多代理技术在Energy Hub中的应用研究

微电网的分布式特点对系统的运行控制带来新的机遇和挑战,多代理系统(MAS)在微电网中的应用是目前研究的热点。在微电网中引入了一个新的概念——Energy Hub,构建并阐述了一个基于多代理系统(MAS)的三层控制体系。该体系依靠一定的经济运行策略,可以解决微电网系统的优化运行问题。

Multi-energy synergistic optimization in steelmaking process based on energy hub concept

The production process of iron and steel is accompanied by a large amount of energy production and consumption. Optimal scheduling and utilization of these energies within energy systems are crucial to realize a reduction in the cost, energy use, and CO_2 emissions.However, it is difficult to model and schedule energy usage within steel works because different types of energy and devices are involved. The energy hub(EH), as a universal modeling frame, is widely used in multi-energy systems to improve its efficiency, flexibility, and reliability.This paper proposed an efficient multi-layer model based on the EH concept, which is designed to systematically model the energy system and schedule energy within steelworks to meet the energy demand. Besides, to simulate the actual working conditions of the energy devices, the method of fitting the curve is used to describe the efficiency of the energy devices. Moreover, to evaluate the applicability of the proposed model, a case study is conducted to minimize both the economic operation cost and CO_2 emissions. The optimal results demonstrated that the model is suitable for energy systems within steel works. Further, the economic operation cost decreased by 3.41%, and CO_2 emissions decreased by approximately 3.67%.

Energy hub-based optimal planning for integrated energy systems considering part-load characteristics and synergistic effect of equipment

Integrated energy systems(lESs)represent a promising energy supply model within the energy internet.However,multi-energy flow coupling in the optimal configuration of IES results in a series of simplifications in the preliminary planning,affecting the cost,efficiency,and environmental performance of IES.A novel optimal planning method that considers the part-load characteristics and spatio-temporal synergistic effects of IES components is proposed to enable a rational design of the structure and size of IES.An extended energy hub model is introduced based on the“node of energy hub”concept by decomposing the IES into different types of energy equipment.Subsequently,a planning method is applied as a two-level optimization framework-the upper level is used to identify the type and size of the component,while the bottom level is used to optimize the operation strategy based on a typical day analysis method.The planning problem is solved using a two-stage evolutionary algorithm,combing the multiple-mutations adaptive genetic algorithm with an interior point optimization solver,to minimize the lifetime cost of the IES.Finally,the feasibility of the proposed planning method is demonstrated using a case study.The life cycle costs of the IES with and without consideration of the part-load characteristics of the components were$4.26 million and$4.15 million,respectively,in the case study.Moreover,ignoring the variation in component characteristics in the design stage resulted in an additional 11.57%expenditure due to an energy efficiency reduction under the off-design conditions.

Optimal Operation and Size for an Energy Hub with CCHP

The interest in distributed generation has been increasing in recent years, especially due to technical devel- opment on generation systems that meet environmental and energy policy concerns. One of the most impor- tant distributed energy technologies is Combined Cooling, Heat and Power (CCHP) systems. CCHP is a small and self-contained electric, heating and cooling generation plant that can provide power for households, commercial or industrial facilities. It can reduce power loss and enhance service reliability in distribution systems. The proposed method in this paper determines the optimal size and operation of CCHP, auxiliary boiler and also heat storage unit as elements of an energy hub, for users by an integrated view of electricity and natural gas network. Authors apply cost and benefit analysis in the optimization. To confirm the proposed method, the optimum sizes of these elements are determined for a hotel in Tehran as a case study.

电-气-氢-热-风-光耦合综合能源系统分层级Energy Hub建模方法

随着多能融合的不断深入,综合能源系统可实现大规模可再生能源消纳。由于综合能源系统广泛涉及电、气、氢、热、风、光等多种能源形式,经典Energy Hub方法与图论Energy Hub方法在建模效率与复杂度等方面均存在局限性。文章提出了分层级Energy Hub建模方法,将综合能源系统从能量输入到输出的耦合过程建模为分配层、转换层、集成层、储能层、网络层5个环节,全面涵盖了综合能源系统复杂多元的多能耦合关系,为输入与输出搭建桥梁,确保能量供需平衡。最后,通过算例分析论证了所提方法的优势与可行性,以及与传统方法在可再生能源消纳量上的提升。

Stochastic Programming for Hub Energy Management Considering Uncertainty Using Two-Point Estimate Method and Optimization Algorithm

