基于信息物理模型的可再生能源电网能量平衡控制

分布式电源从属于不同运营部门,相互之间缺乏有效的信息交换,难以进行集中控制。文章针对可再生能源电网中由于新能源占比较高,易出现出力波动或出力不足,难以保障供能可靠性等问题,提出一种基于信息物理融合的可再生能源电网分布式能量控制模型。首先,为进一步提高可再生能源电网能量平衡控制能力,建立了可再生能源电网信息物理模型;然后,考虑可再生能源波动性对系统的干扰,建立一种自适应滑模观测器对可再生能源电网的扰动进行估计;最后,提出一种基于可再生能源电网的分布式协同控制器,并基于李雅普诺夫稳定性理论验证了该控制器的收敛性。仿真结果表明,文章所提出的控制方法可以提高可再生能源电网的能源利用率,增强系统的鲁棒性。     

分布式能源系统最优配置模式研究——以关中地区新农村为例

基于混合整数线性规划建立分布式能源系统优化模型,解决该系统设备复杂难以设计的问题,得到该系统的最优配置及最佳运行模式。为促进分布式能源系统的推广,模型以关中地区新农村东韩村为对象进行案例分析。通过计算可知,该研究提出的分布式能源系统节能率为18.7%,污染物减排率为28.5%,适用于可再生能源丰富的农村地区。然而,该系统费用较高,建议政府加大补贴力度。此外,为了提高系统能源利用率,建议该系统上网售电。     

考虑多能源协同的可再生能源电网快速解列电压优化控制策略北大核心CSCD

针对含可再生能源接入的电力系统在发生故障后,使得电网中部分机组运行解列,其对电网电压造成影响的问题,提出了一种考虑多能源协同的可再生能源电网快速解列电压优化控制策略。首先,分析电/气/热等多种能源间的转换特性和可调节特性,并分析含电/气/热等多种能源转换系统接入可再生能源电网后系统的运行特性,建立含多能源转换系统的可再生能源电网稳态模型;然后,考虑可再生能源电网解列时系统中重要负荷电能恢复量、系统电压波动量两个优化目标,建立可再生能源电网快速解列电压优化控制模型,并对控制模型进行求解;最后,以西北某地区电网运行数据为基础,搭建含多能源转换系统的可再生能源电网等值模型,分析并验证文章提出的电网快速解列电压优化控制模型的可行性和有效性。     

分布式能源接入后的电动汽车实时电价响应控制策略

随着电动汽车的规模化应用,为了缓解电网的压力,越来越多的分布式能源被接入。然而,电动汽车充电站的可再生能源供给一般小于电动汽车充电负荷,须与大电网联合运行。针对分布式能源与电网之间的协同增效利用,提出了微电网内的充电站储能系统与电网相互协调的策略。在建立电动汽车负荷模型的基础上,根据微网内可再生能源实时出力与负荷需求的求解不平衡率,使充电站储能系统和大电网根据不平衡率按一定比例协同运行。当电动汽车接入电网充电时,首次利用强化学习算法建立电价控制模型,实现两者的能源协调控制。以某地区的微网为例进行仿真分析,通过对比不同用户响应度的配电网负荷和充电站储能系统,验证该策略在微电网与大电网协同运行优化的有效性。该策略发挥了充电站储能系统和电网的联合运行优势,减小了电网负荷峰谷差,优化了电力负荷曲线,对解决如何有效地结合分布式能源和大电网对电动汽车进行充电等问题具有一定的实际意义和价值。     

燃煤机组最小边界出力稳定性评价方法分析

为进一步提升电网对可再生能源发电量的消纳水平,提高电网低谷运行的可靠性,开展了燃煤机组最小出力运行方式的核定研究。基于电站锅炉切圆燃烧机理与运行调整技术,并兼顾安全、稳定、环保、节能等指标,进行了最小出力稳定性评价方法探讨,并在示范机组完成了25%额定负荷的稳燃能力评价,以供同类进行借鉴。     

