基于时序生产模拟仿真的宁夏电网风光优化配比研究

宁夏风和光资源丰富,风电和光伏发电发展并驾齐驱。建立了含新能源发电的电网年度时序生产模拟仿真模型,以电网节能减排效益最大为目标,综合考虑了风光出力特性、负荷特性、机组调峰特性、不同种类供热机组热电耦合特性等因素。在建立模型的基础上,仿真研究了2015年宁夏电网新能源发电接纳能力,得到了综合考虑新能源限电率和电网节能减排效益的风光优化配比。该结果可为地区风电和光伏发电建设、电力系统调度以及政府相关政策制定提供指导。     

Planning of distributed renewable energy systems under uncertainty based on statistical machine learning

The development of distributed renewable energy, such as photovoltaic power and wind power generation, makes the energy system cleaner, and is of great significance in reducing carbon emissions. However, weather can affect distributed renewable energy power generation, and the uncertainty of output brings challenges to uncertainty planning for distributed renewable energy. Energy systems with high penetration of distributed renewable energy involve the high-dimensional, nonlinear dynamics of large-scale complex systems, and the optimal solution of the uncertainty model is a difficult problem. From the perspective of statistical machine learning, the theory of planning of distributed renewable energy systems under uncertainty is reviewed and some key technologies are put forward for applying advanced artificial intelligence to distributed renewable power uncertainty planning.     

Letter to the Editor: Stability Concerns in Smart Grid with Emerging Renewable Energy Technologies

Abstract

The environmental concerns due to conventional power plants have given impetus for widespread utilization of renewable energy based distributed generation technologies. As a consequence, the concepts pertaining to a smart grid with advanced functional architecture are evolving to incorporate these technologies. Many such smart grid strategies are focused on maximum utilization of renewable energy sources compared to conventional fossil or nuclear fuels for meeting real-time load demand. The diverse characteristics of renewable energy based distributed generation technologies compared to conventional power plants have led to many operational stability concerns for the smart grid. This article discusses these stability concerns in smart grid with distributed generation technologies.     

基于动态成本曲线的可再生能源发电目标分解模型

为了解决可再生能源发电国家目标与省域目标的衔接问题,结合中国实际,提出一种基于动态成本曲线的可再生能源发电目标分解模型。模型首先给出了可再生能源发电行业的静态成本曲线,考虑技术进步及外部性的影响,生成动态成本曲线。给出可再生能源发电总量目标情景,依据目标分解模型,可以将总量目标分解到各个区域、各种技术,并给出各种技术的优先发展区域,各区域的优先发展技术。通过福建案例验证该模型的正确性和有效性,到2025年,该省的经济开发量可达2358万kW,碳减排量可达8720万t/a。福州、漳州、泉州和宁德市的可再生能源发电经济装机容量分别达到435万、371万,350万和366万kW装机。     

Assessing effects of renewable deployment on emissions in the Saudi power sector until 2040 using integer optimization

We quantify the impacts of renewable deployment on carbon emissions and natural gas supply in the Saudi power sector. A capacity expansion model, which simultaneously considers generation and transmission builds covering a planning horizon up to 2040, was created. The simulated scenarios, which entailed retiring liquid fuels from the Saudi power sector and accounted for different gas prices, consider the following candidate build technologies: nuclear, gas, solar photovoltaics, wind, concentrated solar power with storage, and battery storage. Renewables can reduce carbon emissions by 66 million tons to 114 million tons (25–41 %) by 2040 depending on the gas price. The abatement costs were estimated to range between 20 $/ton and 50 $/ton of carbon dioxide. Within Saudi Arabia, renewable deployment can also defer national gas supply expansion plans but not investments in expanding domestic gas transport capacities. Finally, under certain conditions when deploying significant renewable capacity, better transmission interconnection between regions manages renewable intermittency more cost-effectively than storage deployment.     

