Two-Stage Low-Carbon Economic Dispatch of Integrated Demand Response-Enabled Integrated Energy System with Ladder-Type Carbon Trading

Driven by the goal of“carbon neutrality”and“emission peak”,effectively controlling system carbon emissions has become significantly important to governments around the world.To this end,a novel two-stage low-carbon economic scheduling framework that considers the coordinated optimization of ladder-type carbon trading and integrated demand response(IDR)is proposed in this paper for the integrated energy system(IES),where the first stage determines the energy consumption plan of users by leveraging the price-based electrical-heat IDR.In contrast,the second stage minimizes the system total cost to optimize the outputs of generations with consideration of the uncertainty of renewables.In addition,to fully exploit the system’s emission reduction potential,a carbon trading cost model with segmented CO_(2) emission intervals is built by introducing a reward-penalty ladder-type carbon trading mechanism,and the flexible thermal comfort elasticity of customers is taken into account by putting forward a predicted mean vote index on the load side.The CPLEX optimizer resolves the two-stage model,and the study results on a modified IES situated in North China show the proposed model can effectively reduce carbon emissions and guarantee economical efficiency operation of the system.

Optimal Scheduling for Flexible Regional Integrated Energy Systemwith Soft Open Point

The Regional Integrated Energy System(RIES)has brought new modes of development,utilization,conversion,storage of energy.The introduction of Soft Open Point(SOP)and the application of Power to Gas(P2G)technology will greatly deepen the coupling of the electricity-gas integrated energy system,improve the flexibility and safety of the operation of the power system,and bring a deal of benefits to the power system.On this background,an optimal dispatch model of RIES combined cold,heat,gas and electricity with SOP is proposed.Firstly,RIES architecture with SOP and P2G is designed and its mathematical model also is built.Secondly,on the basis of considering the optimal scheduling of combined cold,heat,gas and electricity,the optimal scheduling model for RIES was established.After that,the original model is transformed into a mixed-integer second-order cone programming model by using linearization and second-order cone relaxation techniques,and the CPLEX solver is invoked to solve the optimization problem.Finally,the modified IEEE 33-bus systemis used to analyze the benefits of SOP,P2G technology and lithium bromide absorption chillers in reducing systemnetwork loss and cost,as well as improving the system’s ability to absorb wind and solar and operating safety.

Scaling up private investment in low-carbon energy systems through regional cooperation: Effective trade policy measures

How to ensure energy supply and reduce environment pollution have turned into governments’ top priorities and key factors to maintain sustainable development. In this context, two major trade and investment agreements that could lead to profound influence on low-carbon energy systems development around the Asia-Pacific region are the Regional comprehensive economic partnership (RCEP) consisted of the Association of Southeast Asian Nations (ASEAN) plus Australia, China, India, Japan, New Zealand, and Republic of Korea and the Belt and road initiative (BRI) initiated by China. In order to have a smooth transition to low-carbon energy systems in Asia, besides RCEP and BRI, it is imperative to boost private sector investment. Success of encouraging private sector investment depends on appropriate government policies towards promoting innovations and reducing financial risks to private investors. The research questions that are examined in this study are: What type of policy measures affects trade in low-carbon transition, particularly renewable energy (RE) transition? How can investment signals and incentives be reframed to scale up private finance in RE? The objective is to investigate and to provide several feasible trade policy and investment policy tools for both national and regional markets that governments could adopt to accelerate the speed of private financing of the low-carbon energy industry, particularly the RE industry.

Energy Integration in South America Region and the Energy Sustainability of the Nations

The objective of this manuscript is to analyze relation involving the energy sector and socioeco-nomic growth and, then, contextualize the process of energy integration within the development policies in South America. The methodology considers data related to the world’s economy and energy consumption and energy integration policy in countries and regions;and, South America’s energy potential and the energy integration process. Results show that despite the political and institutional difficulties involving the process, energy integration can bring a lot of benefits for countries development. The process of energy integration in South America is divided in three moments, but in both periods the transnational energy projects were restricted, mostly, by a bi-lateral plan and the creation of physical links in a region. In the 21th century’s context, it should be noted Brazil’s participation which has been consolidated as a lead country in this process, and, also the IIRSA (Initiative for the Integration of Regional Infrastructure in South America, nowadays renamed as COSIPLAN) like the main initiative in energy integration in the continent, in a context where the projects are no longer limited to traditional economic blocs. Finally, we note a lack of consensus in defining a comprehensive model of integration and solving asymmetries both within countries and between them.

