A More Renewable-Friendly Electrical Grid: Thermal Storage Refrigeration for Demand Response in California and Denmark

Energy storage technologies, which enable demand response, are being explored throughout the world as a component of strategies for switching to renewable intermittent energy sources and reducing peak loads. This study examines thermal storage refrigeration (TSR) technology as a case study for the potential value of demand response in California and Denmark. Using technical specifications from a TSR prototype developed at UC Davis and market data from California and Denmark, the analysis examines possible business models for the TSR refrigerators and highlights market characteristics that are important to its adoption. Results suggest that the TSR technology is not a viable option in the current market environment in Denmark, but could payback in less than 6 years in California if a part of a demand response based virtual power plant. In a hypothetical future scenario involving real-time pricing in the retail market, a high degree of price volatility would be needed to make TSR technology appealing to residential consumers. Based on this analysis, an interesting area of future work would focus on the market potential of TSR technology for commercial and industrial applications.

Evaluation of greenhouse gas emission reduction potential of a demand–response solution:a carbon handprint case study of a virtual power plant

The transition towards zero-carbon energy production is necessary to limit global warming.Smart energy systems have facilitated the control of demand-side resources to maintain the stability of the power grid and to provide balancing power for increasing renewable energy production.Virtual power plants are examples of demand–response solutions,which may also enable greenhouse gas(GHG)emission reductions due to the lower need for fossil-based balancing energy in the grid and the increased share of renewables.The aim of this study is to show how potential GHG emission reductions can be assessed through the carbon handprint approach for a virtual power plant(VPP)in a grid balancing market in Finland.According to our results,VPP can reduce the hourly based GHG emissions in the studied Finnish grid systems compared with the balancing power without the VPP.Typical energy sources used for the balance power are hydropower and fossil fuels.The reduction potential of GHG emissions varies from 68%to 98%depending on the share of the used energy source for the power balancing,thus VPPs have the potential to significantly reduce GHG emissions of electricity production and hence help mitigate climate change.

基于消费者耦合行为的综合需求响应建模与主从博弈运行策略研究

多种异质能源的集成利用在带来互补耦合效益的同时,通常忽略了需求侧多能耦合转换对用户用能满意度的影响,并且当前主流的需求响应单边定价机制大多难以应对系统与用户间复杂的利益交互与迭代关系。据此,提出一种考虑消费者耦合行为的综合需求响应建模与主从博弈运行策略。首先,考虑消费者耦合行为对用户满意度的影响,建立一种适用于综合能源系统负荷聚合商的综合需求响应改进模型。其次,以系统运营商为领导者、多个负荷聚合商为跟随者,提出一种基于主从博弈的综合能源系统优化运行策略,并对所建立的一主多从互动模型的Nash均衡解存在性与唯一性进行了证明。最后,结合标准IEEE33节点系统与比利时20节点天然气系统构建算例分析系统,所得结论验证了所提出的消费者耦合行为需求响应模型的准确性与所提策略方法在兼顾博弈主体双方利益方面的有效性。

基于荷-储碳流模型的电力系统双层优化调度

为减少高耗能机组出力,同时增加风电消纳能力,考虑负荷和储能两类灵活调用资源,提出基于荷-储碳放流模型的电力系统双层经济低碳优化调度方法。基于电力系统碳排放流理论,分别建立负荷和储能设备的碳排放流模型;设计考虑荷-储协同优化的低碳调度策略,在负荷侧建立基于负荷节点碳势的电-碳耦合价格需求响应模型,同时鉴于荷侧降碳调节的局限性,在储能侧建立基于碳流模型的低碳调度策略,实现荷-储协同低碳调度策略;考虑经济性和低碳性,建立包含上层经济调度、下层低碳调度的双层优化调度模型。通过改进IEEE-14节点系统对优化调度方法进行仿真验证,结果表明:提出的优化调度方法在保证经济性的同时,减少了弃风,并降低了高耗能机组出力,从而有效降低了全系统的碳排放。

Optimal Operation of Integrated Energy Systems Subject to Coupled Demand Constraints of Electricity and Natural Gas

