Electricity-Carbon Interactive Optimal Dispatch of Multi-Virtual Power Plant Considering Integrated Demand Response

As new power systems and dual carbon policies develop,virtual power plant cluster(VPPC)provides another reliable way to promote the efficient utilization of energy and solve environmental pollution problems.To solve the coordinated optimal operation and low-carbon economic operation problem in multi-virtual power plant,a multi-virtual power plant(VPP)electricity-carbon interaction optimal scheduling model considering integrated demand response(IDR)is proposed.Firstly,a multi-VPP electricity-carbon interaction framework is established.The interaction of electric energy and carbon quotas can realize energy complementarity,reduce energy waste and promote low-carbon operation.Secondly,in order to coordinate the multiple types of energy and load in VPPC to further achieve low-carbon operation,the IDR mechanism based on the user comprehensive satisfaction(UCS)of electricity,heat as well as hydrogen is designed,which can effectively maintain the UCS in the cluster within a relatively high range.Finally,the unit output scheme is formulated to minimize the total cost of VPPC and the model is solved using theCPLEX solver.The simulation results showthat the proposed method effectively promotes the coordinated operation among multi-VPP,increases the consumption rate of renewable energy sources and the economics of VPPC and reduces carbon emissions.

Optimized scheduling of integrated energy systems for low carbon economy considering carbon transaction costs

With the introduction of the“dual carbon”goal and the continuous promotion of low-carbon development,the integrated energy system(IES)has gradually become an effective way to save energy and reduce emissions.This study proposes a low-carbon economic optimization scheduling model for an IES that considers carbon trading costs.With the goal of minimizing the total operating cost of the IES and considering the transferable and curtailable characteristics of the electric and thermal flexible loads,an optimal scheduling model of the IES that considers the cost of carbon trading and flexible loads on the user side was established.The role of flexible loads in improving the economy of an energy system was investigated using examples,and the rationality and effectiveness of the study were verified through a comparative analysis of different scenarios.The results showed that the total cost of the system in different scenarios was reduced by 18.04%,9.1%,3.35%,and 7.03%,respectively,whereas the total carbon emissions of the system were reduced by 65.28%,20.63%,3.85%,and 18.03%,respectively,when the carbon trading cost and demand-side flexible electric and thermal load responses were considered simultaneously.Flexible electrical and thermal loads did not have the same impact on the system performance.In the analyzed case,the total cost and carbon emissions of the system when only the flexible electrical load response was considered were lower than those when only the flexible thermal load response was taken into account.Photovoltaics have an excess of carbon trading credits and can profit from selling them,whereas other devices have an excess of carbon trading and need to buy carbon credits.

Agent-Based Simulation for Interconnection-Scale Renewable Integration and Demand Response Studies

This paper collects and synthesizes the technical requirements, implementation, and validation methods for quasi-steady agent-based simulations of interconnectionscale models with particular attention to the integration of renewable generation and controllable loads. Approaches for modeling aggregated controllable loads are presented and placed in the same control and economic modeling framework as generation resources for interconnection planning studies. Model performance is examined with system parameters that are typical for an interconnection approximately the size of the Western Electricity Coordinating Council(WECC) and a control area about 1/100 the size of the system. These results are used to demonstrate and validate the methods presented.

Intelligent Agent-Based Architecture for Demand Side Management Considering Space Heating and Electric Vehicle Load

Contraction of resilience on generation side due to the introduction of inflexible renewable energy sources is demanding more elasticity on consumption side. It requires more intelligent systems to be implemented to maintain power balance in the grid and to fulfill the consumer needs. This paper is concerned about the energy balance management of the system using intelligent agent-based architecture. The idea is to limit the peak power of each individual household for different defined time regions of the day according to power production during those time regions. Monte Carlo Simulation (MCS) has been employed to study the behavior of a particular number of households for maintaining the power balance based on proposed technique to limit the peak power for each household and even individual load level. Flexibility of two major loads i.e. heating load (heat storage tank) and electric vehicle load (battery) allows us to shift the peaks on demand side proportionally with the generation in real time. Different parameters related to heating and Electric Vehicle (EV) load e.g. State of Charge (SOC), storage capacities, charging power, daily usage, peak demand hours have been studied and a technique is proposed to mitigate the imbalance of power intelligently.