Operation Cost Optimization Method of Regional Integrated Energy System in Electricity Market Environment Considering Uncertainty

In the electricity market environment,the regional integrated energy system(RIES)can reduce the total operation cost by participating in electricity market transactions.However,the RIES will face the risk of load and electricity price uncertainties,which may make its operation cost higher than expected.This paper proposes a method to optimize the operation cost of the RIES in the electricity market environment considering uncertainty.Firstly,based on the operation cost structure of the RIES in the electricity market environment,the energy flow relationship of the RIES is analyzed,and the operation cost model of the RIES is built.Then,the electricity purchase costs of the RIES in the medium-and long-term electricity markets,the spot electricity market,and the retail electricity market are analyzed.Finally,considering the risk of load and electricity price uncertainties,the operation cost optimization model of the RIES is established based on conditional value-at-risk.Then it is solved to obtain the operation cost optimization strategy of the RIES.Verification results show that the proposed operation cost optimization method can reduce the operation cost of high electricity price scenario by optimizing the energy purchase and distribution strategy,constrain the risk of load and electricity price uncertainties,and help balance the risks and benefits.

Multivariate Two-stage Adaptive-stacking Prediction of Regional Integrated Energy System

To reduce environmental pollution and improve the efficiency of cascaded energy utilization, regional integrated energy system(RIES) has received extensive attention. An accurate multi-energy load prediction is significant for RIES as it enables stakeholders to make effective decisions for carbon peaking and carbon neutrality goals. To this end, this paper proposes a multivariate two-stage adaptive-stacking prediction(M2ASP) framework. First, a preprocessing module based on ensemble learning is proposed. The input data are preprocessed to provide a reliable database for M2ASP, and highly correlated input variables of multi-energy load prediction are determined. Then, the load prediction results of four predictors are adaptively combined in the first stage of M2ASP to enhance generalization ability. Predictor hyper-parameters and intermediate data sets of M2ASP are trained with a metaheuristic method named collaborative atomic chaotic search(CACS) to achieve the adaptive staking of M2ASP. Finally, a prediction correction of the peak load consumption period is conducted in the second stage of M2ASP. The case studies indicate that the proposed framework has higher prediction accuracy, generalization ability, and stability than other benchmark prediction models.

An Analytical Method for Delineating Feasible Region for PV Integration Capacities in Net-zero Distribution Systems Considering Battery Energy Storage System Flexibility

To provide guidance for photovoltaic(PV)system integration in net-zero distribution systems(DSs),this paper proposes an analytical method for delineating the feasible region for PV integration capacities(PVICs),where the impact of battery energy storage system(BESS)flexibility is considered.First,we introduce distributionally robust chance constraints on network security and energy/carbon net-zero requirements,which form the upper and lower bounds of the feasible region.Then,the formulation and solution of the feasible region is proposed.The resulting analytical expression is a set of linear inequalities,illustrating that the feasible region is a polyhedron in a high-dimensional space.A procedure is designed to verify and adjust the feasible region,ensuring that it satisfies network loss constraints under alternating current(AC)power flow.Case studies on the 4-bus system,the IEEE 33-bus system,and the IEEE 123-bus system verify the effectiveness of the proposed method.It is demonstrated that the proposed method fully captures the spatio-temporal coupling relationship among PVs,loads,and BESSs,while also quantifying the impact of this relationship on the boundaries of the feasible region.

