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.

随着分布式能源渗透率的逐步提高，虚拟电厂技术逐渐成为解决可再生能源规模化发展的关键技术，文章重点研究气电互联虚拟电厂多目标优化问题。首先，文章将风电机组、光伏发电机组、燃气轮机、电转气设备、储气装置等集成为虚拟电厂，同时联动公共网络和天然气网络，负荷侧包括电力负荷、氢气燃料电池汽车负荷、天然气负荷，并在终端负荷引入需求响应技术进行调节。然后，以运行经济效益、削峰填谷效应、二氧化碳排放作为优化目标，结合功率平衡等约束条件，构建气电互联虚拟电厂多目标模型，通过为各目标函数赋权将多目标优化模型转化为单目标模型进行求解。最后，为了验证所建立模型的有效性和可行性，选取了某地区虚拟电厂作为算例进行分析，比较4种情景下运行结果。算例结果表明：1）所提气电互联虚拟电厂多目标优化模型能够实现经济性、稳定性、环保性多方面综合效益最优；2）电转气和需求响应具有协同削峰填谷效应，提高系统运行稳定性；3）电转气设备增加了清洁能源并网量，减小碳排放量；4）虚拟电厂与公共网络相连能够实现能量间灵活互动，有利于制定合理购售电策略优化虚拟电厂运行。

With the gradual increase of distributed energy permeability, virtual power plant technology has gradually become a key technology to solve the large-scale development of renewable energy. This paper focuses on multi-objective optimization of gas-electricity interconnected virtual power plant. Firstly, this paper integrates wind power, photovoltaic power generation, convention gas turbine, power-to-gas, gas storage tank, etc. into virtual power plants. At the same time, it links the public power grid and natural gas network. The load side includes electricity load, hydrogen fuel-cell vehicle load and natural gas load. The demand response is introduced to adjust the terminal load. Then, combined with power balance and other constraints, the multi-objective model of the gas-electricity interconnected virtual power plant is constructed with the optimization objectives of economic benefit of operation, peak regulation, and carbon dioxide emission. The multi-objective optimization model is transformed into a single-objective model by weighing each objective function. Finally, in order to verify the validity and feasibility of the established model, a virtual power plant in a certain area is selected as an example to compare the operation results of four scenarios. The results show that: 1) The multi-objective optimization model of the gas-electricity interconnected virtual power plant can achieve the optimal comprehensive benefits of economy, stability and environmental protection； 2) Power-to-gas and demand response have the synergistic effect of peak regulation, which improves the stability of the system； 3) Power-to-gas increases the amount of grid-connected clean energy and reduces carbon emissions； 4) The connection between the virtual power plant and the public network enables flexible energy interaction, and the rational purchase and sale of electricity strategies can optimize operation.

虚拟电厂对推进“双碳”战略及能源优化配置具有重要意义,如何在应对源荷不确定性因素影响的同时,实现虚拟电厂低碳经济运行,是虚拟电厂调度过程中面临的重要挑战。鉴于此,提出一种考虑碳-绿证交易机制的虚拟电厂分布鲁棒低碳经济调度策略;首先,基于阶梯式碳交易机制和配额制下绿证交易机制,并利用条件风险价值(condition value at risk,CVaR)评估系统运行所面临的风险,构建考虑绿证-碳交易机制的区域虚拟电厂优化模型;其次,综合考虑1-范数和∞-范数构造概率分布模糊集,以调度系统可用的历史数据为基础,构建考虑风光不确定性的虚拟电厂两阶段分布鲁棒优化调度模型,并采用列约束生成算法求解模型;最后,算例仿真验证了所提策略的有效性和鲁棒性。

A virtual power plant (VPP) is of great significance for promoting a dual-carbon strategy and an optimal allocation of energy. Achieving low-carbon economic operation of a VPP while addressing the influence of the source-load uncertainty is a significant challenge in the scheduling process of a VPP. To this end, this study proposes a distributed robust low-carbon economic dispatch strategy for VPPs considering the green certificate-carbon trading mechanism. First, based on the ladder carbon trading and green certificate trading mechanisms under the quota system and using the conditional value-at-risk (CVaR) to evaluate the risks confronted by the system operation, a regional VPP optimization model considering the green certificate-carbon trading mechanism is established. Then, norm-1 and norm-inf are simultaneously included to establish the probability distribution fuzzy set. Based on the existing enormous historical data available in the scheduling system, a two-stage distributed robust optimal scheduling model of a VPP considering the uncertainty of wind and PV power is constructed, and the column-and-constraint generation (C&CG) algorithm is used to solve the model. Finally, case simulations are performed to verify the effectiveness and robustness of the proposed strategy.