考虑抽水蓄能及电网运营成本的源荷储协调优化调度

将需求侧响应与抽水蓄能电站纳入系统优化调度,借助需求侧管理与抽水蓄能电站对负荷分布的调控能力以达到提高风电消纳水平和降低电网运营费用的目的。以弃风总量最小和电网购电费用最低为优化目标,并考虑系统功率平衡、机组启停时间、爬坡能力、机组出力界限、系统备用等约束条件,构建含大规模风电的源荷储协调优化调度模型,将模型转化为混合整数问题并应用MOSEK优化软件对其进行求解。算例结果表明,借助需求侧管理与抽水蓄能电站的协作效应,系统对风电消纳能力将有所提高,电网购电费用亦进一步降低。     

分布式电源电动汽车充电站储能系统电价分析

含分布式电源的电动汽车充电站的可再生能源供给常常小于电动汽车充电负荷,须要配电网辅助补充部分电能,不利于配电网的稳定运行。文章提出基于微电网内不平衡率的充电站储能系统的电能与电网电能联动策略。考虑配电网有峰、谷、平3种电价,故将充电站储能系统SOC分成3部分与之相对应,根据微网内可再生能源实时出力与负荷求出不平衡率U_R。当充电出现缺额时,由充电站储能系统和电网以不平衡率为比例协同补充充电缺额,实现了微电网内的能源协调控制。文章采用蒙特卡洛方法模拟电动汽车负荷,通过对比不同用户响应度的配电网等效负荷和充电站储能系统SOC,验证了该策略在微电网运行优化的有效性。该策略充分发挥了充电站储能系统和电网的联合运行优势,减小了电网负荷峰谷差,优化了电网负荷曲线。     

燃气内燃机分布式能源系统的热力学分析

针对上海某厂新建燃气内燃发电机组分布式能源系统,基于热力学第一定律和热力学第二定律分析了该系统在不同季节、不同运行模式下的能源综合利用率和?效率,结果表明:本能源系统在采暖工况下具有更高的能源利用率和?效率;与分产系统(市电+燃气锅炉+电制冷)相比,分布式能源系统能源利用率提高14%-19%,?效率提高12%-15%。     

多时间尺度滚动优化在冷热电联供系统中的优化调度研究

为解决可再生能源和用户负荷波动所造成的能量供需不平衡问题,该文提出多时间尺度优化运行方法。该方法建立“日前-日内滚动-实时调整”的三阶段优化模型来逐级优化机组出力,日前阶段考虑环境成本,日前优化以日运行成本最低为目标,日内滚动优化以滚动控制时域内购能成本和机组出力变化惩罚成本最低为目标,实时调整优化以设备功率总调整率最小为目标,最终得到设备的实时平滑出力计划。日前阶段比较不同的系统结构对CCHP系统日运行成本的影响,并确定了最佳的系统结构。仿真结果验证了所提策略的准确性,优化结果显示：多元储能模式能降低CCHP系统的运行成本;多时间尺度滚动优化不但能提高CCHP系统的运行经济性,而且能减小设备的功率波动,减小设备运行损耗。     

工业园区分布式冷热电三联供系统设计

针对武汉某工业园区,设计了一套分布式冷热电三联供系统,包括装机方案、制冷供热、水蓄冷、熔盐蓄热供能,详细阐述其设计原理和运行模式。采用天然气清洁能源,年平均综和能源利用效率为88. 9%,对实现园区能源的梯级利用、提高能源利用率、节能减排具有非常重要的意义。     

一种计及无功补偿的分布式电源优化配置方法

可再生能源以分布式电源的形式接入配电网是消纳可再生能源的重要手段,为进一步提高可再生能源的利用率,本文在分布式电源优化配置过程中考虑无功补偿设备以及储能系统的配置,建立了分布式电源、储能系统、无功补偿设备建设成本最小,系统网络损耗最小,系统电压稳定指标最优的多目标优化模型,并提出基于概率分布策略的改进遗传算法用于优化模型的求解。最后,以IEEE-33节点配电网系统为例,表明本文提出的配置方法可以改善分布式电源的波动性对配电网的不利影响,在保证系统稳定的前提下,进一步提高可再生能源利用率。     

Energy‐cost‐aware flow shop scheduling considering intermittent renewables,energy storage,and real‐time electricity pricing