Optimal operation of electricity, natural gas and heat systems considering integrated demand responses and diversified storage devices

In recent years, the increasing penetration level of renewable generation and combined heat and power(CHP) technology in power systems is leading to significant changes in energy production and consumption patterns. As a result, the integrated planning and optimal operation of a multi-carrier energy(MCE) system have aroused widespread concern for reasonable utilization of multiple energy resources and efficient accommodation of renewable energy sources. In this context, an integrated demand response(IDR) scheme is designed to coordinate the operation of power to gas(P2 G) devices, heat pumps,diversified storage devices and flexible loads within an extended modeling framework of energy hubs. Subsequently, the optimal dispatch of interconnected electricity,natural gas and heat systems is implemented considering the interactions among multiple energy carriers by utilizing the bi-level optimization method. Finally, the proposed method is demonstrated with a 4-bus multi-energy systemand a larger test case comprised of a revised IEEE 118-bus power system and a 20-bus Belgian natural gas system.

考虑含HRD的光热电站和综合需求响应的综合能源系统低碳经济调度

在“双碳”的背景下,为进一步提升综合能源系统(Integrated Energy System, IES)的经济性和环境效益,文中提出一种在奖惩阶梯型碳交易机制下考虑含热回收装置(Heat Recycling Device, HRD)的光热电站和综合需求响应的IES系统低碳经济调度方法。首先,在源侧构建含热回收装置的光热电站与加装碳捕集的热电联产机组联合运行的IES架构,并分析电转气两阶段的运行原理,建立计及余热回收的电转气设备模型。其次,考虑到负荷侧电、热、气三种负荷的柔性特性,在负荷侧建立电热气综合需求响应模型。最后,引入奖惩阶梯型碳交易机制,进一步减小系统碳排放量,构建调度周期内以含购能成本、运维成本、碳交易成本等系统总运行成本最小为目标的综合能源系统低碳优化调度模型。通过算例分析结果表明,所提方法不仅能提高机组的运行潜力,而且有效降低了系统总运行成本与碳排放量。

考虑不确定性的综合能源供应商日前优化运行策略

综合能源供应商作为多能源供应主体,可以参与市场化交易。为探索综合能源供应商在电力市场环境下新的盈利点,构建了考虑需求响应的多主体互动机制,并充分考虑光伏出力、多元用能需求、市场电价以及需求响应资源潜力的不确定性,采用区间优化方法构建了表征综合能源供应商日前运行优化问题的混合整数线性规划模型,得到综合能源供应商的购能、设备运行以及需求响应资源调用等策略。算例验证结果表明,需求响应机制可以有效降低购电成本,增加综合能源供应商的运行收益。

考虑阶梯式碳交易与电热需求响应的综合能源系统经济调度

在能源安全新战略背景下,推动可再生能源发展、降低碳排放将是未来发展趋势。为了消纳大规模风电的弃风功率以提升电网的调峰能力,首先考虑阶梯式碳交易机制,采用碳交易市场,利用碳交易价格达到控制碳排放的目的;其次基于分时电价形成用户用电舒适度与用热舒适度,构建电热负荷需求响应模型,在掌握电锅炉、储热装置和热需求可时移特性的基础上,通过风电供给价格弹性系数描述风电出力与电锅炉协议电价之间的变化;最后通过综合满意度指标评估负荷响应能力,构建了考虑需求响应和阶梯式碳交易机制的含蓄热式电锅炉综合能源系统优化调度模型,实现系统经济运行,并采用CPLEX求解器对所构建模型进行求解。结果表明所提方法能够有效促进风电消纳,减少碳排放量且有效降低系统运行成本。