基于深度强化学习的电-气区域综合能源系统安全校正控制决策方法

电–气区域综合能源系统电、气相互耦合与影响,使得其安全校正控制难度大且对快速性要求高,为此,提出一种基于深度确定性策略梯度(deepdeterministicpolicy gradient,DDPG)算法的安全校正控制决策方法。首先,进行系统多能流与变量分析,建立安全校正控制的目标与约束条件。然后,构建基于DDPG的安全校正控制模型,设计目标奖励和各种约束条件奖励,提出结合基于综合灵敏度的安全校正知识经验设计目标奖励函数,使调整具有方向性,且目标奖励考虑能量枢纽(energy hub,EH)的经济效益及其可再生能源消纳;通过智能体离线训练,使其能够在线做出实时最优的安全校正控制策略,预先产生专家经验数据集存放于经验回放池,提高训练速度和收敛性。最后,通过含EH电–气区域综合能源系统仿真算例验证了所提方法的有效性。

含垃圾能源化处理及电动汽车负载的区域综合能源系统协调优化

传统能源系统互相独立、欠缺联动,容易导致能量的浪费,并且能源结构也难以优化。区域综合能源系统具备多能互补、高效利用的优点,是提高能源利用效率和环保性的重要改进技术。为了利用垃圾蕴含的能量和电动汽车负载端的能源消纳,文中建立一个考虑垃圾焚烧和电动汽车负载的区域综合能源系统模型,利用模型进行系统的优化调度研究。论文分析了系统内的多能源能量流通关系,而后对系统内的各种能源转换设备及电动汽车进行分析,引入垃圾能源化处理,将热能转化为电能,并利用电动汽车进行电能消纳的模式,得出区域综合能源系统的能源效益最大化的模型。通过python进行算例分析,结果表明,含垃圾处理和电动汽车参与的区域综合能源系统既能提高能源的利用效率,又能带来更优的经济效益。

考虑需求响应及不确定性的综合能源优化调度

如何在区域综合能源系统中建立有效的需求侧模型,对于需求响应政策的实施至关重要。为提高用户参与需求响应积极性,引入实时定价机制,同时考虑系统的经济低碳性和电气热用户的用能满意度,构建兼顾系统和用户利益的综合需求响应主从博弈模型。针对用户参与需求响应的不确定性,引入贝叶斯方法更新负荷曲线。算例分析表明,所提博弈模型及贝叶斯方法能够有效平衡系统和用户之间的利益,提高了综合需求响应的可靠性。

基于某商务区多源耦合供热系统运行研究

为了实现“双碳”目标,提高可再生能源的利用率,减少碳排放量,对沈阳某商务区进行规划,充分发挥区域内地热能、污水能等可再生能源灵活供热的特点,以地源热泵+污水源热泵+电锅炉3种热源耦合进行供热,为区域综合能源多能互补、灵活调度提供参考。利用DeST模拟软件建立区域建筑模型,模拟出区域建筑供暖季逐时热负荷;通过TRNSYS软件建立区域综合能源系统模型,以某典型设计为例,分别讨论了在5种工况下该耦合供热系统峰谷电时段的运行策略,并采用费用年值法对系统经济性进行分析。结果显示:该区域内办公类建筑热负荷最大;系统不蓄热时初投资最小,由于在电高峰时段增加了电锅炉运行时长,导致系统运行费用增加,系统整体经济性变差;在蓄热率为100%时,该耦合供热系统初投资较大,但运行费用较低,系统费用年值最小,经济性最优,体现了蓄热方案下降低运行费用的优势。

An explainable framework for load forecasting of a regional integrated energy system based on coupled features and multi-task learning

To extract strong correlations between different energy loads and improve the interpretability and accuracy for load forecasting of a regional integrated energy system(RIES),an explainable framework for load forecasting of an RIES is proposed.This includes the load forecasting model of RIES and its interpretation.A coupled feature extracting strat-egy is adopted to construct coupled features between loads as the input variables of the model.It is designed based on multi-task learning(MTL)with a long short-term memory(LSTM)model as the sharing layer.Based on SHapley Additive exPlanations(SHAP),this explainable framework combines global and local interpretations to improve the interpretability of load forecasting of the RIES.In addition,an input variable selection strategy based on the global SHAP value is proposed to select input feature variables of the model.A case study is given to verify the effectiveness of the proposed model,constructed coupled features,and input variable selection strategy.The results show that the explainable framework intuitively improves the interpretability of the prediction model.

