考虑碳排放的光储充一体站日前运行策略

"双碳"背景下,光储充一体站不仅能够缓解大量电动汽车充电对电网带来的冲击,而且能够利用新能源减少二氧化碳排放,逐渐成为未来电动汽车充电站的一种主流形式.为使光储充一体站在满足负荷需求的前提下减少碳排放,并且获取最优的运行经济性,提出一种考虑碳排放的光储充一体站日前运行策略.首先,通过数据-模型混合驱动的方式进行场景生成...     

基于二级聚集式的端对端电力交易控制策略

为更好地实现端对端电力交易,提出了二级聚集式控制策略。该策略只需一个数据监测点和从监测点到产消者的单向通信就能够实现端对端电力交易。其中,第一级控制采用带约束的非线性优化,以最小化社区微电网电费为目标,第二级控制采用基于规则的实时控制策略。通过仿真算例验证了控制策略的有效性,并对比分析了在社区微电网中采用集中式和分布式蓄电池对电能损耗及电费的影响。     

Evaluation of a plug‐in hybrid electric vehicle considering power generation best mix

In the transport section, it is necessary to reduce the amount of CO₂ emissions and oil dependence. Bio fuels and fuel cell vehicle (FCV), electric vehicle (EV) and plug‐in hybrid electric vehicle (PHEV) are expected to reduce CO₂ emissions and oil dependence. We focus on PHEV. PHEV can reduce total energy consumption because of its high efficiency and can run with both oil and electricity. Introduction of PHEV reduces oil consumption, but it also increases electricity demands. Therefore, we must evaluate PHEV's CO₂ reduction potential, not only in the transport section but also in the power grid section. To take into account the distribution of the daily travel distance is also very important. All energy charged in the PHEV's battery cannot always be used. That influences the evaluation. We formulate the total model that combines passenger car model and power utility grid model, and we also consider the distribution of the daily travel distance. With this model, we show the battery cost per kWh at which PHEV begins to be introduced and oil dependence in the passenger car section is to be reduced to 80%. We also show PHEV's CO₂ reduction potentials and effects on the power supply system. © 2010 Wiley Periodicals, Inc. Electr Eng Jpn, 171(2): 12–22, 2010; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20920     

Effects of Smart Charging of Multiple Electric Vehicles in Reducing Power Generation Fuel Cost

The high penetration of variable sources of renewable power generation will lead to operational difficulties in supply/demand balancing in the entire power system. The mass deployment of electric vehicles (EVs) and plug‐in hybrid vehicles (PHEVs) will also cause significant changes in electricity demand. Therefore, controlling and managing the charging time of EVs/PHEVs are effective approaches that are imperative for improving balancing in power system operation. We assumed travel patterns for EVs in a model of the future Tokyo power system and analyzed the power system loads, including the charging load of the EVs, under several charging control scenarios. We verified that charging time controls are substantially effective for reducing the fuel costs in the power system. Further, we found that load leveling under a multicar charging management scenario gave the best results in terms of the fuel costs in all cases.     

Evaluation of Residential PV‐EV System for Supply and Demand Balance of Power System

In recent years, there has been a growing interest in ecofriendly technologies such as residential photovoltaic (PV) systems and electric vehicles (EVs). PV systems and EVs will contribute to reducing CO₂ emissions in the residential sector and the transportation sector, respectively. In spite of that, high penetration of PV systems into the power grid can cause grid voltage and frequency stability problems. Also, the growth of the EV market will create an extra electricity load (for charging the EV fleet), leading to an increase in power utility fuel costs. In this research, we proposed the usage of the PV‐EV system as a method of mitigating the impact the spread of residential PV systems and EV on the power grid. We built an PV‐EV system simulation model and investigated the PV‐EV system contribution to the balance of power supply and demand and to reducing the total cost of the household under different electricity pricing scenarios. We also evaluated the effect of uncertainty in the forecasting of load and PV output on the performance of the PV‐EV system.     

Plug-In并联式混合动力汽车实时优化能量管理策略

能量管理策略是混合动力汽车的核心技术之一,其品质直接影响车辆的动力性、经济性和排放性能。首先制定了基于确定性规则的Plug-In并联式混合动力汽车能量管理策略;然后,为了提高车辆的燃油经济性,设计了电池能量观测单元,并对等效燃油消耗最小策略进行改进,提出了适用于Plug-In混合动力汽车的实时优化能量管理策略。研究结果表明,该能量管理策略显著提高了Plug-In并联式混合动力汽车的燃油经济性。     

Coordinated Electric Vehicle Charging for Commercial Parking Lot with Renewable Energy Sources

Electric vehicles (EVs) are increasing in popularity because of their low operating cost and environmental friendly operation. The anticipated rise in EV usage, along with the increased use of renewable energy sources and smart storage devices for EV charging, presents opportunities as well as challenges. Time-varying electricity pricing and day-ahead power commitment add another dimension to this problem. In this research, we develop coordinated EV charging strategies for renewable energy powered charging stations in parking lots. This work maximizes the profits for parking lot operators by taking advantage of time-varying electricity pricing while satisfying system constraints. We propose a linear programming-based strategy for EV charging, and we specifically derive a centralized linear program that minimizes the charging cost for parking lot operator while satisfying customers’ demand in available time.     