Hybrid fuel cells technologies for electrical microgrids

Hybrid systems are characterized by containing two or more electrical generation technologies, in order to optimize the global efficiency of the processes involved. These systems can present different operating modes. Besides, they take into account aspects that not only concern the electrical and thermal efficiencies, but also the reduction of pollutant emissions. There is a wide range of possible configurations to form hybrid systems, including hydrogen, renewable energies, gas cycles, vapour cycles or both. Nowadays, these technologies are mainly used for energy production in electrical microgrids. Some examples of these technologies are: hybridization processes of fuel cells with wind turbines and photovoltaic plants, cogeneration and trigeneration processes that can be configured with fuel cell technologies, etc. This paper reviews and analyses the main characteristics of electrical microgrids and the systems based on fuel cells for polygeneration and hybridization processes.     

CO2 emissions,renewable energy and economic growth in the US

Given the great importance of achieving sustainable economic growth, however, it has been suggested that the replacement for fossil fuels by renewable energy sources can reduce environmental pollution. Renewable energy can decrease emissions caused by economic activities through increasing renewable energy consumption in energy-intensive-polluted sectors, and adopting environmental-friendly technologies in production. Therefore, this paper examines the linkages between energy-related CO2 emissions, economic growth, and renewable energy consumption for the 48 U.S. states over the period 1997–2017 by employing the panel ?xed-effects, the panel-corrected standard errors, the two-step Generalized Method of Moments, and the Method of Moments Quantile Regression with ?xed effects developed by Machado and Silva (2019). The results provide strong evidence of an inverted U-shaped relationship be-tween economic growth and environmental degradation, which known as the Environmental Kuznets Curve. Furthermore, this paper con?rms that renewable energy consumption, electricity prices, and primary energy prices have negative impact on emissions whereas Heating Degree Days have a positive impact on emissions. Moreover, the panel quantile regression models con?rm that the effects of all explanatory variables on CO2 emissions are heterogeneous at different quantiles. The ?ndings of this paper provide evidence of the environmental bene?ts of promoting in renewable energy and suggest policy tools to reduce emissions through energy price mechanisms.     

Optimal use of energy storage systems with renewable energy sources

This article proposes a multi-period optimization to study the technical and economic effects of the placement and use of Renewable Energy Sources (RES) and Energy Storage Systems (ESS) in an electrical network. As the RES penetrations increase, their inherent variability affects the actual amounts of energy dispatched, their contribution to decrease emissions of pollutants and greenhouse gases, and the overall welfare effects they may have. Moreover, to better harness the energy from renewable sources, both new methodologies and technologies need to be adopted, counteracting the variability and uncertainty of these sources. A possible solution to the challenges of RES adoption is the coupling to energy storage sources, either as dedicated facilities on the supply side, or supporting the accommodation of loads to the available generation on the demand side. This paper suggests an algorithm for network dispatch, aimed at answering some of fundamental changes in the way the system is managed and discusses analytical characteristics of the optimal solution.The proposed methodology is applied to a case study. Four scenarios are analyzed in their dispatches, estimating the welfare effects on the participants in the wholesale market for a modified IEEE 30-bus network with wind energy as the RES in penetrations close to 15%. The policy implications from the results obtained prove that, first, ESS can decrease the ramping necessary for load following, but not necessarily increase the amount of wind energy used, and second, congestion patterns in the electrical network play a crucial role in the final effectiveness of the RES and ESS. These are important insights into an ongoing debate on how to direct storage and renewable energy investments for a low carbon economy.     

考虑碳排放成本的多能互补微能源网储能装置优化运行

随着综合能源管理技术的成熟,建立含大比例可再生能源和储能装置的多能互补微能源网成为发展趋势。近年来,我国在进行能源结构调整,碳排放控制力度逐步提升。因此在考虑碳排放成本的基础上,以微能源网日运行成本最低为目标建立经济运行模型,对储能的充放电策略进行调整,并采用商业软件CPLEX进行求解。以某一实际微能源网为例验证所提模型的有效性,分析了两种储能容量和功率配置对微能源网运行成本的影响。算例结果表明,所建模型纳入了碳排放成本的影响,在保障可再生能源消纳的前提下,对微能源网内的多种能源和储能装置充放电策略进行了优化,实现微能源网运行成本最低的同时达到多能互补的效果。     

