Forecasting the Impact of CCGT-CCS on the UK’s Electricity Market by LCOE

To achieve the target for building a low-carbon economy, the UK will have to build more low-carbon power plants to reduce carbon dioxide emissions from electricity generation. However, renewable energy is difficult to meet the increasing energy demand and keep lights on. This limitation of renewable could be solved by coal and gas-fired power station fitted with carbon capture storage (CCS) technology. CCS technology could capture up to 90% of carbon dioxide from emissions and allow fossil fuel power station to provide continuous low-carbon electricity power. This paper presents the levelised cost of electricity of CCGT with CCS and compared with renewable technology to forecast the impact of CCGT with CCS on the UK’s electricity market.

Research on Interpolation Method for Missing Electricity Consumption Data

Missing value is one of the main factors that cause dirty data.Without high-quality data,there will be no reliable analysis results and precise decision-making.Therefore,the data warehouse needs to integrate high-quality data consistently.In the power system,the electricity consumption data of some large users cannot be normally collected resulting in missing data,which affects the calculation of power supply and eventually leads to a large error in the daily power line loss rate.For the problem of missing electricity consumption data,this study proposes a group method of data handling(GMDH)based data interpolation method in distribution power networks and applies it in the analysis of actually collected electricity data.First,the dependent and independent variables are defined from the original data,and the upper and lower limits of missing values are determined according to prior knowledge or existing data information.All missing data are randomly interpolated within the upper and lower limits.Then,the GMDH network is established to obtain the optimal complexity model,which is used to predict the missing data to replace the last imputed electricity consumption data.At last,this process is implemented iteratively until the missing values do not change.Under a relatively small noise level(α=0.25),the proposed approach achieves a maximum error of no more than 0.605%.Experimental findings demonstrate the efficacy and feasibility of the proposed approach,which realizes the transformation from incomplete data to complete data.Also,this proposed data interpolation approach provides a strong basis for the electricity theft diagnosis and metering fault analysis of electricity enterprises.

Harnessing overlapped temperature-salinity gradient in solar-driven interfacial seawater evaporation for efficient steam and electricity generation

Solar-driven interfacial water evaporation(SIWE)offers a superb way to leverage concentrated solar heat to minimize energy dissipation during seawater desalination.It also engenders overlapped temperaturesalinity gradient(TSG)between water-air interface and adjacent seawater,affording opportunities of harnessing electricity.However,the efficiency of conventional SIWE technologies is limited by significant challenges,including salt passivation to hinder evaporation and difficulties in exploiting overlapped TSG simultaneously.Herein,we report self-sustaining hybrid SIWE for not only sustainable seawater desalination but also efficient electricity generation from TSG.It enables spontaneous circulation of salt flux upon seawater evaporation,inducing a self-cleaning evaporative interface without salt passivation for stable steam generation.Meanwhile,this design enables spatial separation and simultaneous utilization of overlapped TSG to enhance electricity generation.These benefits render a remarkable efficiency of90.8%in solar energy utilization,manifesting in co-generation of solar steam at a fast rate of 2.01 kg m^(-2)-h^(-1)and electricity power of 1.91 W m^(-2)with high voltage.Directly interfacing the hybrid SIWE with seawater electrolyzer constructs a system for water-electricity-hydrogen co-generation without external electricity supply.It produces hydrogen at a rapid rate of 1.29 L h^(-1)m^(-2)and freshwater with 22 times lower Na+concentration than the World Health Organization(WHO)threshold.