The industrial sector is one of the major energy consumers that contribute to global climate change. Demand response programs and on‐site renewable energy provide great opportunities for the industrial sector to both go green and lower production costs. In this paper, a 2‐stage stochastic flow shop scheduling problem is proposed to minimize the total electricity purchase cost. The energy demand of the designed manufacturing system is met by on‐site renewables, energy storage, as well as the supply from the power grid. The volatile price, such as day‐ahead and real‐time pricing, applies to the portion supplied by the power grid. The first stage of the formulated model determines optimal job schedules and minimizes day‐ahead purchase commitment cost that considers forecasted renewable generation. The volatility of the real‐time electricity price and the variability of renewable generation are considered in the second stage of the model to compensate for errors of the forecasted renewable supply; the model will also minimize the total cost of real‐time electricity supplied by the real‐time pricing market and maximize the total profit of renewable fed into the grid. Case study results show that cost savings because of on‐site renewables are significant. Seasonal cost saving differences are also observed. The cost saving in summer is higher than that in winter with solar and wind supply in the system. Although the battery system also contributes to the cost saving, its effect is not as significant as the renewables.     

冷热电三联供系统的优化研究

冷热电联供系统主要应用于大型集中性供能系统中。作为分布式能源的一种,冷热电联供系统具有节约能源、改善环境、提高电力综合效益的优势。一般情况下,三联供系统是以天然气为燃料带动燃气轮机、微燃机或内燃机发电机等燃气发电设备运行,产生的电力供应用户的电力需求,系统发电后排出的余热通过余热回收利用设备(余热锅炉或者余热直燃机等)向用户供热、供冷。通过这种方式提高整个系统的一次能源利用率,实现能源的梯级利用,还可以提供并网电力作能源互补,经济收益和效率均得以提升。研究较为常见的燃气轮机中的一种蒸汽型吸收式冷热电联产系统,对不同配置方式和运行方式进行横向与纵向交叉比较,以完成系统优化研究。     

计及不确定性的多类型发电机组联合调度优化模型

为了促进可再生能源并网,解决可再生能源机组在内的多类型发电机组联合优化调度问题,引入全额收购可再生能源发电,由火电机组提供备用、允许适度弃风,由火电机组提供备用以及水火机组联合提供备用的可再生能源发电三种不同方案。首先构建了涵盖风、光伏、水力机组的可再生能源机组发电处理模型;再结合设定的三种方案组建了多类型发电机组节能调度优化模型;最后,基于基础数据,得出该节能调度优化模型的发电系统总煤耗、备用煤耗、系统发电成本、启停成本、弃风量及弃水量等关键指标的优化效果,对多类型发电机组联合调度优化具有一定的指导意义。     

储能对可再生能源并网发电的支撑作用

可再生能源发电并网对于电力系统的节能减排具有关键作用,选择合理的储能容量,并分析储能对可再生能源并网发电的支撑作用具有重要意义。从节能减排和供电可靠性角度建立具有储能装置的单母线电力系统和剩余电力系统的随机规划模型,并通过蒙特卡罗模拟算法对国外某地区的风力发电和储能联合运行系统进行模拟分析。结果表明,适度规模的储能容量不仅能有效解决可再生能源发电的功率波动问题、减小系统停电损失概率,而且能够降低系统的环境成本,但其减少程度与储能的全过程效率有关。     

基于改进支持向量机的多能源电力系统中储能容量规划及运行模型

研究多能源电力系统中储能装置的定容及运行,有利于减小功率波动,降低对电网的冲击,提高电能质量。以青海省海西千万瓦级可再生能源基地为例,首先根据光伏电站和风电场的历史数据分析了两种新能源发电系统的出力特性,在此基础上建立了支持向量机模型,对新能源电站的输出功率进行了短期预测。根据光伏电站和风电场的出力预测误差,建立了ARMA误差预测模型,进一步修正了光伏电站和风电场的预测曲线,最后根据出力预测曲线的功率谱确定了储能系统的容量及出力曲线。研究成果可为新能源并网提供技术支持。     