To maximize energy profit with the participation of electricity,natural gas,and district heating networks in the day-ahead market,stochastic scheduling of energy hubs taking into account the uncertainty of photovoltaic and wind resources,has been carried out.This has been done using a new meta-heuristic algorithm,improved artificial rabbits optimization(IARO).In this study,the uncertainty of solar and wind energy sources is modeled using Hang’s two-point estimating method(TPEM).The IARO algorithm is applied to calculate the best capacity of hub energy equipment,such as solar and wind renewable energy sources,combined heat and power(CHP)systems,steamboilers,energy storage,and electric cars in the day-aheadmarket.The standard ARO algorithmis developed to mimic the foraging behavior of rabbits,and in this work,the algorithm’s effectiveness in avoiding premature convergence is improved by using the dystudynamic inertia weight technique.The proposed IARO-based scheduling framework’s performance is evaluated against that of traditional ARO,particle swarm optimization(PSO),and salp swarm algorithm(SSA).The findings show that,in comparison to previous approaches,the suggested meta-heuristic scheduling framework based on the IARO has increased energy profit in day-ahead electricity,gas,and heating markets by satisfying the operational and energy hub limitations.Additionally,the results show that TPEM approach dependability consideration decreased hub energy’s profit by 8.995%as compared to deterministic planning.

Prospects for key technologies of new-type urban integrated energy system

In recent years,primary energy consumption in China’s urban areas has increased rapidly,facing the problems of extensive use of energy,high energy consumption and insufficient intensified use of energy resources.Improving multienergy supply,increasing the proportion of clean energy and integrated energy efficiency are the main goals of urban development.The integrated energy system with multi-functional synergy and open trading will become one of the new directions for the development of new urban energy systems.This paper summarizes the main problems faced by the current towns and the characteristics of the new urban energy system,analyzes the development of new urban energy system from three aspects including energy interconnection hub infrastructure construction,energy management platform construction and energy value sharing,and forecasts the future development direction of new urban energy systems.

Optimal operation of cold–heat–electricity multi-energy collaborative system based on price demand response

In a multi-energy collaboration system, cooling, heating, electricity, and other energy components are coupled to complement each other. Through multi-energy coordination and cooperation, they can significantly improve their individual operating efficiency and overall economic benefits. Demand response, as a multi-energy supply and demand balance method, can further improve system flexibility and economy. Therefore, a multi-energy cooperative system optimization model has been proposed, which is driven by price-based demand response to determine the impact of power-demand response on the optimal operating mode of a multi-energy cooperative system. The main components of the multi-energy collaborative system have been analyzed. The multi-energy coupling characteristics have been identified based on the energy hub model. Using market elasticity as a basis, a price-based demand response model has been built. The model has been optimized to minimize daily operating cost of the multi-energy collaborative system. Using data from an actual situation, the model has been verified, and we have shown that the adoption of price-based demand response measures can significantly improve the economy of multi-energy collaborative systems.

A Summary of the Main Contents and Existing Problems in the Study of Multi-Energy Coupling in Energy Internet

Multi-energy flow (MEF) coupling is one of the key features of the energy Internet and integrated energy systems that are different from smart grids. With the increasing coupling of heterogeneous energy flow, the system characteristics of coupling are becoming more and more obvious and more complicated. The modeling, analysis and control methods of traditional single flow systems have not been applied directly. Therefore, it is necessary to study the modeling of multi-energy flow coupling, the power flow analysis, optimization and control method of heterogeneous energy flow, which plays the role of multi-energy flow synergy to avoid the adverse effects of coupling. This paper summarizes the current research situation of energy Internet at home and abroad from the aspects of modeling of multi-energy flow, power flow calculation and optimal dispatching, and analyzes the existing problems in the research of these aspects.

含P2G和复合储能的高速公路服务区综合能源系统日前优化调度

为了提高高速公路服务区综合能源系统可再生能源消纳能力、降低经济成本,本文面向高速公路服务区中电、气、冷、热等多态能源,基于能源枢纽矩阵建模方法,建立能源供给侧、能量转换侧和负荷需求侧各模块的能量转换与供需耦合特性模型;在充分消纳可再生能源的情况下,以系统运行总成本最小为目标函数,建立系统优化调度模型;针对同一负荷不同运行场景下的调度结果表明,所提模型能最大程度使用风光发电,降低系统总运行成本;供给侧引入电气耦合与负荷侧引入复合储能的调度结果表明,所提模型能达到系统运行费用最优,同时可实现系统周期内运行费用的“削峰填谷”。