考虑风光储互补与工作负载分配的数据中心优化调度

随着 “双碳”目标的推进,数据中心新能源微电网不断发展,为减少数据中心综合运行成本与碳排放,提出了一种考虑风光储互补与工作负载分配的数据中心多目标优化调度模式。利用风光储互补在一定程度上解决新能源出力的间歇性;利用负载分配策略,使数据中心的用能需求尽可能与新能源出力曲线相匹配,提高新能源的利用率,减少碳排放。最后通过算例分析该模式下的优化调度结果,并比较不同运行模式下,数据中心的综合运行成本、碳排放量和新能源利用率。结果表明,该模式可明显降低运行成本与碳排放并提高新能源利用率。     

Generalized Estimation of Average Displaced Emissions by Wind Generation

This paper presents a generalized approach for the estimation of average displaced or avoided system emissions by intermittent renewable sources such as wind. The quantification of the environmental benefits of renewable energy projects is of utmost importance for: 1) the creation and trading of certified emission reductions or credits and 2) the design of green energy government policies that recognize the contribution of renewable energy for the reduction of national/regional carbon emissions. The proposed approach is based on the correlation factor between time-evolution of system marginal emissions and wind power generation. Results show that average displaced emissions by wind generation can be estimated once typical power system dispatch data and regional wind generation is available, thus circumventing the use of proprietary power dispatch models. The main objective of this work is to contribute towards the development of simplified methodologies that will facilitate the assessment of renewable energy projects in a variety of regulatory and regional settings.     

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.     

清洁发展机制与我国可再生能源发电

结合我国可再生能源发电的实际情况和清洁发展机制（CDM）的规则,从各方面分析了CDM在可再生能源发电中的潜力和预期效益。我国可再生能源发电潜力巨大,而且具备减排成本低等多重比较优势,但同时也存在着发电成本高等制约因素。通过CDM项目的开发和实施,可以带来环境、经济、社会等多方面的效益。     

基于改进条件生成对抗网络的可控场景生成方法

可再生能源发电具有较强的随机性和波动性,为实现高效可靠的场景建模,提出一种基于改进条件生成对抗网络的可控场景生成方法。提出基于条件生成对抗网络的场景生成框架,结合Transformer的全局注意力机制以及常规卷积和深度可分离卷积的局部泛化机制,设计适用于提取可再生能源发电不同维度特征的网络结构;利用条件生成对抗网络模型建立低维气象特征隐空间和高维可再生能源发电数据之间的映射关系,提出一种可控场景生成方法,并建立随机场景生成、场景约减、极端场景生成和连续日场景生成4种生成策略。基于实际光伏、风电数据和气象数据的仿真结果表明,所提模型与方法能够有效学习可再生能源发电的随机性、时序性、波动性及空间相关性,实现对不同策略下场景的可控生成。     

污水源热泵空调系统节能减排性能分析

暖通空调能耗存建筑能耗中占较大比重．且空凋能效较低,通过利用可冉生能源,特别是城市污水源供热供冷．可以有效节约能源,减降污染物排放量。介绍了污水源空渊系统的工作原理,对其节能减排性能进行分析与计算．污水源热泵空调系统节能减排效果十分显著。     

计及P2G和CCS的园区级电-热-气综合能源系统多目标优化

碳捕集和可再生能源利用已经成为减少碳排放的重要措施。但捕集到的二氧化碳利用方式不明确,弃风弃光现象频发,限制了上述2种措施的减排效果。文章通过耦合电转气(power to gas, P2G)技术和碳捕集系统(carbon capture system,CCS),将其扩展到园区级电-热-气综合能源系统中,建立了一种高比例可再生能源渗透水平下的经济低碳多目标优化模型,在多情景下模拟分析了该综合能源系统在某工业园区的运行效果。结果表明,该耦合能源系统排放的大部分CO₂可以被有效捕获并送往P2G装置用于合成燃气,为利用CO₂提供了新的思路,同时显著提高了系统对可再生能源的消纳能力。对P2G设备容量的敏感性分析表明,单纯增加P2G容量虽然能减少弃能率,但会增加碳排放,因此对P2G的容量规划应当综合考虑可再生能源可用量与碳排放之间的关系。     