考虑碳交易的综合能源系统在不同配置情景下的运行分析

大量分布式可再生能源发电机组的部署和碳排放交易的成本可对综合能源系统的运行产生重要影响。首先,针对电热综合能源系统,本文建立了考虑负荷需求、风速、太阳辐射强度和碳排放交易成本等不确定性因素的热网-主动配电网耦合模型。其次,本文采用多时段蒙特卡洛树状仿真的随机方法,分析可再生能源发电集成度和碳排放交易成本对系统运行总成本的影响。最后,本文以新疆能源系统为对象进行了算例分析。算例仿真结果表明:在新能源补贴下滑的大环境下,碳排放交易的实施可以为政府推进可再生能源装机提供新的动力。     

基于区块链技术的电动汽车充电交易探讨

针对规模化电动汽车在充电交易时存在安全性低、自主性差的问题,提出了基于区块链技术的电动汽车充电交易模型。该模型在“多卖方-多买方”的电力市场竞争机制下,利用区块链技术去中心化、安全性高等特点还原电力商品属性,开放用户协商定价的权利。首先阐述了区块链技术在电力系统各领域应用现状。其次基于区块链平台与电力市场相似的网络拓扑形态,建立区块链架构下的电动汽车充电交易模型；最后制定传统电力市场和应用区块链平台的电力交易市场下满足电动汽车聚合商需求的充电方案,对比分析得出区块链去中心化的特点为满足电动汽车聚合商个性化需求提供了可能,同时提升新能源电厂收益,降低火电厂售电量从而减少碳排放。算例结果证明了所提模型的有效性和可行性,为电动汽车充电交易市场提供了一种新思路。     

计及含氢储能与电价型需求响应的能量枢纽日前经济调度

为了解耦冷热电联供(combined cool,heat and power system,CCHP)机组“以热定电”的运行约束,提高风电消纳能力,降低社会碳排放,提出了计及含氢储能与电价型需求响应的能量枢纽日前经济调度模型。源侧利用冷、热、电、氢4种储能装置,打破CCHP机组热电耦合约束;荷侧引入电价型需求响应改变用户用电行为,通过优化各机组出力与电负荷曲线,增加风机出力。该模型以系统日运行成本最低为目标,引入弃风惩罚成本增加风电消纳,综合功率平衡等约束,调用Gurobi求解器进行优化求解。对不同场景下能量枢纽的优化结果进行分析,并计算燃油汽车的碳排放量以量化氢燃料电池汽车节约的社会碳排放。结果表明:在电价型需求响应策略下,考虑CCHP与含氢储能的能量枢纽系统在增加风电消纳能力的同时降低了系统的日运行总成本,减少了社会碳排放。     

Optimization of Lebanon's power generation scenarios to meet the electricity demand by 2030

Presently, Lebanon provides 95 % of the primary energy electricity power generation by using fuel-oil used in thermal power plants. To meet the population needs, private generators are also used in all the country and they represent the third of total electricity production. The challenges over the future development of the Lebanese electric sector are economic and environmental. This is why currently, the energy policy makers aim to diversify the national electricity generation mix in the energy planning strategy and to introduce low-carbon technologies. The complexity of these challenges in the particular Lebanese context has motivated our study which aims to recommend policies to develop the optimal electricity generation scenario by 2030. This paper presents a methodology to evaluate different scenarios reflecting different combinations of technologies by 2030. This is achieved by using an excel tool “Excel Solver Optimization Calculator” which makes possible the interaction of various inputs to produce a least-cost generation mix. The main results focus on the least-cost electricity generation portfolio, total investment required to generate electricity, level of energy independence and carbon emissions. Many policy choices could be feasible and very advantageous for Lebanon if renewable energies are deployed massively. However, this requires policies that support the massive use of renewable energy technologies in the mix.     

Probabilistic Constrained Load Flow Considering Integration of Wind Power Generation and Electric Vehicles

A new formulation and solution of probabilistic constrained load flow (PCLF) problem suitable for modern power systems with wind power generation and electric vehicles (EV) demand or supply is represented. The developed stochastic model of EV demand/supply and the wind power generation model are incorporated into load flow studies. In the resulted PCLF formulation, discrete and continuous control parameters are engaged. Therefore, a hybrid learning automata system (HLAS) is developed to find the optimal offline control settings over a whole planning period of power system. The process of HLAS is applied to a new introduced 14-busbar test system which comprises two wind turbine (WT) generators, one small power plant, and two EV-plug-in stations connected at two PQ buses. The results demonstrate the excellent performance of the HLAS for PCLF problem. New formulae to facilitate the optimal integration of WT generation in correlation with EV demand/supply into the electricity grids are also introduced, resulting in the first benchmark. Novel conclusions for EV portfolio management are drawn.     

