A Distributionally Robust Optimization Scheduling Model for Regional Integrated Energy Systems Considering Hot Dry Rock Co-Generation

Hot dry rock(HDR)is rich in reserve,widely distributed,green,low-carbon,and has broad development potential and prospects.In this paper,a distributionally robust optimization(DRO)scheduling model for a regionally integrated energy system(RIES)considering HDR co-generation is proposed.First,the HDR-enhanced geothermal system(HDR-EGS)is introduced into the RIES.HDR-EGS realizes the thermoelectric decoupling of combined heat and power(CHP)through coordinated operation with the regional power grid and the regional heat grid,which enhances the system wind power(WP)feed-in space.Secondly,peak-hour loads are shifted using price demand response guidance in the context of time-of-day pricing.Finally,the optimization objective is established to minimize the total cost in the RIES scheduling cycle and construct a DRO scheduling model for RIES with HDR-EGS.By simulating a real small-scale RIES,the results show that HDR-EGS can effectively promote WP consumption and reduce the operating cost of the system.

Two-Stage Optimal Scheduling of Community Integrated Energy System

From the perspective of a community energy operator,a two-stage optimal scheduling model of a community integrated energy system is proposed by integrating information on controllable loads.The day-ahead scheduling analyzes whether various controllable loads participate in the optimization and investigates the impact of their responses on the operating economy of the community integrated energy system(IES)before and after;the intra-day scheduling proposes a two-stage rolling optimization model based on the day-ahead scheduling scheme,taking into account the fluctuation of wind turbine output and load within a short period of time and according to the different response rates of heat and cooling power,and solves the adjusted output of each controllable device.The simulation results show that the optimal scheduling of controllable loads effectively reduces the comprehensive operating costs of community IES;the two-stage optimal scheduling model can meet the energy demand of customers while effectively and timely suppressing the random fluctuations on both sides of the source and load during the intra-day stage,realizing the economic and smooth operation of IES.

Low-Carbon Dispatch of an Integrated Energy System Considering Confidence Intervals for Renewable Energy Generation

Addressing the insufficiency in down-regulation leeway within integrated energy systems stemming from the erratic and volatile nature of wind and solar renewable energy generation,this study focuses on formulating a coordinated strategy involving the carbon capture unit of the integrated energy system and the resources on the load storage side.A scheduling model is devised that takes into account the confidence interval associated with renewable energy generation,with the overarching goal of optimizing the system for low-carbon operation.To begin with,an in-depth analysis is conducted on the temporal energy-shifting attributes and the low-carbon modulation mechanisms exhibited by the source-side carbon capture power plant within the context of integrated and adaptable operational paradigms.Drawing from this analysis,a model is devised to represent the adjustable resources on the charge-storage side,predicated on the principles of electro-thermal coupling within the energy system.Subsequently,the dissimilarities in the confidence intervals of renewable energy generation are considered,leading to the proposition of a flexible upper threshold for the confidence interval.Building on this,a low-carbon dispatch model is established for the integrated energy system,factoring in the margin allowed by the adjustable resources.In the final phase,a simulation is performed on a regional electric heating integrated energy system.This simulation seeks to assess the impact of source-load-storage coordination on the system’s low-carbon operation across various scenarios of reduction margin reserves.The findings underscore that the proactive scheduling model incorporating confidence interval considerations for reduction margin reserves effectively mitigates the uncertainties tied to renewable energy generation.Through harmonized orchestration of source,load,and storage elements,it expands the utilization scope for renewable energy,safeguards the economic efficiency of system operations under low-carbon emission conditions,and empirically validates the soundness and efficacy of the proposed approach.

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 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.

New framework of low-carbon city development of China:Underground space based integrated energy systems

Cities play a vital role in social development,which contribute to more than 70%of global carbon emission.Low-carbon city construction and decarbonization of the energy sector are the critical strategies to cope with the increasingly serious climate change problems,and low-carbon technologies have attracted extensive attention.However,the potential of such technologies to reduce carbon emissions is constrained by various factors,such as space,operational environment,and safety concerns.As an essential territorial natural resource,underground space can provide large-scale and stable space support for existing low-carbon technologies.Integrating underground space and low-carbon technologies could be a promising approach towards carbon neutrality,and hence,warrants further exploration.First,a comprehensive review of the existing low-carbon technologies including the technical bottlenecks is presented.Second,the features of underground space and its low carbon potential are summarized.Moreover,a framework for the underground space based integrated energy system is proposed,including system configuration,operational mechanisms,and the resulting benefits.Finally,the research prospect and key challenges required to be settled are highlighted.