考虑氢储能和需求响应的综合能源系统双层优化配置

在双碳目标下,为改善综合能源系统功率不平衡,提高能源运营商收益,降低用户购能成本,首先,结合氢储能可作为源-荷-储的优点以及电制热的能源转换特性,设计了考虑氢储能的综合能源系统双层框架。其次,根据两种不同时间尺度,提出了一种考虑负荷侧需求响应和含电制热设备用户群的综合能源系统氢储能双层优化配置模型,上层模型结合氢储能特性进行长时间尺度优化配置;下层模型利用需求响应和电制热设备对用户群负荷进行优化,以求解短时间尺度含氢储能综合能源系统优化运行问题。再次,采用KKT条件和Big-M法将模型转为单层线性问题。最后,结果显示,通过配置氢储能以及采用电制热设备和需求响应,可提高运营商收入和新能源消纳,降低用户群成本,减少功率失衡风险。

计及阶梯式碳-绿证联合交易和需求响应的生物质能综合能源系统优化

在“30·60”“双碳”目标背景下,生物质能因其储量大、污染小、可再生等优势愈发受到重视。为促进生物质能的有效应用、减少综合能源系统的碳排放量,提出一种考虑阶梯式碳-绿证联合交易机制和综合需求响应下的生物质能综合能源系统优化模型。首先,基于有机朗肯循环技术,对生物质热电联产的关键机理进行研究,构建生物质热电联产模块,同时对系统中其他设备建立数学模型;其次,将多种负荷的综合需求响应机制引入系统,实现电-热-气灵活响应;然后,在阶梯式碳交易机制与绿色证书交易机制的基础上,根据国家可再生能源政策,构建阶梯式碳-绿证联合交易机制;最后,针对6个不同场景的实际算例,从多个角度对比研究生物质成本、阶梯式碳-绿证联合交易机制和综合需求响应分别对系统规划产生的影响。算例结果表明,以生物质热电联产为核心,并考虑阶梯式碳-绿证联合交易机制和综合需求响应的综合能源系统具有良好的经济性和碳减排效果。

考虑电动汽车共享储能特性的园区综合能源系统低碳运行

园区综合能源系统拥有高效的能源利用率,然而其储能设备前期投入较高等问题仍然明显。为此,提出了计及电动汽车集群共享储能特性的园区综合能源系统低碳调度模型。首先,介绍了园区综合能源系统的运行框架,分别建立了用户及含有碳排放权交易机制的微网运营商模型。其次,充分挖掘多类型电动汽车的集群可调度潜力,制定了利用电动汽车作为储能单元的运行策略。然后,为使园区中各主体利益最大化,构建了含多用户与微网运营商的主从博弈模型。最后,以某市园区综合能源系统为研究对象进行分析。结果表明,所建立的模型不仅能降低园区中用于储能设备的成本,而且可以有效减少碳排放,实现微网运营商与用户聚合商之间的双赢。

考虑电-氢一体化的微电网低碳-经济协同优化调度

针对微电网中缺乏对碳排放流特性的精确刻画,导致运行层面中微电网的低碳运行方式和经济运行方式之间矛盾凸显,低碳和经济难以兼顾的问题,构建了计及绿电制氢和多能耦合的电-氢一体化运行框架,提出了综合考虑碳排放流和低碳需求响应的微电网低碳-经济协同双层优化调度模型。上层优化调度模型中,以风光储氢一体化工业园区为典型微电网场景,以低碳性和经济性协调最优为目标,将源侧碳交易机制融入调度决策目标中,充分挖掘微电网低碳-经济协同运行方式,以此制定微电网最优低碳经济调度策略;下层低碳需求响应模型中,以微电网用户碳减排所节约的碳排放成本为激励信号,通过建立微电网能量流与碳排放流的映射关系,实现碳排放责任的转移和分摊以及对微电网运行中的碳排放特性精细化评估,进而建立由负荷碳排放强度时空差异性引导用户参与碳减排策略的低碳需求响应(demond response,DR)模型,深入挖掘微电网源-荷间的低碳性和经济性间的协同性。以某工业园区微电网为例,验证了所提模型能有效兼顾系统的低碳性和经济性。