This paper proposes a hybrid multi-objective optimization and game-theoretic approach(HMOGTA)to achieve the optimal operation of integrated energy systems(IESs)consisting of electricity and natural gas(E&G)utility networks,multiple distributed energy stations(DESs),and multiple energy users(EUs).The HMOGTA aims to solve the coordinated operation strategy of the electricity and natural gas networks considering the demand characteristics of DESs and EUs.In the HMOGTA,a hierarchical Stackelberg game model is developed for generating equilibrium strategies of DESs and EUs in each district energy network(DEN).Based on the game results,we obtain the coupling demand constraints of electricity and natural gas(CDCENs)which reflect the relationship between the amounts and prices of electricity and cooling(E&C)that DESs purchase from utility networks.Furthermore,the minimization of conflicting costs of E&G networks considering the CDCENs are solved by a multi-objective optimization method.A case study is conducted on a test IES composed of a 20-node natural gas network,a modified IEEE 30-bus system,and 3 DENs,which verifies the effectiveness of the proposed HMOGTA to realize fair treatment for all participants in the IES.

基于主从博弈的差异化建筑集群与微网协同优化调度方法

为充分调动绝热性能差异化建筑的需求响应能力,本文提出基于主从博弈的差异化建筑集群与微网协同优化调度方法。首先,采用热阻-热容网络对建筑的热动态特性进行建模,并构建暖通系统的用能模型;其次,为充分发挥接入建筑的电动汽车的灵活可调潜力,提出电动汽车到建筑集成系统的用能模型;然后,基于主从博弈提出微网与差异化建筑群的协同优化框架,并针对建筑群的差异化需求响应潜力提出定制化的电价方案;最后,通过算例验证了本文方法可根据建筑的差异化绝热性能灵活制定差异化的售电价格,从而充分挖掘建筑群差异化的需求响应能力。

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.

电氢市场主体参与电力市场的路径及发展展望

随着世界各国氢能发展战略的出台,电氢耦合成为备受关注的方向。电氢市场主体作为电力系统的灵活调节资源,能够助力实现双碳目标下新型电力系统的安全经济运行。中国电力现货市场建设稳步推进,致力于通过电价信号引导电力系统的资源配置,电氢市场主体能够通过参与电力市场降低其购电成本并获得额外收益,进而促进电氢产业的发展。为此,首先从技术可行性和商业模式的角度综述了已有电氢市场主体参与电力市场的相关研究;总结现有电力市场机制下电氢市场主体的参与方式;提出电氢负荷参与电能市场的投标模型和提供调频服务的机会成本计算模型并进行算例验证,在此基础上结合中国电力现货市场建设现状,为促进电氢市场主体参与电力市场提出了待解决的问题和建议。

考虑电-气-热耦合和需求响应的虚拟电厂优化调度策略

热电联产机组以热定电的工作方式无法同时满足冬季供暖效率最大化和电力调峰需求,存在发电出力调节能力不足的问题。针对上述问题,提出了考虑电、气、热能源耦合特性以及需求响应的虚拟电厂优化调度策略。首先,为提升热电联产机组向下调峰能力,引入电制气设备和碳捕集技术,构建新型的热电联产耦合模型。其次,为提升系统运行的灵活性,考虑峰谷分时电价、热价,建立综合需求响应机制。然后,为减少系统发电成本,引入电、热储能装置,以系统总成本和电、热储能运行成本最小化为目标建立虚拟电厂双层优化模型,并根据下层优化模型的KKT(Karush-Kuhn-Tucher,KKT)条件将双层模型转为单层并线性化处理进行求解。结果表明,所提方法的碳排放、运行成本以及新能源消纳率达到最优,提升了热电机组向下调峰能力,满足了系统低碳性、经济性的需求。

考虑电动汽车和5G基站的电力-信息-交通耦合网络需求响应策略

电动汽车(EV)是具有移动负荷和通信用户双重属性的主体,为充分挖掘其参与需求响应产生的可调度潜力并降低电网负荷波动,提出了电力-信息-交通网络耦合背景下EV和5G基站需求响应策略。首先,分析了EV和5G基站参与下的多网络耦合关系。其次,建立了EV集群和5G基站集群的灵活性模型。基于此模型,提出了两阶段需求响应优化调度策略:第1阶段以通信成本最小为目标,为EV提供充电导航和路径规划并优化基站用能模式;第2阶段以配电网负荷波动最小为目标,制定EV的充放电策略。最后,通过某城市交通模型的测试,分析了调度策略对基站运行、配电网负荷、潮流和用户的影响,验证了模型和方法的有效性。