Opportunities in energy: National policy approaches for addressing climate change

Last year’s Intergovernmental Panel on Climate Change (IPCC) report and the Fourth National Climate Assessment both showed that to limit the worst consequences of climate change by keeping global average temperature increases to 1.5 C, the United States and other countries must achieve net-zero heat-trapping emissions economy-wide by mid-century, with nearly half of those reductions occurring by 2030. Decarbonizing the electric sector is one of the most cost-effective ways to reduce emissions and can help decarbonize other sectors with increased electrification. While renewable energy and energy efficiency have grown significantly in recent years due to technology cost reductions, state policies, and federal tax incentives, our rate of emissions reduction does not go far enough. Our analysis shows that a well-designed national Low Carbon Electricity Standard (LCES), Renewable Electricity Standard (RES), or increasing carbon price can help get the U.S. on a pathway for decarbonizing the power sector by 2050. The most cost-effective strategy for reducing emissions in the near-term is through the increased deployment of wind and solar, regardless of the policy. How much the generation mix shifts to low-carbon resources is a function of the stringency of the policy. These policies can also spur the development of low-carbon electricity in parts of the country that are not as far along in their transition to a clean energy economy. Allowing a wide range of carbon-free and low-carbon resources to compete against each other could deliver the most low-carbon electricity at the lowest cost and help broaden support for these policies.     

计及电动汽车与温控负荷需求响应的分层能源系统优化调度

针对电动汽车(electric vehicle,EV)大规模接入电网对电力系统带来的影响,构建了一种基于电动汽车及温控负荷需求响应的分层能源系统管理框架。受到激励的电动汽车集群(electric vehicles, EVs)和温控负荷集群(temperature-controlled load clusters, TCLs)能够快速响应负荷聚合商的调度策略,以此减少大量柔性负荷并网对电网产生的冲击。在基于卷积神经网络和长短期记忆网络混合模型对负荷进行预测的基础上,假设负荷聚合商可通过调度可控柔性负荷来减小实际负荷与预测负荷的误差,并根据制定的负荷调度策略与电力运营商之间进行点对点(peer to peer, P2P)电力交易,运用分布式优化方法求解双方可获得的最大利益。对于P2P交易以后剩余的能源需求,建立了系统运行成本、碳排放和风能溢出的多目标优化模型,采用集中优化的二代非支配排序遗传算法(non dominated sorting genetic algorithm-II, NSGA-Ⅱ)求解该模型的帕累托前沿,并在IEEE 30节点系统进行了算例验证。仿真结果表明,在所提出的能源优化调度策略下既能满足电动汽车和温控负荷的功率需求,也给电力系统带来了良好的经济效益和环境效益。     

提高能源效率的主要技术与途径

与1978年相比,2008年我国电力工业通过降低供电煤耗及线损节约了3．8亿tce,减少二氧化碳排放约9．2亿t,减少二氧化硫排放约320万t,为我国节能减排作出了巨大贡献。但未来我国电力工业将随着中国经济的发展而持续增长,其能源消耗量以及二氧化碳、二氧化硫的排放量将呈不断增加的趋势。这将对电力工业的能效提出严峻的挑战。研究提高发电、输电、配电及用电的能效将具有重要的现实意义。介绍了美国发电、输电、配电及用电方面提高能效的先进技术,结合我国发布的行业标准,探讨提高我国发输配用电效率的途径。     

Assessment of Optimal Power Generation Mix Considering Extensive Variable Renewable Energy and Nationwide Power Interchange through Tie Lines

This paper evaluates the optimal power generation mix considering massive deployment of variable renewable energy and regional power interchange. Japan has initiated the feed‐in‐tariff (FIT) and expected the significant introduction of PV and wind power for energy self‐sufficiency and climate change. However, wind power resources in Japan are concentrated mainly in Hokkaido and the Tohoku region, which are remote from electricity‐consuming areas such as Tokyo, and facilitating the considerable deployment of wind power requires the establishment of inter‐regional power transmission lines. Against these backgrounds, we develop an optimal power generation mix model including regional electricity exchange as a large‐scale linear programming model with 10 million variables and 30 million constraints. The calculation results show that regional grid expansion encourages wind power installation in the Hokkaido and Tohoku regions for power supply to the Tokyo area, where PV power and stationary batteries are alternatively replaced. Grid expansion too promotes the shift of PV installation to the Kyushu and Shikoku regions, which have longer sunshine duration, and interchangeably mitigates PV deployment in other regions through the transport of PV power from those two regions.     