Optimal Scheduling of Electrical Energy Systems Using a Fluid Dynamic Analogy

The electricity-gas transformation problem and related intrinsic mechanisms are considered.First,existing schemes for the optimization of electricity-gas integrated energy systems are analyzed through consideration of the relevant literature,and an Electricity Hub(EH)for electricity-gas coupling is proposed.Then,the distribution mechanism in the circuit of the considered electricity-gas integrated system is analyzed.Afterward,a mathematical model for the natural gas pipeline is elaborated according to the power relationship,a node power flow calculation method,and security requirements.Next,the coupling relationship between them is implemented,and dedicated simulations are carried out.Through experimental data,it is found that after 79 data iterations,the optimization results of power generation and gas purchase cost in the new system converge to$54,936 in total,which is consistent with the data obtained by an existing centralized optimization scheme.However,the new proposed optimization scheme is found to be more flexible and convenient.

Two-stage distributionally robust optimization-based coordinated scheduling of integrated energy system with electricity-hydrogen hybrid energy storage

A coordinated scheduling model based on two-stage distributionally robust optimization(TSDRO)is proposed for integrated energy systems(IESs)with electricity-hydrogen hybrid energy storage.The scheduling problem of the IES is divided into two stages in the TSDRO-based coordinated scheduling model.The first stage addresses the day-ahead optimal scheduling problem of the IES under deterministic forecasting information,while the sec-ond stage uses a distributionally robust optimization method to determine the intraday rescheduling problem under high-order uncertainties,building upon the results of the first stage.The scheduling model also considers col-laboration among the electricity,thermal,and gas networks,focusing on economic operation and carbon emissions.The flexibility of these networks and the energy gradient utilization of hydrogen units during operation are also incor-porated into the model.To improve computational efficiency,the nonlinear formulations in the TSDRO-based coordinated scheduling model are properly linearized to obtain a Mixed-Integer Linear Programming model.The Column-Constraint Generation(C&CG)algorithm is then employed to decompose the scheduling model into a mas-ter problem and subproblems.Through the iterative solution of the master problem and subproblems,an efficient analysis of the coordinated scheduling model is achieved.Finally,the effectiveness of the proposed TSDRO-based coordinated scheduling model is verified through case studies.The simulation results demonstrate that the proposed TSDRO-based coordinated scheduling model can effectively accomplish the optimal scheduling task while consider-ing the uncertainty and flexibility of the system.Compared with traditional methods,the proposed TSDRO-based coordinated scheduling model can better balance conservativeness and robustness.

海水淡化厂与区域水-能耦合系统的协同调度

海水淡化厂具有能量密集、运行灵活的特点,是理想的电力需求响应资源。然而,现有关于淡化厂与电网协同运行的研究大多关注电网和淡化厂的一体化调度、无法适应双方自主决策的工程场景,对淡化厂运行约束的刻画也比较粗糙。该文研究反渗透淡化厂与区域水-能耦合系统(waterenergy nexus,WEN)的协同运行方法。首先,考虑淡化厂的生产流程、调节特性和运行约束,分别建立传统及新能源淡化厂的水-能管理模型;其次,在保障两类淡化厂和区域WEN自主决策和信息隐私的条件下,提出以双方调度计划互动为载体的“激励型”和“价格型”两种协同运行机制及调度模型,并提出基于二阶锥松弛和McCormick包络的求解方法。用算例验证所提协同运行机制、调度模型及求解方法的有效性。

基于深度强化学习的氢能综合能源系统优化调度方法

为实现碳减排目标,氢能与综合能源系统的结合成为最具潜力的发展方向之一。针对当前氢能综合能源系统调度策略灵活性不足、复杂系统多目标优化求解困难等问题,提出一种基于深度强化学习的氢能综合能源系统优化调度方法。首先,采用耦合设备的变工况模型,构建风-光-氢-冷-热-电综合能源系统,拓展设备联合供能空间。其次,考虑系统运行成本、碳排放量、系统自供给平衡度和新能源利用率,基于最优解距离构建多目标优化模型,激发智能体探索性。然后,通过时序片段表征优化深度强化学习算法,增强了智能体对系统状态变化的估计精度。最后,在源荷实测数据的基础上设计仿真算例。结果表明,所提方法可以有效提高氢能综合能源系统调度的灵活性,充分挖掘氢能的碳减排潜力,实现调度经济性和环保性的双重优化。