面向多元灵活资源聚合的区域综合能源系统主动调节能力评估与优化:关键问题与研究架构

区域综合能源系统(regional integrated energy system,RIES)通过对多元灵活资源的整合与协调,在本地多能源供需平衡的基础上优化可调节能力,进而通过共享可调节量实现跨区域能量互济,有望提升能源利用效率,在深入挖掘海量用户可调节潜力,充分发挥系统灵活性价值方面发挥着重要作用。该文首先系统分析多元灵活资源聚合下构建RIES的驱动力和瓶颈,对现有研究概况进行综述。基于当前研究路径,从RIES主动调节能力时空动态演变规律深度挖掘、复杂非线性动态RIES主动调节能力优化、多RIES集群分布式最优协调3个方面,分析RIES研究过程中的关键问题。在此基础上,从RIES“主动调节能力评估、自治协调优化、集群协同控制”3个共同影响系统经济稳定运行的重点问题提出多元灵活资源聚合下RIES的研究架构,并对关键研究内容进行分析和阐述。

考虑灵活性资源和多能共享的低碳区域综合能源系统联盟-配电网博弈优化调度

随着全国碳交易市场政策落地,为充分挖掘区域综合能源系统(regional integrated energy system,RIES)低碳减排能力,提高多区域综合能源系统接入主动配电网(active distribution network,ADN)的经济交互效益,提出了考虑灵活性资源与低碳交互结构的区域综合能源系统联盟参与配电网调峰调度的优化调度策略。建立了以主动配电网为主体,区域综合能源系统联盟为从体的主从博弈模型。主体以最大化交互效益目标制定分时电价策略,从体成员间通过联络线实现多能共享,考虑碳交易制度以供能与碳交易成本之和最小为目标,响应主体电价策略,建立了下层多区域综合能源系统联盟合作博弈优化模型。引入包含需求响应、储能和电动汽车在内的灵活性资源,配合碳捕集-电转气耦合机组优化联盟内部各系统的低碳供能策略,满足联盟负荷需求。基于纳什议价理论完成联盟成员合作收益的分配。通过算例验证所提策略能够有效减少各区域综合能源系统碳排放,并保障主从交互经济效益。

计及用户热耐受度的区域综合能源系统韧性评估及提升研究

区域综合能源系统韧性评估涉及电力、燃气、冷热及建筑物等多元素特性,极端自然灾害的发生可能造成区域综合能源系统基础设施的严重损坏,尽管现有方法已部分考虑了区域热网动态特性,但对于长时间供热缺失造成的用户生命健康影响考虑不足。针对这一问题,提出了考虑用户热耐受度的韧性评估及提升方法。首先,建立了建筑物室内环境和用户热舒适度的耦合关系模型,提出了计及用户热耐受度的韧性评估指标,进而提出面向区域综合能源系统的韧性评估流程。其次,建立了极端天气灾前、灾中和灾后三阶段的韧性提升调度优化方法,实现了区域综合能源系统运行成本和停供能损失的兼顾。最后算例分析表明,所提方法填补了传统区域综合能源系统韧性分析中对于用户生命健康考量的缺失,实现了多能源经济效益和用户感受的双重提升。