Electricity Carbon Quota Trading Scheme based on Certificateless Signature and Blockchain

The carbon tradingmarket can promote“carbon peaking”and“carbon neutrality”at low cost,but carbon emission quotas face attacks such as data forgery,tampering,counterfeiting,and replay in the electricity trading market.Certificateless signatures are a new cryptographic technology that can address traditional cryptography’s general essential certificate requirements and avoid the problem of crucial escrowbased on identity cryptography.However,most certificateless signatures still suffer fromvarious security flaws.We present a secure and efficient certificateless signing scheme by examining the security of existing certificateless signature schemes.To ensure the integrity and verifiability of electricity carbon quota trading,we propose an electricity carbon quota trading scheme based on a certificateless signature and blockchain.Our scheme utilizes certificateless signatures to ensure the validity and nonrepudiation of transactions and adopts blockchain technology to achieve immutability and traceability in electricity carbon quota transactions.In addition,validating electricity carbon quota transactions does not require time-consuming bilinear pairing operations.The results of the analysis indicate that our scheme meets existential unforgeability under adaptive selective message attacks,offers conditional identity privacy protection,resists replay attacks,and demonstrates high computing and communication performance.

Rational design of natural leather-based water evaporator for electricity generation and functional applications

In recent years,water evaporation-induced electricity has attracted a great deal of attention as an emerging green and renewable energy harvesting technology.Although abundant materials have been developed to fabricate hydrovoltaic devices,the limitations of high costs,inconvenient storage and transport,low environmental benefits,and unadaptable shape have restricted their wide applications.Here,an electricity generator driven by water evaporation has been engineered based on natural biomass leather with inherent properties of good moisture permeability,excellent wettability,physicochemical stability,flexibility,and biocompatibility.Including numerous nano/microchannels together with rich oxygen-bearing functional groups,the natural leather-based water evaporator,Leather_(Emblic-NPs-SA/CB),could continuously produce electricity even staying outside,achieving a maximum output voltage of∼3 V with six-series connection.Furthermore,the leather-based water evaporator has enormous potential for use as a flexible self-powered electronic floor and seawater demineralizer due to its sensitive pressure sensing ability as well as its excellent photothermal conversion efficiency(96.3%)and thus fast water evaporation rate(2.65 kg m^(−2)h^(−1)).This work offers a new and functional material for the construction of hydrovoltaic devices to harvest the sustained green energy from water evaporation in arbitrary ambient environments,which shows great promise in their widespread applications.

Analyzing the Wind-Dominant Electricity Market under Coexistence of Regulated and Deregulated Power Trading

Currently,both regulated and deregulated power trading exist in China’s power system,which has caused imbalanced funds in the electricity market.In this paper,a simulation analysis of the electricity market with wind energy resources is conducted,and the calculation methods of unbalanced funds are investigated systematically.In detail,the calculation formulas of unbalanced funds are illustrated based on their definition,and a two-track electricity market clearing model is established.Firstly,the concept of the dual-track system is explained,and the specific calculation formulas of various types of unbalanced funds are provided.Next,considering the renewable energy consumption,the market clearing model based on DC power flow is constructed and solved;by combining fitting methods of mid-and long-term curves,the unbalanced funds are calculated based on clearing results and formulas.

Optimizing Household Wastes (Rice, Vegetables, and Fruit) as an Environmentally Friendly Electricity Generator

The high consumption of electricity and issues related to fossil energy have triggered an increase in energy prices and the scarcity of fossil resources.Consequently,many researchers are seeking alternative energy sources.One potential technology,the Microbial Fuel Cell(MFC)based on rice,vegetable,and fruit wastes,can convert chemical energy into electrical energy.This study aims to determine the potency of rice,vegetable,and fruit waste assisted by Cu/Mg electrodes as a generator of electricity.The method used was a laboratory experiment,including the following steps:electrode preparation,waste sample preparation,incubation of the waste samples,construction of a reactor using rice,vegetable,and fruit waste as a source of electricity,and testing.The tests included measuring electrical conductivity,electric current,voltage,current density,and power density.Based on the test results,the maximum current and voltage values for the fruit waste samples were 5.53 V and 11.5 mA,respectively,with a current density of 2.300 mA/cm^(2) and a power density of 12.719 mW/cm^(2).The results indicate the potential for a future development.The next step in development involves determining the optimum conditions for utilizing of rice,vegetable,and fruit waste.The results of the electrical conductivity test on rice,vegetable,and fruit waste samples were 1.51,2.88,and 3.98 mS,respectively,with the highest electrical conductivity value found in the fruit waste sample.