考虑热网约束和碳交易的多区域综合能源系统优化调度

为了提高可再生能源消纳率及减少发电过程中碳排放对环境的污染,提出了一种考虑热网约束和碳交易的多区域综合能源系统优化调度模型。首先,通过热网管道和节点的基本方程描述热网系统,建立区域综合能源系统与热网耦合模型;其次,分析国内外两种碳交易机制的特点,建立以系统运行成本、碳交易成本和可再生能源消纳惩罚成本之和最小为目标函数的低碳经济调度模型;最后,以冬季某热网连接的多区域综合能源系统为例,采用混合整数线性规划对模型进行求解,分析2种碳交易机制对系统经济运行和碳排放的影响。结果表明,通过热网连接多个区域综合能源系统,能充分利用区域间负荷的互补特性,减少系统碳排放,提高可再生能源的消纳率。     

太阳能技术及其并网特性综述

太阳能是继风能之后又一个无污染、高效率的新能源,有巨大的应用前景。文章介绍了光伏太阳能技术和热力太阳能技术的原理和特性。光伏太阳能技术通常以较小的规模在配电层面上使用,而热力太阳能技术则以较大的规模在输电层面上使用。文章指出由于技术上差异所致两种太阳能接入电网策略不同之处。根据美国新能源发展的策略和经验结合中国的情况提出对中国太阳能技术发展的看法和建议。     

Exploring the cost implications of increased renewable energy for the U.S. power system

Over the last decade, the fraction of annual U.S. electricity generation for renewable energy has doubled from 10 % to 20 %. This growth has been driven by several factors, including technology cost reductions and policy support. The share of renewable generation is projected to increase over time. Reference case scenarios from four different organizations show least-cost U.S. electricity buildouts with renewable energy generation fractions of 31–36 % by 2030 and 40–65 % by 2050. Using a capacity expansion modeling tool, we investigate how changing the amount of renewable energy from the least-cost solution impacts the cost of building and operating the electricity system. The relationship between system cost and renewable energy generation fraction is non-linear. Small deviations near the least-cost solution have minimal cost impacts (changing the renewable energy penetration by +/- 5% results in system cost changes of less than 1%), while similar deviations that are farther from the least-cost solution can result in large cost changes. Increased levels of RE lead to lower absolute emissions, and we evaluate the trade-offs between emissions savings and system costs for higher and lower levels of RE penetration.     

Understanding the impact of state-level financial incentives on the deployment of renewable energy at colleges and universities

Over 400 colleges and universities have signed carbon reduction pledges through Second Nature. Nonetheless, a review of their greenhouse gas inventories shows that many universities continue to show limited or no progress in terms of renewable energy deployment and generation. One study from 2019 shows that it is now cheaper to build new renewable energy projects than it is to continue operating existing coal-fired power plants (for 74% of existing fleet). Meanwhile, another study shows that universities rarely achieve a positive economic net benefit when deploying solar on their campuses, despite the cost declines in solar and rising utility prices. This same study finds that these same projects accrue a positive social and environmental net benefit for the surrounding community that outweighs current economic subsidies, implying that increased subsidies for college solar deployment would, more often than not, pass cost-benefit analysis. This present study builds on the previous two studies and explores the question of whether state-level financial incentives have a meaningful impact on the deployment of renewable energy on college campuses. The thesis guiding this research is that universities in states with certain state-level financial incentives will be more successful in deploying renewable energy and in meeting their clean energy goals. The financial incentives being studied are limited to grants, tariffs, net metering (at retail rates), and solar renewable energy credits. This research paper shows that the presence of these financial incentives is positively correlated with renewable energy deployment across colleges, providing a starting map for policy-makers interested in supporting universities’ renewable energy deployment in their states.