基于供冷/热系统质-量调节的区域综合能源系统动态最优能流计算

区域综合能源系统(regional integrated energy system,RIES)的最优能流计算是求解RIES的设备配置、优化调度、故障分析等问题的基础。考虑供冷/热和供气管道传输能量的动态特性,建立RIES动态最优能流计算模型,其中基于特征线法获得了供冷/热管道和供气管道动态偏微分方程的代数解析解。针对基于供冷/热系统质–量调节模式下管道能量传输时滞变量造成RIES的动态能流计算模型难以求解的问题,提出采用分段插值法获得供冷/热管道两端节点温度之间关系的近似表达式并加入动态最优能流计算模型中。此外,针对优化模型中供冷/热系统的流量与温度相乘的双线性项,提出一种能够缩紧松弛间隙的分段凸包络松弛方法将原混合整数非线性优化模型转化为混合整数二次约束规划模型,能够在保证计算精度的同时实现高效求解。最后以某个RIES算例进行分析,验证了所提方法的计算准确性和高效性,并与常用的质调节模式相比,表明在供冷/热系统质–量调节模式下能找到经济性更优的RIES运行点。

基于图论的区域综合能源服务商交易路径优化

随着电力体制改革的不断推进,区域能源服务商数量不断增加,电网结构日益复杂,购、售电交易双方之间的可选路径增多。在此背景下,提出了区域能源服务商交易路径两步选择法。首先基于p-中位模型的区域能源服务商交易路径第1步优化选择,考虑综合建设运行成本、能源站与负荷中心的最短路径距离、用户负荷需求三方因素,构建多目标优化模型,作用于区域综合能源服务商的站址规划;然后,基于OD矩阵和双约束重力模型提出了区域能源服务商交易路径第2步优化选择,以电能传输量最大和区域能源服务商日运营利润最大为目标函数,作用于多个区域能源服务商之间的能源传输路径选择。采用枚举法和Dijkstra算法对所建模型进行求解并通过算例仿真证明该模型能够有效降低网络损耗成本,减少弃风弃光量,提高区域能源服务商的运营利润。

满足多元需求的区域综合能源系统经济性对比评估

在共同建设低碳社会,加快能源转型,实现“双碳”目标形势下,为解决我国能源结构调整等各类问题,区域综合能源系统成为满足我国生态工业园区电力、供冷和供热需求的合适方案。区域综合能源系统由燃气轮机子系统、余热锅炉及汽轮机子系统、太阳集热发电子系统和氨水余热吸收制冷子系统组成。通过采用能量分析法和㶲分析法进行经济性评估,该系统输出电量为765.00MW,输出冷量为11.70MW,能源利用效率达63.15%。区域综合能源系统的经济性优于分供式系统,在未来有着很大的发展前景。

高寒地区综合智慧供热平台建设及应用分析

为了推进高寒地区供热系统的智能化与低碳化,围绕海拉尔智慧供热平台的构建与实施,本文研究分析了智慧供热在极端寒冷环境中面临的挑战与潜在机遇,并对海拉尔智慧供热平台进行了实际运行效果的评估。通过数据分析方法探讨了平台在不同温度条件下的性能,重点关注供回水温度的精准控制、能耗的优化以及在热网波动和负荷变化下的稳定运行。研究结果表明,该平台在-30~-10℃的不同温度工况下均展现出卓越的运行效率和稳定性,尤其在极端温度下,热源调度模拟与实测值高度吻合,并表现出较低的误差。研究突显了智慧供热平台在提升高寒地区供热系统效率、降低能耗方面的显著作用,并为供热行业的智能化、低碳化发展提供了宝贵的实践经验和策略指导。

基于多源热泵协同优化的区域综合能源系统经济调度

为探究电、气热泵协同优化效果,提出多源热泵协同运行的区域综合能源系统(RIES)经济调度方法。首先,对电、气热泵技术特性进行对比阐述,并基于能量枢纽对电、气热泵多能互补运行工况下系统各类能量流进行分析;其次,根据电、气能源价格优势,在谷电时段利用电热泵进行电冷能源耦合供能,在电价高峰时段通过气热泵进行气冷替代供能,改善系统用电负荷峰谷特性与降低运行成本;最后,以系统成本最优建立电、气热泵协同优化调度模型,采用CPLEX软件进行求解。算例表明:电、气热泵协同运行能够充分发挥二者优势,降低系统运行成本的同时优化联络线交互功率波动,并且所提出的方法具有良好的环保效益。