随着我国能源结构逐步低碳转型，风、光等新能源的并网比例将不断扩大，为满足未来新能源装机容量规划的同时保证电力系统的安全可靠运行，在电力系统中需要具备相应调节能力的灵活性资源。为此，提出一种计及时空响应特性的多类型灵活性资源配置优化模型。首先，建立基于空间响应特性和时间响应特性的灵活性评价模型，并构造灵活性平均缺额和灵活性覆盖指数的灵活性评价指标，分别用于电力系统灵活性不足节点筛选和各节点的灵活性充裕性分析。然后，分析多类型灵活性资源的调节特性，建立多类型调节能力模型。最后，考虑时间灵活性评价指标约束，构建灵活性资源两阶段配置优化模型，基于灵活性资源与新能源波动特性的多尺度匹配特性，指导各灵活性不足节点的灵活性资源配置，并以IEEE 9节点系统验证了所提灵活性资源配置方法的有效性和适用性。

As China is gradually transitioning towards a low-carbon energy structure, the proportion of new grid-connected energy sources, such as wind and solar power, continues to increase. To ensure the safe and reliable operation of the power system and meet the capacity planning for future new energy installations, flexible resources are required with corresponding adjustment capabilities in the power system. To this end, this study presents an optimization model for the allocation of multiple types of flexible resources, considering spatiotemporal response characteristics. First, a flexibility assessment model was developed based on the spatial and temporal response characteristics, constructing flexibility evaluation indices such as flexibility average deficit and flexibility coverage index. These indices are used to screen nodes with inadequate flexibility in the power system and analyze the flexibility adequacy at various nodes. Next, the adjustment characteristics of multiple types of flexible resources were analyzed, and a model was established to determine adjustment capabilities. Finally, by considering constraints based on time flexibility evaluation indices, a two-stage optimization model for flexible resource allocation was constructed. This model leverages the multiscale matching characteristics between flexible resources and fluctuation patterns of new energy sources, to guide the allocation of flexible resources to nodes with insufficient flexibility. The effectiveness and applicability of the proposed flexible resource allocation method were validated using the IEEE 9-node system.

风电和光伏的高渗透率增加了新型电力系统对灵活性资源需求.虚拟电厂作为一个特殊电厂聚合了可控分布式电源、新能源、储能、碳处理、负荷等各类资源,“对内协同”可以实现内部资源协同调控,“对外统一”可以参与外部电碳市场获利.基于此,本文创新地提出了虚拟电厂参与电碳多类市场分布鲁棒优化模型.为了刻画风电和光伏的不确定性,构造了基于Wasserstein距离的分布模糊集和基于数据驱动的误差不确定集.为了兼顾经济性和鲁棒性,考虑内部运行成本以及外部参与多类市场收益,构建了最坏分布下期望收益最大的两阶段鲁棒优化模型,并提出模型求解方法.为了保证联盟动态平衡,提出了多层利益分配方法.最后,算例分析表明:在“对内协同,对外统一”的经营模式下,有效激发虚拟电厂内各类资源的潜力,参与多个市场后获取共享利益,实现了多方互利共赢.所提模型具有数据驱动、快速求解、灵活可控、经济实用等优越性.多层利益分配方法能够简便、有效地将共享效益传导至各主体.

基于低碳电力和智能电网的背景,考虑现有的风电消纳困境,该文以绿色电力证书为基础,结合碳排放权的交易制度,同时引入需求侧高载能企业负荷的响应模型,并将虚拟电厂经济效益作为优化目标函数,建立以绿证交易为基础,结合碳交易制度和高载能需求侧响应的“源-荷”双侧互补协调优化调度模型。最后将某省份区域电网代入到该文所构建模型之中进行仿真,并采用自适应免疫疫苗算法对模型进行求解,结果表明所建立的计及绿证交易与碳交易的模型有利于促进风电消耗,降低单位发电量的碳排放。

Under the background of low-carbon power and smart grid,considering the existing dilemma of wind power consumption,based on the Green Power Certificate and carbon emission trading system, at the same time introducing the response model of the demand side high capacity energy enterprise load,and taking the economic benefit of the virtual power plant as the optimization objective function, a “source-load” dual-side complementary coordinated optimal dispatch model is established. And then,the regional power grid of a province is substituted into the model constructed in this paper for simulation. Finally, the model is solved using advanced adaptive immune vaccine algorithm. The results show that the established model taking into account green certificate trading and carbon trading is beneficial to improve wind power utilization and reduce carbon emission per unit of electricity generation.