考虑云储能的综合能源运营商-负荷聚合商联盟混合博弈定价策略

为了准确描述负荷聚合商在与上级主体和同级主体进行能源交易过程中的各主体利益交互,以及用户侧储能昂贵且难以实施的问题。建立了综合能源运营商与负荷聚合商联盟之间的主从博弈模型,并特别考虑了拥有大量光伏用户的负荷聚合商之间的讨价还价博弈,以综合处理各主体之间的竞争与合作关系。为了实现负荷聚合商的低储高放策略,引入了云储能租赁的概念。采用二分法结合(alternating direction method of multipliers,ADMM)求解所构建的模型,以在各方持续互动过程中实现最大化的效益。研究结果表明,所建立的涵盖云储能租赁的混合博弈理论模型在保证各主体利益的同时能够制定合理的定价策略。

需求响应的园区综合能源系统优化运行方式研究

为了更好地展现园区综合能源系统中多种能源网络耦合互补、协调配合的特点,有效提高系统运行的经济性,提出了在电、热、冷、气4种网络负荷约束下考虑综合需求响应的冷热电联供型园区综合能源系统优化运行模型。首先在某园区建立电、热、冷、气4种能源网络,以及建立系统内部多种能量转换设备和储能装置的数学模型,同时考虑供热/供冷系统具有的热惯性,在此基础上,以综合能源系统建设运行成本与综合考虑价格型、激励型、替代型需求响应补偿成本之和最小为目标函数构建优化调度模型,并采用MATLAB平台中的Gurobi求解器对所提模型进行求解。通过算例分析可以得到:在能更好体现多能耦合互补特点的4种网络构成的园区综合能源系统中,综合考虑价格型、激励型、替代型需求响应的方式起到对负荷进行“削峰填谷”的作用,能更好地缓解系统高峰时期的供能压力,更有效地降低园区综合能源系统的日内运行成本,使得系统运行的总成本降低5.7%,有效提高了系统运行的经济性。

基于信息间隙决策理论-分布鲁棒优化的含电-氢-热混合储能综合能源系统需求响应策略

混合储能系统具有储能容量大、调节能力强等优点,有助于提高综合能源系统(integrated energy system,IES)的需求响应能力。首先,构建了一种电-氢-热混合储能系统(electric-hydrogen-thermal hybrid energy storage system,EHT-HESS),其中采用电解槽(electrolytic cell,EC)、蒸气重整反应(steam methane reforming,SMR)装置、储氢、热电联产氢燃料电池(hydrogen fuel cell,HFC)设备,实现电、气向氢能的转换,以及以氢能作为中间模态的“制氢-储氢-放氢/电/热”功能。其次,建立考虑EHT-HESS的IES需求响应策略优化模型,其中考虑IES响应电价和气价,同时根据富余风电量,进行购电、购气、用电、用热、用氢等策略决策的综合需求响应(integrated demand response,IDR)行为;并采用信息间隙决策理论(information gap decision theory,IGDT)计入概率分布未知的风电严重不确定性,采用基于综合范数的分布鲁棒优化(distributionally robust optimization,DRO)方法计入概率分布不完备的电价严重不确定性。最后,算例验证了模型和方法的合理性及有效性,并表明IES装设热电联产HFC构建EHT-HESS可实现氢能向电能与热能的转换,有助于增加风电消纳量,增加IDR决策的鲁棒性。

计及动态能源价格和共享储能电站的多主体综合能源系统双层优化调度策略

可再生能源不确定性背景下,为协调综合能源运营商、电热负荷聚集商及共享储能电站之间的利益关系,提出一种电热综合动态定价机制,基于综合需求响应特性,引导电热负荷聚集商参与综合能源系统运营商优化,促进储能高效应用和新能源就地消纳,实现多利益主体互利共赢。以综合能源系统运营商为主体,以电热负荷聚集商和共享储能运营商为从体,构建一主多从的综合能源多运营主体系统优化模型。充分挖掘共享储能运营商的运行模式,包括充电、放电和提供备用等模式。采用CPLEX对主从博弈模型迭代求解,算例结果验证了模型及方法的有效性。