基于制氢设备精细建模的综合能源系统绿氢蓝氢协调低碳优化策略

在“双碳”背景下,为了降低氢能利用成本及综合能源系统的碳排放,该文提出一种综合能源系统绿氢和蓝氢协调低碳优化策略。首先考虑电解水制氢和天然气制氢的经济和碳排放特性,分别引入绿氢和蓝氢产-储-用模块,并对绿氢制取设备的功率-效率动态特性、蓝氢制取中的能量转换过程进行精细化建模,实现不同类型氢能高效协调利用。其次,通过优化氢负荷供应中的绿氢和蓝氢比例,提升供氢灵活性。基于此,综合考虑碳交易、波动性风电制氢下的电解槽寿命损耗以及各设备的约束条件,以风电运行与弃风惩罚成本、购能成本、电解槽的寿命折损成本、蓝氢提纯成本及碳排放成本之和的总经济成本最小为目标,构建低碳经济调度模型。最后,通过算例分析验证了所提绿氢蓝氢协调优化策略的合理性。

考虑氢能利用与需求响应的综合能源系统低碳优化调度

综合能源系统(IES)对提高能源利用效率、减少碳排放具有重要意义.为了更好地实现这一目标,提出一种考虑氢能利用与需求响应的IES低碳优化调度方法.在源侧,构建以氢能利用为核心的IES模型来优化设备运行灵活性;在负荷侧,考虑到用户用能特征,建立基于Logistic函数的需求响应模型来优化负荷曲线、协助降碳;同时,为进一步挖掘系统的碳减排潜力,在优化模型中引入阶梯式碳交易机制;最后,综合考虑系统购能成本、运维成本、碳交易成本以及弃风成本,以IES日运行总成本最小为目标函数进行优化调度.算例验证结果表明,所构建模型不仅达到负荷削峰填谷的效果,同时可以有效地降低IES的运行总成本和碳排放,具有较好的低碳经济性.

考虑能耗节约的集装箱码头装卸设备集成调度

针对自动化集装箱码头中岸桥与人工智能运输机器人(ART)的集成调度问题,依据作业阶段将设备能耗划分成多个表现形式,构建以最小化岸桥和ART的总能耗为目标的整数规划模型。为提高求解质量,提出一种具有重组变异和随机扰动的自适应粒子群算法。根据不同时期的搜索需求,对惯性权重实行自适应调整;并引入随机粒子增强个体的交互能力,结合迭代进程对最优粒子实施不定维更新,为其摆脱局部困境提供更多机会。最后,以天津港北疆C段自动化集装箱码头为研究背景设计了不同规模算例,将改进算法与GUROBI求解器以及其他算法进行比较,验证了模型和算法的有效性。结果表明,随着岸桥和ART的配置数量逐渐增加,作业进程加快,码头总能耗分别呈现降低和先降后升的趋势;此外,相比于传统的调度模型,所提方法能够在较短的完工时间里节约更多的作业能耗。

新型储能技术进展与挑战Ⅲ:储能集成技术、安全技术和系统规划调度

新型储能日益成为中国建设新型能源体系和新型电力系统的关键技术,已成为中国经济发展的新动能。与之相应,新型储能技术的相关研究也在快速发展。开展了该领域的系列评价性综述工作,共分为电化学储能技术、物理储能与储热技术、储能集成技术、安全技术和系统规划调度3个部分,对各类新型储能技术的应用领域、最新研究进展及局限性等问题进行了全面系统的对比分析,并进一步探讨了储能集成技术、安全技术、系统规划调度等储能系统相关领域面临的挑战及发展趋势。第3部分为新型储能技术进展与挑战,重点对储能集成技术、安全技术和系统规划调度中的高压级联技术、构网型储能技术、数智化和数字孪生技术、分布式温度监测技术、浸没式液冷技术、高效的优化算法等技术进展进行综合分析与讨论。

考虑太阳能辅助碳捕集技术的综合能源生产单元随机低碳调度策略

为解决综合能源生产单元(integrated energy production unit,IEPU)中燃煤机组碳捕集过程的高能耗问题,同时应对新能源不确定性对运行调度带来的挑战,该文提出一种考虑太阳能辅助碳捕集技术的IEPU随机低碳调度策略,旨在实现IEPU的多能协同与低碳运行。首先,对含太阳能辅助碳捕集热电联产单元(combined heat and power based on solar-assisted carbon capture,CHP-SACC)的能量流动与运行机理进行分析,并构建其运行模型;其次,考虑风电不确定性带来的影响,提出一种基于条件最小二乘生成对抗网络(conditional-least squares generative adversarial networks,C-LSGANs)的可再生能源场景生成方法来提高场景的生成质量;然后,考虑异质能流耦合约束、多元设备运行约束以及能量平衡约束等,以最大化系统运行收益期望为目标构建IEPU随机低碳调度模型;最后,在算例仿真中设置不同的运行策略验证所提低碳转型方案的有效性,并分析了能源价格、设备容量等因素对系统运行收益的影响。

