.

Deepening the electric power system reform and building a new power system with new energy as the main body are the top priorities in the development of the energy and power field. The participation of new energy in electricity market transactions is in the early stage of development, and there are many problems in the mechanism design. Aiming at the problem of new energy participating in electricity market transactions, this paper summarizes and analyzes the current situation of new energy participating in the electricity markets at home and abroad, then puts forward the incentive mechanism and price mechanism of new energy participating in electricity market transactions, and finally makes some suggestions about this problem. The research objective is to better promote the participation of new energy in the electricity market, realize the efficient use of new energy, and help to achieve carbon peak and neutrality goals.

针对中国双碳目标下能源绿色低碳转型面临的重大挑战,能源互联网利用跨界思维,破除能源系统中的各种壁垒,低成本地从电力行业之外寻找潜在资源,助力构建以新能源为主体的新型电力系统.能源互联网跨界思维应用有3个维度的要素:目标维度,包含绿色、低碳、安全、高效、优质等;对象维度,包含部门之间、主体之间、行业之间的跨界;手段维度,包含能量层打破物理壁垒实现互补资源互联、信息层打破信息壁垒打造灵活协同智慧、价值层打破价值壁垒构建多方共赢生态.分析了中国已实施的若干能源互联网项目在跨界思维3个维度的要素.探讨了学术层面学科跨界交叉融合若干方向的科学问题和关键技术.

With the development of energy coupling components such as combined heat and power (CHP) units, heat pumps, and air conditioners, multi-energy systems (MES) play important roles in energy supply. Integrated operational security becomes more significant due to the complex interactions among different energy systems and huge economic and social costs of large-scale energy outages. This paper proposed concepts of integrated operational security of MES, which has new features of multi-energy coupling, multi-time scale, and multimanagement body. Interactions among systems are the causes of integrated operational security problems, and the security problems can evolve over time. Cascading failures have great impacts, and are analyzed specifically. A case study showed a cascading failure in a combined electricity and heating system.

随着能源互联网的快速发展,综合能源系统建模的准确性对其运行经济性、高效性至关重要。文章在已有设备模型基础上,考虑设备间拓扑连接和能量梯级利用关系,建立面向综合能源系统的多能网络模型;建立指数型目标函数的抗差估计模型,利用实际现场的运行数据实现设备参数的准确辨识,并对比分析提出的抗差方法相对于传统最小二乘估计方法的优势;进一步提出了基于网络模型的综合能源系统效率评价模型,通过抗差辨识得到的设备模型计算多种典型工况下的理论效率,并与现场实测效率对比,证明了所提方法的有效性以及抗差参数的准确性。

The integrated Energy System (IES) becomes very important nowadays, however, the coupling between multiple energy systems will bring new challenges to the security control of the IES, such as combined heat and power (CHP) system. The corrective control means that the operations can be adjusted after contingency happens to eliminate the constraints violation in the contingency state such as the transmission outage or generator outage. This paper proposes a corrective control approach for CHP system integrated with the energy storage system based on security constrained economic dispatch (SCED) model. Case studies based on the IEEE 9-bus CHP system are presented to verify the method. The case result shows that the energy storage device can solve the ramping of the unit's output adjustment well. The corrective control method is more scientific and economical.

Integrated Energy System (IES), which plays a vital role in the development of Energy Internet (EI), can improve the efficiency of energy utilization and integration of renewable energy. However, the coupling between multiple energy systems will bring new challenges to the security control of the IES, such as combined heat and power (CHP) system. For IES, the preventive control is the first line of defense to ensure that the system can keep stable operation when contingencies such as the transmission outage or generator outage happen. This paper proposes a preventive control approach for CHP system, in which a day-ahead security constrained economic dispatch (SCED) model of CHP system considering the coupling of heat and electric is formulated. The model aims to minimize the cost of the whole system, while the preventive control of the system can be achieved with the constraints considering the normal states and contingencies states. Case studies based on the IEEE 9-bus system with CHPs are presented to illustrate the approach. The case result shows that the combined electric and heat optimal dispatch is more economical than when two systems are independently optimized and operated. And the proposed preventive control approach of the CHP system can satisfy both the electric and heat demand, and system security is ensured when the N-1 contingencies happened.

Due to the imbalance of source-load distribution and the randomness of the output of new energy in China, the peaking pressure of power grid is increasing. And the trouble of energy development is becoming more and more prominent. Under this background, it is proposed that to participate in power grid peak-shaving by optimizing the output of units in the multi-energy complementary park. The demand for peak-adjustable auxiliary service of power grid is the target of market regulation of peak-adjustment auxiliary service. How to maximize its own interests by participating in the power grid peaking under the current power market environment. This paper proposes an optimization model of comprehensive consideration of the demand of internal load and peaking of the park. And the feasibility and accuracy of the method are verified by the actual case.