电热固耦合作用下车载功率模块引脚焊点振动疲劳寿命研究

本文对车载功率模块引脚焊点在器件功率损耗产生的热量和路面颠簸引起的随机振动共同影响下的可靠性进行了研究.建立多物理场有限元分析模型对引脚焊点进行电热固耦合疲劳寿命仿真,得到发热状态和常温状态下的焊点随机振动响应应力分布和振动疲劳损伤值.利用基于经验的Dirlik疲劳损伤模型和Miner线性损伤累积法则对两种状态的疲劳寿命进行了估算和对比分析.结果表明:在考虑电热固耦合作用下,局部约束刚度降低和焊点振动响应应力增大导致焊点振动疲劳寿命明显降低,但仍然满足规定的振动可靠性要求.结合满功率负载发热状态下的振动失效试验结果,验证了分析结果的准确性和装置设计的可靠性.

A Demand Response System for Wind Power Integration: Greenhouse Gas Mitigation and Reduction of Generator Cycling

A smart grid power system for a small region consisting of 1,000 residential homes with electric heating appliances from the demand side,and a generic generation mix of nuclear,hydro,coal,gas and oil-based generators representing the supply side,is investigated using agent-based simulations.The simulation includes a transactive load control in a real-time pricing electricity market.The study investigates the impacts of adding wind power and demand response(DR)on both greenhouse gas(GHG)emissions and generator cycling requirements.The results demonstrate and quantify the effectiveness of DR in mitigating the variability of renewable generation.The extent to which greenhouse gas emissions can be mitigated is found to be highly dependent on the mix of generators and their operational capacity factors.It is expected that the effects of demand response on electricity use can reduce dependency on fossil fuel-based electricity generation.However,the anticipated mitigation of GHG emissions is found to dependent on the number and efficiency of fossil fuel generators,and especially on the capacity factor at which they operate.Therefore,if a generator(the marginal seller)is forced to use less efficient fossil fuel power generation schemes,it will result in higher GHG emissions.The simulations show that DR can yield a small reduction in GHG emissions,but also lead to a smaller increase in emissions in circumstances when,for example,a generator(the marginal seller)is forced to use less efficient fossil fuel power generation schemes.Nonetheless,DR is shown to enhance overall system operation,particularly by facilitating increased penetration of variable renewable electricity generation without jeopardizing grid operation reliability.DR reduces the amount of generator cycling by an increased order of magnitude,thereby reducing wear and tear,improving generator efficiency,and avoiding the need for additional operating reserves.The effectiveness of DR for these uses depends on the participation of responsive loads,and this study highlights the need to maintain a certain degree of diversity of loads to ensure they can provide adequate responsiveness to the changing grid conditions.

计及源-荷互动的区域电-热联合系统日前优化调度

中国大型清洁能源基地形成了含风电、光伏发电、电/热负荷等多重随机性的区域电-热联合系统,灵活可调资源依赖性强,低碳、经济运行难度大。为了充分整合源、荷侧资源并最大限度消纳新能源,提出了计及电、热负荷需求响应及日前预测误差场景的区域电-热联合系统日前优化调度方法。首先,采用滑动时间窗多元高斯混合分布和蒙特卡洛对随机性源-荷日前预测误差进行场景生成和预测值修正;然后,类比定义了电、热负荷需求响应模型,建立了考虑源-荷互动的区域电-热系统模型;接着,综合考虑多重成本,在所有典型场景下建立了联合系统的低碳、经济日前优化调度期望模型;最后,以北方某地区冬季能源供给为例,渐进对比有无电、热负荷需求响应的多场景优化运行结果。结果表明,全面引入电、热负荷需求响应及电加热熔盐储热锅炉可以促进规模化风、光电力消纳,且区域电-热联合系统低碳、经济运行能力显著增强。

考虑电热需求响应的光热-电热综合能源系统源荷协调经济调度

负荷侧灵活性资源协同源侧多模式供热有利于电热综合能源系统低碳运行,为缓解“三北”地区“风热冲突”现象、提高风电消纳量从而降低系统碳排放量提出一种计及电热需求响应的光热-电热综合能源系统源荷协调经济调度模型。源侧通过配备储热装置的光热电站(Concentrated Solar Power,CSP)和电加热装置(Electric Heater,EH)协同热电联产机组(Combined Heat and Power,CHP)供热在一定程度上解耦其“以热定电”工作模式,网侧建立了稳态电热潮流,荷侧计及电热需求响应,模型的综合优化目标考虑了系统总运行成本、弃风惩罚成本及碳交易成本。基于改进的IEEE30电网与6节点热网系统对所建立模型进行仿真,算例结果表明源荷协调运行可有效降低系统总调度成本、提高风电并网发电量及减少系统碳排放量。

