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.

Distributed Robust Optimal Dispatch of Regional Integrated Energy Systems Based on ADMM Algorithm with Adaptive Step Size

This paper proposes a distributed robust optimal dispatch model to enhance information security and interaction among the operators in the regional integrated energy system(RIES).Our model regards the distribution network and each energy hub(EH)as independent operators and employs robust optimization to improve operational security caused by wind and photovoltaic(PV)power output uncertainties,with only deterministic information exchanged across boundaries.This paper also adopts the alternating direction method of multipliers(ADMM)algorithm to facilitate secure information interaction among multiple RIES operators,maximizing the benefit for each subject.Furthermore,the traditional ADMM algorithm with fixed step size is modified to be adaptive,addressing issues of redundant interactions caused by suboptimal initial step size settings.A case study validates the effectiveness of the proposed model,demonstrating the superiority of the ADMM algorithm with adaptive step size and the economic benefits of the distributed robust optimal dispatch model over the distributed stochastic optimal dispatch model.

Optimal Scheduling of Regional Integrated Energy Systems Considering Hybrid Demand Response

Flexible load can optimize the load curve,which is an important means to promote renewable energy consumption.The peculiarities of electricity,heat,cooling and gas loads are analyzed in this paper,considering the fuzzy degree of human perception for water temperature,and the characteristic model of hot water load is established.Considering the fuzzy degree of human perception of ambient temperature,the characteristic model of cooling load is established by using PMV and PPD index.Meanwhile,considering four combinations of cut load,translatable load,transferable load and alternative load,and considering the coupling relationship of composite parts,different response models of load are established respectively.With the minimum cost of the system,including operation and compensation costs as the objective function,the optimization scheduling model of the regional integrated energy system is established,and the Gurobi solver is used for simulation analysis to solve the optimal output and load response curve of each piece of equipment.The results show that the load curve can be optimized,the flexible regulation ability of the regional integrated energy system can be enhanced,the energy loss of the system can be reduced,and the wind power consumption ability of the system can be increased by considering the integrated demand response.

A study of novel real-time power balance strategy with virtual asynchronous machine control for regional integrated electric-thermal energy systems

The development of regional integrated electric-thermal energy systems(RIETES) is considered a promising direction for modern energy supply systems. These systems provide a significant potential to enhance the comprehensive utilization and efficient management of energy resources. Therein, the real-time power balance between supply and demand has emerged as one pressing concern for system stability operation. However, current methods focus more on minute-level and hour-level power optimal scheduling methods applied in RIETES. To achieve real-time power balance, this paper proposes one virtual asynchronous machine(VAM) control using heat with large inertia and electricity with fast response speed. First, the coupling timescale model is developed that considers the dynamic response time scales of both electric and thermal energy systems. Second, a real-time power balance strategy based on VAM control can be adopted to the load power variation and enhance the dynamic frequency response. Then, an adaptive inertia control method based on temperature variation is proposed, and the unified expression is further established. In addition, the small-signal stability of the proposed control strategy is validated. Finally, the effectiveness of this control strategy is confirmed through MATLAB/Simulink and HIL(Hardware-in-the-Loop) experiments.

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BWM-CRITIC定权的区域综合能源系统综合评价研究

综合能源系统是能源互联网的载体,可以有效提高能源利用效率。对其进行综合评价,是衡量新技术、新策略投入工程后应用效果的重要手段。但目前的评价方法仍受到主观性与不确定性因素的影响。针对此问题,从技术、经济和环境三方面构建评价指标体系,建立基于最优最劣法(best worst method,BWM)-客观权重赋权法(criteria importance though intercrieria correlation,CRITIC)组合赋权的综合评价模型。提出的新方法能够客观反映各指标的权重,使得评价结果更加科学准确。最后,通过项目实例评价,验证所提方法的合理性与可行性。

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。

基于主从博弈的含碳捕集与热电联产综合能源系统优化运行

为了合理地分配综合能源系统中各主体之间的利益,促进能源低碳化,文中基于主从博弈框架建立了含碳捕集系统的综合能源系统优化调度模型,降低了热电联产机组的碳排放量和系统的运营成本。文章构建碳捕集、电转气和热电联产的联合运行模型,在考虑综合需求响应的基础上,建立综合能源系统各主体的收益模型;构建一主多从的Stackelberg博弈模型,由于构建的优化模型具有高维、非线性非凸的特点,数值方法难以求解,传统启发式算法容易陷入局部最优且收敛速度较慢,因此提出一种新型天牛郊狼算法结合二次规划的分布式算法。以北方某工业园区为算例进行验证,分析结果表明,文中提出的模型及求解算法与传统模型相比,有效地降低了综合能源系统的运行成本和碳排放量,提高了可再生能源的消纳能力。

基于碳交易-绿色证书联合交易机制的含CHP-CCS-P2G耦合的区域综合能源系统低碳经济调度

提出一种基于碳交易-绿色证书联合交易机制的含热电联产机组、碳捕集和电转气设备联合运行的区域综合能源系统低碳经济调度模型。首先,分析碳交易和绿色证书交易机制的运行原理并构建其模型;同时,研究绿证交易价格变化对可再生能源消纳的影响。然后,在热电联产机组中引入碳捕集和电转气设备,构建热电联产机组、碳捕集和电转气设备联合运行的模型,将碳交易-绿证联合交易机制引入该模型中,并且分析热电联产机组联合运行模式下的电力、热力耦合特性。最后,在算例中通过设置不同的调度场景进行对比分析,结果表明该策略可有效降低碳排放,扩大可再生能源上网空间,使系统的运行更加经济。

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。

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.

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。

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。

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。

考虑多能互补灵活性和用户低碳意愿的区域综合能源系统鲁棒优化调度

为了解决区域综合能源系统(regional integrated energy system,RIES)中由于新能源出力不确定性和多能负荷波动所导致的灵活性不足问题,该文提出了一种考虑多能互补灵活性和用户低碳意愿的鲁棒优化方法。首先,计及新能源出力与负荷的共同影响,通过净负荷波动来刻画RIES电力子系统灵活性需求。为了计及用户低碳意愿对新能源消纳的影响,分别构建用户购买普通和零碳电能的效用函数。考虑多能耦合设备的灵活备用容量,建立包含多能灵活性供需平衡约束的目标为RIES总运行成本最小及用户总效用最大的三层鲁棒优化调度模型。引入设备最优运行区间对模型内时间耦合约束进行解耦,并采用KKT(Karush-Kuhn-Tucker)条件和嵌套列与约束生成(nested column and constraints generation,NC&CG)算法进行求解。算例分析表明,所提模型可提升RIES运行的灵活性,促进新能源消纳,实现了RIES的低碳经济运行。