为发挥分布式能源的供能潜力,文章重点研究热电联合虚拟电厂(virtual power plant,VPP)的调度优化问题。首先,将热电联产(combined heat and power, CHP)机组与各种分布式能源聚合为热电联合虚拟电厂,通过碳捕集和电转气装置来实现CO₂的循环利用,并加入储碳和储氢装置来解耦碳捕集和电转气过程。然后,通过不确定性场景生成和条件风险价值(conditional value at risk, CVaR)理论来量化虚拟电厂实时调度的风险。最后,以运行成本、碳排放量和运行风险为目标,构建虚拟电厂多目标随机调度优化模型,并采用主客观集成赋权的方法进行求解。算例结果表明,所提方法能促进风电和光伏的消纳,同时降低虚拟电厂的碳排放。

To determine the energy supply potential of distributed energy resources, this study focuses on the dispatching optimization of combined heat and power virtual power plants (VPP). First, combined heat and power (CHP) units and various distributed energy sources were integrated into a combined heat and power virtual power plant. Carbon capture and power-to-gas devices were also introduced to realize the recycling utilization of CO₂. Further, carbon and hydrogen storage devices are added to decouple the carbon capture and electro-gas conversion processes. Then, through un-certainty scenario generation and conditional value-at-risk (CVaR) theory, the risks in virtual power plant real-time dispatching are qualified. Finally, with operating cost, carbon emissions, and operating risk as the objectives, a multi-objective stochastic optimization model of a virtual power plant is constructed and solved using a subjective and objective integrated weighting method. The example results demonstrate that the proposed method can promote the consumption of wind and photovoltaic power, besides reduce the carbon emissions of power plants.

综合能源系统是实现“双碳”目标的有效途径,为进一步挖掘其需求侧可调节潜力对碳减排的作用,提出了一种碳交易机制下考虑需求响应的综合能源系统优化运行模型。首先,根据负荷响应特性将需求响应分为价格型和替代型2类,分别建立了基于价格弹性矩阵的价格型需求响应模型,及考虑用能侧电能和热能相互转换的替代型需求响应模型;其次,采用基准线法为系统无偿分配碳排放配额,并考虑燃气轮机和燃气锅炉的实际碳排放量,构建一种面向综合能源系统的碳交易机制;最后,以购能成本、碳交易成本及运维成本之和最小为目标函数,建立综合能源系统低碳优化运行模型,并通过4类典型场景对所提模型的有效性进行了验证。通过对需求响应灵敏度、燃气轮机热分配比例和不同碳交易价格下系统的运行状态分析发现,合理分配价格型和替代型需求响应及燃气轮机产热比例有利于提高系统运行经济性,制定合理的碳交易价格可以实现系统经济性和低碳性协同。

The integrated energy system (IES) is an effective way to achieve the“carbon neutrality and emission peak”goal. In order to further explore the role of the adjustable potential of demand side on carbon emission reduction, an optimized operation model of IES considering the demand response under the carbon trading mechanism is proposed. Firstly, according to the characteristics of load response, the demand response is divided into two types: price-type and substitution-type. The price-type demand response model is established on the basis of price elasticity matrix, and the substitution-type demand response model is constructed by considering the conversion of electricity and heat. Secondly, base-line method is used to allocate free carbon emission quota for the system, and considering the actual carbon emissions of gas turbine and gas boiler, a carbon trading mechanism for the IES is constructed. Finally, a low-carbon optimal operation model of IES is established, whose objective is to minimize the sum cost of energy purchase, cost of carbon transaction and cost of IES operation and maintenance. The effectiveness of the proposed model is verified through four typical scenarios. By analyzing the sensitivity of demand response, heat distribution ratio of gas turbine and the operating state of the system under different carbon trading prices, it is found that reasonable allocation of price-type and substitution-type demand response and heat production ratio of gas turbine is beneficial to improve the operating economy of the system. Making reasonable carbon trading price can realize the coordination of system economy and low carbon.

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.