电热协同互补提升电网灵活性的评估及仿真

电热协同互补对于提升能源安全、克服长时储能能力的不足意义重大。从满足电网功率调节灵活性的需求出发,以蓄热式电采暖作为电热协同互补系统的代表,建立了描述其功率调节特性的模型;提出了蓄放热可行域的概念,进一步实现了灵活调节能力的量化评估。基于实际场景,分析测算了典型日大规模电热协同互补对系统预防停电和促进新能源消纳的提升效果,结果表明,配置大规模储热容器有利于实现电热解耦,提升电热协同参与调峰备用的能力。

GDI喷油器电-磁-热耦合分析

汽油直喷(Gasoline direct injection,GDI)喷油器性能受温升影响较大,限制了发动机电子控制单元(Electronic control unit,ECU)对其喷油量的控制精度。针对GDI喷油器电、磁、热子系统之间的耦合关系,建立了耦合过程的物理模型,通过研究GDI喷油器工作过程中能量损耗及转化关系,揭示了电磁转化过程中产生的损耗是造成喷油器本体温升的主要原因。以电磁转化过程中能量损耗为热源,以热辐射和热传导基本理论为依据,利用ANSYS有限元软件对GDI喷油器温度场进行仿真分析,并进行了试验验证,分析了GDI喷油器本体温度场分布特点以及温升变化对喷油器性能的影响规律。结果表明,线圈和铁芯部分的温升较高,随温度升高GDI喷油器动态响应时间延长、喷油量减少,且温升受保持电流和保持脉宽的影响较大。

考虑电/热/气耦合需求响应的多能微网多种储能容量综合优化配置

在多能微网中配置多种储能设备有利于平滑可再生能源波动性,提升供能可靠性和用能经济性。以含风光发电和电/热/气负荷的多能微网为研究对象,研究考虑电/热/气耦合需求响应的微能源网多种储能系统优化配置方法。首先,基于人体对温度的模糊度以及电负荷和气负荷的可转移特性建立耦合需求响应模型。在此基础上,以经济成本和碳排放量最小为目标,建立了基于耦合需求响应的多种储能容量综合规划的多目标优化模型。然后,采用自适应动态权重因子以适应规划场景的灵活多变。最后,通过算例比较了应用耦合需求响应以及配置储能系统前后多能微网的经济性以及碳排放量,从而验证了所提方法的有效性。

基于路–电耦合网络的电动汽车需求响应技术

随着电动汽车(electric vehicle,EV)保有量的增长,大量无序充电负荷的接入可能给电网带来节点电压偏低、线路阻塞等影响。该文提出基于路-电耦合网络的EV需求响应技术,精确预测充电负荷时空分布特性并对其进行合理调度,以缓解或解决大规模EV无序充电引发的电网问题。首先分析路网交通信息与电网运行状态的交互影响,提出路网-电网耦合原则;在综合考虑路-电耦合对EV行为规律影响的基础上构建充电负荷预测模型,以获得聚合充电负荷的时空分布特性;进而提出考虑快充与慢充调控差异性的需求响应策略,其中快充调控可降低短时间内节点负荷,慢充调控可转移大量EV充电时间段;最后仿真结果表明,考虑路-电耦合能够更准确预测EV充电负荷并有效缓解电网电压偏低及输电线路阻塞问题。

基于舒适度的需求响应与碳交易的园区综合能源经济调度

在碳中和背景下,高比例新能源消纳和减排目标的实现要求打破不同能源间的壁垒,进行多能源联合优化调度。电转气技术在消纳新能源的同时也捕捉固定碳。文章基于含电转气、电制热、热电联产、燃气轮机等设备的电、气深度耦合的园区多能源系统,提出考虑用户舒适度的联合热、电需求响应和碳交易成本,并以园区运行成本最低为目标,建立园区综合能源系统联合经济调度模型。在满足用户舒适度前提下充分发挥联合热、电需求响应潜力,利用多能互补,源、荷互动,提高新能源消纳的同时降低园区运行成本。通过仿真验证了该模型能有效降低园区运行成本、提高新能源消纳能力。

计及综合需求响应和不确定性风险的电气热耦合型微电网协同优化

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