为应对化石燃料日益短缺问题和全球气候变化带来的一系列威胁，实现“双碳”目标，风电、光伏等可再生能源在电网中的接入比例不断提高。然而，可再生能源发电具有随机性和不可控性，且接入位置分散，增加了电力系统安全稳定运行的难度。虚拟电厂(virtual power plant，VPP)的提出为上述问题提供了可行路径。总结并阐述了虚拟电厂的概念、分类，比较了虚拟电厂与微电网的主要区别，分别从协调控制、资源聚合与优化调度、参与电力市场等角度对现有研究进行分析并总结归纳，进一步以区块链、数字孪生技术为例，分析数字技术在虚拟电厂中的应用，最后指出适合我国国情的虚拟电厂发展前景以及未来可能面临的挑战。

In order to cope with the increasing shortage of fossil fuels and a series of threats brought by global climate change, and achieve the goal of “dual carbon”, the proportion of renewable energy such as wind power and photovoltaic power in the grid has been continuously increased. However, the renewable energy power generation is random and uncontrollable, and the access location is scattered, which increases the difficulty of safe and stable operation of the power system. The introduction of virtual power plant (VPP)provides a feasible path for the above problems. The concept and classification of VPP was summarized and expounded. Moreover, the main differences between VPP and microgrid were compared. The existing researches from the perspectives of coordinated control, resource aggregation and optimal scheduling, and participation in the electricity market were analyzed and summarized. Taking the blockchain and digital twin technologies as examples, the applications of digital technologies in VPP were analyzed. Finally, the development prospects of VPP suitable for China’s national conditions and the challenges that may be faced in the future were pointed out.

随着大量分布式能源接入电网，虚拟电厂作为一种分布式能源管理技术，因其灵活性、高效性和可持续性而受到了广泛关注。首先简述了虚拟电厂的产生背景，分析了虚拟电厂中的研究热点和新兴方向，介绍了虚拟电厂的组成与结构。并进一步根据虚拟电厂调节目标和功能的不同，将其分为任务驱动型虚拟电厂、经济驱动型虚拟电厂和混合驱动型虚拟电厂。在此基础上，进一步论述了不同类型虚拟电厂的不同运行模式及其相应的关键技术。最后，展望了虚拟电厂未来的发展前景。

With a large number of distributed energy resources connected to the grid,virtual power plants as a distributed energy management technology have received a lot of attention because of their flexibility,efficiency and sustainability. This paper briefly discussed the background of virtual power plants, analyzed the hot directions and emerging directions in virtual power plants,and introduced the composition and structure of virtual power plants. According to the different goals and functions of virtual power plants,virtual power plants can be divided into mission-driven virtual power plants, economy-driven virtual power plants and hybrid driven virtual power plants. On this basis, the different operation modes and different solution methods of different types of virtual power plants were further discussed. Finally,the future development prospects of virtual power plants were prospected.

碳交易机制下，虚拟电厂(virtual power plant，VPP)聚合分布式能源(distributed energy resource，DER)参与电力市场(electricity market，EM)交易有助于新能源消纳与提升环境效益。为此，首先，构建风电、光伏、可控分布式电源、储能及柔性负荷的多主体VPP模型，并制定各主体参与电能量市场(electric energy market，EEM)和调峰市场(peak regulating market，PRM)竞标策略。通过EEM及PRM算例展现了VPP参与调峰竞标实现VPP效益最大化及各DER成员利益的合理分配。其次，引入碳交易机制，分析碳交易价格变化与风光消纳率、碳排放量及VPP收益之间的关联性。最后，进一步探索碳汇资源交易对电力价格、产量及能源需求变化率的影响，为碳汇价值的生态保护补偿机制提供依据，也为电-碳市场协同下碳市场(carbon market，CM)对EM的价格传导效应及CM价格机制的优化设计提供参考。

Under the carbon trading mechanism, virtual power plants (VPP) aggregating distributed energy resource (DER) to participate in electricity market (EM) trading will help new energy consumption and improve environmental benefits. This paper constructed a multi-agent VPP model including wind turbine, photovoltaic power, controllable distribution generation, stored energy, and flexible load, and formulated bidding strategies for each entity participating in the electric energy market (EEM) and peak regulating market (PRM). The EEM and PRM examples showed that participating in peak regulating bidding by VPP could achieve the maximum benefits of VPP and reasonable distribution of the interests among DER members. Moreover, this paper introduced the carbon trading mechanism, analyzed the correlation between changes in carbon trading price and wind and solar consumption rate, carbon emissions and VPP benefits, and further explored the impact of carbon sink resource trading on electricity price, output and energy demand change rate. It provided a basis for the ecological protection compensation mechanism of carbon sink value, and also provided a reference for the price transmission effect of carbon market (CM) on EM under the coordination of electricity-carbon market and the optimization design of CM price mechanism.