Integration of PV and EVs in unbalanced residential LV networks and implications for the smart grid and advanced metering infrastructure deployment

Voltage unbalance is a relevant problem that causes a less efficient operation of the system due to higher energy losses and lower hosting capacity. Unbalance has often been neglected by distribution system operators due to the lack of monitoring data in the low voltage (LV) grid. However, the massive deployment of smart metering in recent years in many countries provides very valuable information to detect unbalance. Moreover, in the current context of increasing presence of single-phase distributed energy resources connected to LV networks, such as electric vehicles (EVs) and photovoltaic (PV) generation, unbalance is bound to increase.This article investigates the technical impact of future integration of EV and PV in LV unbalanced networks. This paper has assessed the daily energy losses and voltage problems as load unbalance gradually increases, based on load flow analysis on an hourly basis, considering residential demand and homogeneously distributed EV and PV. The analysis has been carried out for several rural and semi-rural LV networks and various scenarios of demand level and penetration degree of EV and PV. The three-phase load flow analysis is computed using the forward-backward sweep algorithm.Furthermore, this work discusses the implications for the deployment of supervision and monitoring solutions based on advanced metering infrastructure (AMI). Their implementation should be prioritized in more loaded and longer networks where high integration of distributed energy resources is expected so that unbalance can be detected and corrective actions can be applied.     

风电和电动汽车组成虚拟电厂参与电力市场的博弈模型

风电与电动汽车(EV)等储能装置联合运行,有助于缓解风电不确定性对电网带来的影响。为了研究风电商与EV聚合商以合作模式组成虚拟电厂(VPP)参与电力市场投标竞争对市场均衡结果的影响,基于寡头竞争的博弈均衡理论,分别建立风电商和EV聚合商以VPP合作模式参与投标竞争,以及以非合作模式独立参与投标竞争的电力市场多时段随机博弈均衡模型,采用场景生成与削减技术计入风速不确定性,并引入投标偏差惩罚机制。根据合作博弈理论,采用Shapley值法对VPP合作收益在风电商和EV聚合商之间进行分配。最后,算例分析验证了模型的合理性和有效性,并表明风电商和EV聚合商以VPP合作模式参与投标竞争时,能有效减少投标偏差,并能增加风电商和EV聚合商各自的利润,因而风电商和EV聚合商具有自愿组成VPP参与电力市场竞争的动机。     

含电动汽车充电站的风光互补系统容量优化配置

电动汽车与新能源的综合利用是当前研究的热点问题。在微电网模式下,如何确定电动汽车充电基础设施与风光互补系统的容量配比,是值得探讨的问题。在考虑电动汽车用电需求的前提下,同时发挥电动汽车换电模式所具备的储能能力,以系统投资成本、运行成本和电量不足损失成本综合最低为目标,并考虑风光系统、充放电机和动力电池的约束条件,构造了一种含电动汽车充电站的风光互补系统容量优化配置模型。采用微分进化算法求解,可获得含风机、光伏电池、动力电池和充放电机的最优容量配置结果。最后,针对某地区的系统规划算例进行了求解与分析,结果验证了模型的合理性。     

Impact of Climate Change on Energy Production,Distribution, and Consumption in Russia

An assessment of the overall impact of the observed and expected climatic changes on energy production, distribution, and consumption in Russia is presented. Climate model results of various complexity and evaluation data on the vulnerability of various energy production sectors to climate change are presented. It is shown that, due to the increase of air temperature, the efficiency of electricity production at thermal and nuclear power plants declines. According to the climate model results, the production of electricity at TPPs and NPPs by 2050 could be reduced by 6 billion kW h due to the temperature increase. At the same time, as a result of simulation, the expected increase in the rainfall amount and river runoff in Russia by 2050 could lead to an increase in the output of HPP by 4–6% as compared with the current level, i.e., by 8 billion kW h. For energy transmission and distribution, the climate warming will mean an increase in transmission losses, which, according to estimates, may amount to approximately 1 billion kW h by 2050. The increase of air temperature in summer will require higher energy consumption for air conditioning, which will increase by approximately 6 billion kW h by 2050. However, in total, the optimal energy consumption in Russia, corresponding to the postindustrial level, will decrease by 2050 by approximately 150 billion kW h as a result of climate- induced changes. The maximum global warming impact is focused on the heat demand sector. As a result of a decrease in the heating degree-days by 2050, the need for space heating is expected to fall by 10–15%, which will cause a fuel conservation sufficient for generating approximately 140 billion kW h of electricity. Hence, a conclusion about the positive direct impact of climate change on the Russia’s energy sector follows, which is constituted in the additional available energy resource of approximately 300 billion kW h per year.