考虑源荷互动的综合能源系统多目标双层规划

随着综合能源系统建设的不断推进,传统的“源随荷动”模式转向“源荷互动”已成为发展趋势。为此,提出了一种考虑源荷互动的综合能源系统多目标双层规划方法。首先,引入电–热–冷可中断负荷和可转移负荷参与综合需求响应,并制定了一种基于新能源发电与等效负荷相匹配的动态定价策略。然后,构建了含电动汽车充电站的综合能源系统多目标双层规划与运行模型,在上层规划模型中以经济成本、碳排放量、自主性为目标,在下层模型中以综合能源系统和电动汽车充电站的总运行成本最小为目标。最后,利用非支配排序遗传算法(non-dominated sorting genetic algorithm Ⅱ,NSGA-Ⅱ)算法和商业求解器CPLEX求解获得Pareto前沿解集,并利用Topsis法选择最优解。算例表明,该方法可以有效降低经济性成本、减少碳排放量、提高系统自主性。

基于AA-CAES电站和综合需求响应的供暖期弃风消纳策略

“双碳”目标背景下,为解决热电联产机组“以热定电”模式导致的大规模弃风问题,本文提出基于先进绝热压缩空气储能电站(advanced adiabatic compressed air energy storage,AA-CAES)和综合需求响应的综合能源系统(integrated energy system,IES)供暖期弃风消纳策略。首先,在“源-储”两侧建立热电联产机组与AA-CAES电站耦合运行模型,分析耦合运行实现热电解耦机理;其次,在“荷”侧引入价格型和替代型需求响应机制来探寻负荷侧优化系统调度潜力;然后,在IES中引入碳捕集系统和阶梯型碳交易机制来约束碳排放,并在碳排放量最少、综合成本最低为目标构建IES运行基础上,引入模糊机会规划约束模型来分析风、光不确定性对系统调度影响;最后,利用西北某地区实际数据进行算例验证。结果表明:热电机组与AA-CAES电站耦合运行相较于未耦合运行可提高风电消纳率84.55%、降低总成本11.42%、减少碳排放20.28%;综合需求响应机制的引入可进一步提高风电消纳率35.00%、降低总成本20.93%、减少碳排放24.43%;风光不确定性的上升会提高与外部电网的交互成本。

基于源荷储灵活资源协同的电热综合能源系统实验平台

当前能源转型背景下,发展综合能源系统是实现“碳达峰、碳中和”以及新型电力系统建设目标的重要途径。针对含多元化灵活资源的电热耦合系统,提出考虑“源-荷-储”协同的电热综合能源系统实验平台构建方案。设计考虑热电联产机组、电制热装置、蓄热罐以及电/热需求响应协同优化调度的实验案例,探讨实验平台在基础教学和拓展科研方面的用途。实验平台的建设为电气工程专业学生参与项目训练和创新实践类活动提供了重要的实践平台,有助于激发科研人员的探索性、创新性思维,促进理论研究和实验仿真的有机结合与良性循环,为综合能源系统领域的研究提供有力支撑。

考虑综合需求响应的多区域综合能源系统协同优化调度模型

新型电力系统大背景下,风光接入规模不断扩大,需求侧负荷类型愈发多样化。为提高综合能源系统的多能耦合转换能力,匹配源荷两侧供需关系,文章提出一种考虑综合需求响应的多区域综合能源系统协同优化调度模型。建立了考虑多种可调负荷的综合需求响应负荷模型和成本及收入模型;构建能源流向为“源侧出力-输入端能源节点-能源集线器-输出端能源节点-终端负荷”的多区域综合能源系统能流拓扑,并建立其能源耦合矩阵;在此基础上,以系统总调度成本最小为优化目标,建立考虑区域间电能交互的多区域综合能源系统协同优化调度模型;通过对冬夏典型日下的多种调度方案进行算例对比分析,证明所提模型能够增强总系统的多能耦合转换能力,进而有效提高系统整体经济性、灵活性和可靠性。