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。

基于奖惩阶梯型碳价机制的能源枢纽低碳优化策略

为进一步降低碳排放水平以及源-荷不确定性对系统运行的影响,文中提出一种基于奖惩阶梯型碳价机制和分布式模型预测控制(distributed model predictive control,DMPC)的能源枢纽(energy hub,EH)日前-日内-实时多时间尺度低碳优化调度策略。引入奖惩阶梯型碳价计算方法,构建EH日前低碳优化调度模型,并制定基于DMPC的日内滚动和实时调整的反馈闭环优化策略,降低源-荷预测误差,提高传统模型预测控制(model predictive control,MPC)的求解效率。在日内阶段,构建以阶梯型碳成本、运行成本和储能调整惩罚成本之和最小为目标的日内滚动优化模型;在实时阶段,分解整体优化问题,建立基于DMPC的多智能体实时调整模型。算例结果表明,文中所提策略能够有效提升系统经济效益,降低源-荷不确定性,实现EH的低碳经济、稳定可靠运行。

计及短期运行灵活性的城市能源系统扩展规划

城市是能源消费与碳排放的主力.在“双碳”背景下,促进城市能源系统低碳转型已成为当前城市规划的首要任务.然而,在新能源出力占比增加的同时,系统的灵活性需求也随之增加.为此,提出一种考虑长短期不确定性的城市能源系统扩展规划模型,涵盖电、气、热多种能源形态,在规划的层面计及实时运行阶段的不确定性及运行灵活性,并采用随机优化方法进行求解.模型考虑新能源机组和能源枢纽中各类能源转换设备的容量扩建,通过施加碳排放配额约束来确保达成碳减排目标.算例结果表明,该模型能有效提高城市能源系统的经济性和新能源消纳率,并且可以满足不同的碳减排需求.

考虑多元协同互动的微能源网多目标优化运行

微能源网是促进新能源消纳和碳减排的重要载体,可提供电、热、气、氢等多类型的能源,有利于实现多种能源的统一协同调度。首先提出了含高比例风电的低碳微能源网架构,电、热系统通过包含电-热-氢多能转化和存储的能量枢纽互联;其次,综合考虑微能源网对上级网络能源价格及节点边际碳排放强度的响应、微能源网中配电网和热网自身的优化运行、电-热-氢能量枢纽内部灵活调节、终端负荷柔性能量需求,建立了考虑多元协同互动的微能源网多目标优化运行模型。通过分段线性化、二阶锥松弛、多目标加权模糊化处理技术将优化模型转化为易于求解的混合整数二阶锥单目标规划问题。最后,通过电-热-氢能量枢纽将改进的IEEE33节点电力系统和改进的巴厘岛32节点热力系统互联组成微能源网进行仿真验证,结果表明考虑多元协同互动的能源供需在系统运行经济性和低碳性方面具有优势。

计及广义储能的园区综合能源系统低碳规划

以综合能源系统的低碳规划为目标,建立了考虑蓄电池电储能、楼宇热储能、数据中心热储能为广义储能的通用统一模型,量化分析了广义储能运行灵活性对园区综合能源系统低碳化转型的支撑作用。计及负荷长短期增长不确定性与碳排放约束,建立了以规划年扩建成本与运行成本之和为目标函数的综合能源系统低碳扩建模型;以园区各设备运行约束为基础,考虑广义储能的灵活性运行方式,建立了基于能源枢纽的园区运行模型;以江苏省某工业园区为测试算例,分析了广义储能资源的灵活性运行对园区扩建规划的影响。结果表明,广义储能资源可利用时间转移特性实现多能源跨时段高效利用,有效促进了新能源消纳,保证了综合能源系统的规划方案兼具经济性与环保性。