Modeling and daily operation optimization of a distributed energy system considering economic and energy aspects

This paper presents a distributed energy system (DES) for a local district and formulates a constrained nonlinear multiobjective optimization model for the daily operation of the system. The main objective of the study is to increase the efficiency by minimizing energy cost, energy consumption, and energy losses. It is implemented through the integration and complementation of renewable energies and fossil fuels as well as the recycling utilization of waste heat in the DES. The consideration of network topology and energy losses of water heating network could also contribute to the improvement of energy efficiency. To solve the optimization problem, a novel Whale Optimization Algorithm is employed. Furthermore, the economic and energy performance of the DES are evaluated and compared with that of conventional centralized energy systems, ie, the EG and MG energy‐supply modes. After simulation studies, the hourly optimal energy (both natural gas and electricity) purchasing schedule as well as the hourly optimal set points of mass water flow rates and supply/return water temperatures could be determined. The results show that the DES saves more than 50% of energy costs/energy consumption than the MG mode and over 22% than the EG mode for a whole day, verifying the competitive advantage and great potential of both energy saving and cost reduction of the DES.     

储能技术在冷热电三联供系统中的研究现状与应用

冷热电三联供（CCHP）系统是利用一次能源或可再生能源发电,并通过多种余热回收设备高效利用余热,建立在能源的综合梯级利用基础上的产能系统。用户负荷动态变化及可再生能源输出不稳定会导致冷热电联供系统供、需侧能量不匹配,储能技术可有效解决该问题。本文总结了CCHP系统中储能技术类型及其研究现状,阐明了CCHP系统中电能储存和热能储存技术的应用方式。指出在传统能源与可再生能源相结合、供能系统越发复杂化的能源发展态势下,系统特性、配置优化和对不同场景制定出运行策略是储能技术与CCHP集成系统未来的研究方向。     

Master‐slave game optimization method of smart energy systems considering the uncertainty of renewable energy

As the uncertainty of renewable energy output brings more and more risks to the day‐ahead dispatch of the power grid, an optimization scheduling strategy of a smart energy system based on improved master‐slave game model is proposed. Risk factors related to the uncertainties of renewable energy are introduced into the master‐slave game model. Taking the smart energy system as the leader and the end users as the follower, an optimized operation model of the smart energy system based on the improved master‐slave game model is established, which is transformed into a single‐layer linear programming model according to the Karush‐Kuhn‐Tucher conditions and the duality theorem. The benefits of the system and electric vehicle users in four application scenarios are obtained by the YALMIP algorithm and the sensitivity affecting the economics of the smart energy system is analyzed. The validity of the model is verified by a simulation analysis of actual operation data from the smart energy system in China. The simulation results show that the method proposed in this paper can increase the revenue of the smart energy system by 7%, reduce the risk cost and charging cost of electric vehicle users by 63.92% and 48.34%.     

Energy management system for smart grid: An overview and key issues

Energy crisis and the global impetus to “go green” have encouraged the integration of renewable energy resources, plug-in electric vehicles, and energy storage systems to the grid. The presence of more than one energy source in the grid necessitates the need for an efficient energy management system to guide the flow of energy. Moreover, the variability and volatile nature of renewable energy sources, uncertainties associated with plug-in electric vehicles, the electricity price, and the time-varying load bring new challenges to the power engineers to achieve demand-supply balance for stable operation of the power system. The energy management system can effectively coordinate the energy sharing/trading among all available energy resources, and supply loads economically in all the conditions for the reliable, secure, and efficient operation of the power system. This paper reviews the framework, objectives, architecture, benefits, and challenges of the energy management system with a comprehensive analysis of different stakeholders and participants involved in it. The review paper gives a critical analysis of the distributed energy resources behavior and different programs such as demand response, demand-side management, and power quality management implemented in the energy management system. Different uncertainty quantification methods are also summarized. This review paper also presents a comparative and critical analysis of the main optimization techniques used to achieve different energy management system objectives while satisfying multiple constraints. Thus, the review offers numerous recommendations for research and development of the cutting-edge optimized energy management system applicable for homes, buildings, industries, electric vehicles, and the whole community.