考虑需求响应和共享储能的微网联盟两阶段优化调度

随着共享储能的推广,能源信息的流动与共享得到进一步发展,为促进能源管理和提升利用效率,提出一种基于共享储能和需求响应的微网联盟两阶段优化调度策略。首先,建立多微网联盟-共享储能系统运行框架,并基于综合贡献度对微网利益分配过程进行建模;其次,建立两阶段优化调度模型,第一阶段以多微网联盟-共享储能系统净收益最大为目标,第二阶段考虑用户的需求响应,求解耗能用户的最低购能费用;再次,利用求解器对两阶段模型分别进行求解,得到多微网系统的分时能源价格、各微网设备的运行状态、需求响应后负荷和各微网利益;最后,设置4个方案作为算例,验证所提优化策略在提高各微网收益和激励用户需求响应的有效性。

Coordinated Scheduling of Energy Resources for Distributed DHCs in an Integrated Energy Grid

As more and more distributed renewable energy resources connected to electric power grids,the conventional power system evolves into an integrated energy grid(IEG)in order to satisfy various types of energy demands.This paper proposes a model of the coordinated scheduling of energy resources(CSoERs)for distributed district heating and cooling systems(DHCs)in an IEG.The model takes into consideration both the dispatchable grid-connected generators and distributed renewable energy resources,such as wind energy,solar energy and natural gas.The objective is to minimize the operation costs in the IEG in order to satisfy not only the electrical loads but also the heating loads and cooling loads.Furthermore,an energy storage system for heating loads and cooling loads is also developed in the DHCs to improve the operation reliability in the distributed DHCs.Detailed simulation studies are carried out to verify the effectiveness of the CSoERs under two different operation scenarios:grid-connected scenario and stand-alone scenario.Simulation results demonstrate that the performance of the CSoERs contributes to significant energy saving and reliability operation in both grid-connected scenario and standalone scenario in the IEG.

光伏光热一体化建筑热负荷能效分层调度仿真

光伏光热一体化系统中涉及多种能源,包括太阳能和热能等。由于不同能源的产生、存储和使用特性不同,加之系统内部的复杂性,使得实现多能源协同调度变得复杂。为了获取满意的建筑热负荷能效分层协同调度结果,提出一种光伏光热一体化建筑热负荷能效分层协同调度方法。研究光伏光热一体化建筑中热负荷的热量传递过程,对热负荷自身和热惯性展开分析,获取热负荷热惯性大小和室内热量需求两者的关系。以最大[火用]效率和最小调度成本为目标,分别建立光伏光热一体化建筑热负荷能效上层和下层协同调度模型。通过量子粒子群算法对模型展开分析计算,确定最优建筑热负荷能效分层协同调度方案。实验分析表明,所提方法的热负荷能效分层协同调度效果好,且节能效益高。

计及负荷灵活特性的工业园区综合能源系统日前优化调度研究

研究工业灵活负荷可调特性是提升电网动态调节能力的有效途径。工业园区用户侧存在大量具备调节潜力的工业负荷资源,针对此特性,基于能源集线器构建包含分布式发电系统、储能电站、燃气轮机、燃气锅炉、灵活负荷等在内的工业园区综合能源系统数学模型,并提出一种考虑负荷灵活特性的园区能源系统日前优化调度方法。首先,考虑系统需求响应侧电解铝等灵活性负荷的可平移、可转移、可中断的负荷特性;其次,在计及生产运行要素的基础上,以购能成本、补偿成本以及运行和维护成本之和最小为目标函数,建立系统优化调度模型;最后,基于Matlab软件结合Cplex求解器,并通过3种不同典型场景对比分析,验证了所提模型的有效性。算例分析表明,考虑工业灵活电、热负荷耦合优化,成本最低,比没有灵活负荷参与时的成本降低了6.6%。研究分析表明,工业灵活负荷资源优化配置有助于促进新能源的消纳、减轻工业用电压力和提高工业园区系统运行的经济性。

低碳综合能源系统研究框架与关键问题研究综述

低碳综合能源系统是融合多种低碳技术和措施、集成灵活性资源、促进清洁能源消纳、降低碳排放的多能源系统,是实现“双碳”目标的物理载体。首先,从能源转型的宏观战略、物理载体和低碳技术角度论证了低碳综合能源系统是能源转型的有效路径,归纳了低碳综合能源系统的定义与特征内涵;然后,构建了低碳综合能源系统的研究框架,从源-网-荷-储及碳捕集等环节挖掘了低碳综合能源系统的减排潜力;为了充分发挥低碳综合能源系统的低碳优势,从协同规划与优化调度、市场机制等角度提炼了低碳综合能源系统的几个关键问题;最后,聚焦提炼的协同优化关键问题,从研究现状、面临问题和研究展望等方面进行了阐述,以期为能源系统的低碳发展提供参考。