基于系统动力学模型的综合货运枢纽绿色转型机理及实施路径研究

为助力加快实现交通运输行业绿色转型,以综合货运枢纽为着眼点,探索其绿色转型和高质量发展的实施方案。首先,识别出政策、技术创新、管理效率等3个关键因素,揭示综合货运枢纽绿色转型的动态支撑机理。然后,基于对各因素的分析,将环保政策松紧系数、科技投入系数、污染物排放系数作为变量,构建包含枢纽物流供应子系统、枢纽物流需求子系统、节能减排子系统的系统动力学模型。再以四川省某综合货运枢纽为例进行模拟,验证模型的有效性和实用性。最后,从政策标准、技术组合和管理效率等3个方面提出绿色转型路径。研究结果显示:(1)表征政策因素的环保政策松紧系数对节能减排有显著正面影响,但同时限制了枢纽总产值的提升,需关注政策出台时机和松紧度;(2)表征科技研发投入的科技投入系数对节能减排有显著正面影响,既减少碳排放,又不影响枢纽总产值提升,且存在后发优势;(3)表征绿色技术设备投入效果的污染物排放系数对节能减排有显著正面影响,但提示资金投入与减排效果并不是简单的线性关系,需重点关注绿色技术设备的组合优化,做好技术与业务流程的融合;(4)表征管理效率的排放治理投资系数呈现先增后减的趋势,说明需在枢纽结构、招商、人力、资金等方面设定合理区间以确保环保投入产出效果。通过动态模拟综合货运枢纽绿色转型机理,为地方政府因地制宜出台相关政策,以及为货运枢纽运营企业采取科学有效的技术手段和管理措施提供了理论依据。

考虑风电消纳的电热联合系统优化调度模型

电热联合系统能够有效整合电能和热能,具有显著的能源利用优势。为了分析电热联合调度的经济节能效果,在分时电价以及负荷波动的条件下,建立了包含风电场、能源集线器(energy hub,EH)、热泵和蓄热罐的电热联合系统优化调度模型。电热联合系统以日运行成本最小为目标,考虑了稳态电热联合潮流、储能设备动态特性、管道温度降方程等实际约束条件。为提高优化效率,采用方程线性化和分段McCormick凸包络技术处理约束中的非线性项,将原本的非凸优化问题转化为混合整数二次规划(mixed integer quadratic programming,MIQP)问题求解。通过算例分析验证了所提模型的有效性,在4种场景下比较了风电制热以及热网传输损耗对系统日运行成本和弃风量的影响,并确定了风电场接入热网的最佳节点。结果表明,电热联合系统能够将不稳定的风能转化为稳定的热能,从而有效提升风电消纳空间和系统经济效益。

考虑城市多能源系统不确定性的移动能量枢纽规划方法

针对低碳新能源供能与电热气负荷间能量平衡困难及其时空不确定性,提出一种基于交通流和多源能量流协同的城市多能源系统移动能量枢纽(mobile energy hub, MEH)模型及规划方法。首先,研究低碳型高比例可再生能源供能的城市多能源系统源网荷能量和功率平衡及其调节需求特性,建立具有灵活的“电-气-氢”能源转换和存储特性的移动能量枢纽模型;其次,基于移动能量枢纽模型,综合考虑交通运输网络流量动态及其输运成本,建立基于交通网与城市多能源系统网络协同和移动能量枢纽能量特性的多能流时空协调模型;然后,考虑可再生能源出力以及负荷不确定性,提出城市多能源系统不确定性模型,并在此基础上建立了综合投资和运行成本最小的移动能量枢纽规划模型;最后,以我国北方某地区多能源系统运行数据为基础,建立移动能量枢纽仿真模型。算例仿真结果表明,该文提出的移动能量枢纽规划模型能够有效提升城市多能源系统维持较高能量平衡水平下的经济性,并可为较大供能规模的多能源网络提供较好的多时空尺度能量调节特性。

基于能量枢纽的沼–风–光综合能源系统双层协同优化配置

针对沼-风-光乡村综合能源系统协同优化问题,构建了综合能源系统能量枢纽模型,并提出沼-风-光综合能源系统配置-运行协同优化双层规划模型,上层以年化总成本最小和碳排放量最小为目标,采用NSGA-II算法获取配置方案Pareto最优解集;下层以运行成本(包括碳排放成本)最小为目标获取最优运行方案,引入启发性规则,排除上层输入配置方案可能存在的设备冗余,加速上层优化配置。通过对福建某乡村沼-风-光综合能源系统进行算例验证,结果证明了所提优化配置和运行方案的多元性和优越性。

含干热岩区域综合能源系统日前优化调度

为了研究干热岩增强地热系统的发电性能和潜力,建立含干热岩综合能源系统的优化调度模型。首先,依据干热岩对流换热和有机朗肯循环发电机理,建立干热岩增强地热系统运行模型,为含干热岩区域综合能源系统的运行和规划提供模型基础;其次,针对系统调度中的风电、光伏不确定性波动,基于模糊信息间隙决策理论对不确定性半径和调度成本进行协同优化,从风险规避和机会寻取两方面量化系统不确定性波动变化范围,并评估相应的风险损失和机会收益;最后,通过算例仿真验证所提模型的有效性。