针对三北地区现有能源结构调节能力不足而导致的弃风问题,将风电场、光热电站、火电机组和热电联产机组聚合为虚拟电厂。采用随机优化处理风光不确定性问题,通过拉丁超立方抽样生成大量随机风光场景,并在充分考虑风光相关性和分布随机特性的基础上,利用Kantorovich距离削减与K-均值聚类算法对随机场景进行降维优化,获得风电、太阳直接辐照度典型预测场景。结合光热电站的灵活性与供能惯性,构建含光热虚拟电厂热电联合优化调度模型,并建立系统总运行成本最小的目标函数。最后在算例部分验证所提随机优化方法在计算效率、预测精度和处理风光随机问题的优越性;对不同运行模式下的目标函数进行求解,验证所提出的优化调度策略能够在满足系统运行经济性的同时实现风电的最大消纳。

Aiming at the problem of wind curtailment caused by the energy structure lacked the adjustment ability in the three north area, this paper aggregated wind farm, concentrating solar power plant（CSPP）, thermal power units and combined heat and power（CHP） plant into virtual power plant（VPP）. Using stochastic optimization to deal with the uncertainty of wind-solar, Latin hypercube sampling （LHS） was used to generated a large number of random scenes, and based on considering the random characteristics and correlation of wind-solar distribution fully,Kantorovich distance reduction and <em>K</em>-means clustering algorithm were used to optimized and reduced the dimension of random scenes, for obtaining typical prediction wind-solar scenes. Combined with the flexibility and energy supply inertia of CSPP, the optimal dispatching model of the VPP contained photothermal was constructed, and the objective function of minimizing the total operation cost of the system was established. Finally, an example was given to verify the superiority of the proposed stochastic optimization method in computational efficiency and prediction accuracy; The objective functions under different operation scenarios were solved to verify that the optimal dispatching model could improve the wind power consumption capacity while reducing the system operation cost effectively.

针对考虑碳捕集的虚拟电厂-电制氢多主体能源系统的协调优化问题,建立基于纳什谈判理论的虚拟电厂-电制氢多主体合作运行模型。首先将难以求解的原纳什模型等效为合作运行收益最大化和电能交易支付两个子问题模型;然后采用改进的交替方向乘子法（ADMM）对子问题模型进行优化求解,加快算法收敛速度,保护各谈判主体隐私。算例仿真结果表明：聚合的碳捕集单元促进可再生能源消纳,减少碳排放;通过虚拟电厂-电制氢多主体的合作运行,可较大幅度提高各主体的运行收益以及联合合作的整体收益,验证了所建模型以及改进算法的有效性和优越性。

Aiming at the coordination and optimization of VPPS-P2H multi-agent energy system considering carbon capture, a VPPS-P2H multi-agent cooperative operation model is proposed based on Nash negotiation theory. In view of the difficulty of solving the optimization model directly, the original Nash model is broken down into two equivalent subproblems： the maximization of cooperative operation income and the payment of electric energy transaction. In order to protect the privacy of each negotiation subject and accelerate the convergence speed of the algorithm, the improved alternating direction method of multipliers （alternating direction method of multipliers,ADMM） is used to optimize the subproblems. The simulation results show that through the cooperative operation of VPPS-P2H multi-agent, the operation income of each agent and the overall income of joint cooperation can be greatly improved, which verifies the effectiveness and superiority of the proposed cooperative operation model and the improved algorithm.

随着新能源规模的不断扩大以及各种资本进入电力市场，未来电网运行将呈现出多虚拟电厂(virtual power plant，VPP)相互合作并竞争的博弈格局。为解决电网优化运行和市场主体利益分配问题，本工作提出了基于纳什谈判的多能VPP间协同优化运行模型。首先，针对包含燃气轮机、热泵、多种储能装置、电热冷负荷等的多能VPP，构建基于纳什谈判理论的多能VPP群优化运行模型；其次，为解决复杂非凸非线性优化的求解问题，依据均值不等式将模型转化为多能VPP效益最大化和多能VPP间电能支付值两个子问题；再次，考虑到各VPP间信息隐私安全，采用交替方向乘子法(alternating direction method of multipliers，ADMM)对上述两个子问题进行分布式求解。本工作选取了三个多能VPP进行算例分析，结果表明本工作提出的优化方法可以实现在兼顾公平性的前提下提升各VPP的收益和整体收益。

Multiple virtual power plants (VPP) will cooperate and compete with each other in the operation of the future power grid because of the constant growth of the scale of new energy sources and the entry of diverse capitals into the power market. A collaborative optimal operation model between multi-energy VPPs based on the Nash bargaining theory is proposed to solve the problem of optimal power grid operation and market players' interest distribution. First, for the multi-energy VPP, including the gas turbine, heat pump, various energy storage devices, electric load, thermal load, cooling load, etc., a multi-energy VPP group optimization operation model based on Nash negotiation theory is constructed. Second, to solve the complex non-convex nonlinear optimization problem, based on the mean value inequality, the model is transformed into two sub-problems of multi-energy VPP benefit maximization and energy payment value between multi-energy VPPs. Third, considering the information privacy and security between VPPs, the alternating direction method of multipliers (ADMM) is employed to solve the above two sub-problems in a distributed manner. Three multi-energy VPPs were selected for this study's example analysis. The results show that when fairness is considered, the optimization method proposed in this study can improve both the income and overall income of each VPP.