Analysis of Electricity Consumption Pattern Clustering and Electricity Consumption Behavior

Studying user electricity consumption behavior is crucial for understanding their power usage patterns.However,the traditional clustering methods fail to identify emerging types of electricity consumption behavior.To address this issue,this paper introduces a statistical analysis of clusters and evaluates the set of indicators for power usage patterns.The fuzzy C-means clustering algorithm is then used to analyze 6 months of electricity consumption data in 2017 from energy storage equipment,agricultural drainage irrigation,port shore power,and electric vehicles.Finally,the proposed method is validated through experiments,where the Davies-Bouldin index and profile coefficient are calculated and compared.Experiments showed that the optimal number of clusters is 4.This study demonstrates the potential of using a fuzzy C-means clustering algorithmin identifying emerging types of electricity consumption behavior,which can help power system operators and policymakers to make informed decisions and improve energy efficiency.

Energy Storage Operation Modes in Typical Electricity Market and Their Implications for China

As the Chinese government proposes ambitious plans to promote low-carbon transition,energy storage will play a pivotal role in China’s future power system.However,due to the lack of a mature electricity market environment and corresponding mechanisms,current energy storage in China faces problems such as unclear operational models,insufficient cost recovery mechanisms,and a single investment entity,making it difficult to support the rapid development of the energy storage industry.In contrast,European and American countries have already embarked on certain practices in energy storage operation models.Through exploration of key issues such as investment entities,market participation forms,and cost recovery channels in both front and back markets,a wealth of mature experiences has been accumulated.Therefore,this paper first summarizes the existing practices of energy storage operation models in North America,Europe,and Australia’s electricity markets separately from front and back markets,finding that perfect market mechanisms and reasonable subsidy policies are among the main drivers for promoting the rapid development of energy storage markets.Subsequently,combined with the actual development of China’s electricity market,it explores three key issues affecting the construction of costsharing mechanisms for energy storage under market conditions:Market participation forms,investment and operation modes,and cost recovery mechanisms.Finally,in line with the development expectations of China’s future electricitymarket,suggestions are proposed fromfour aspects:Market environment construction,electricity price formation mechanism,cost sharing path,and policy subsidy mechanism,to promote the healthy and rapid development of China’s energy storage industry.

Simulation and Analysis of Cascading Faults in Integrated Heat and Electricity Systems Considering Degradation Characteristics

Cascading faults have been identified as the primary cause of multiple power outages in recent years.With the emergence of integrated energy systems(IES),the conventional approach to analyzing power grid cascading faults is no longer appropriate.A cascading fault analysis method considering multi-energy coupling characteristics is of vital importance.In this study,an innovative analysis method for cascading faults in integrated heat and electricity systems(IHES)is proposed.It considers the degradation characteristics of transmission and energy supply com-ponents in the system to address the impact of component aging on cascading faults.Firstly,degradation models for the current carrying capacity of transmission lines,the water carrying capacity and insulation performance of thermal pipelines,as well as the performance of energy supply equipment during aging,are developed.Secondly,a simulation process for cascading faults in the IHES is proposed.It utilizes an overload-dominated development model to predict the propagation path of cascading faults while also considering network islanding,electric-heating rescheduling,and load shedding.The propagation of cascading faults is reflected in the form of fault chains.Finally,the results of cascading faults under different aging levels are analyzed through numerical examples,thereby verifying the effectiveness and rationality of the proposed model and method.

基于LCOE原理的光伏电站最优容配比分析

容配比是影响光伏电站初投资与后期经济性的关键因素之一。容配比过低或过高都将会导致系统运行效率低、度电成本提高,直接影响发电效益。因此,在光伏电站设计过程中最优容配比的选择至关重要。本文以缅甸某光伏电站为研究对象,以LCOE最优为原则,对比分析不同容配比参数对电站经济性的影响,进而确定项目最优容配比,提高光伏电站整体经济性。

Electricity as an Energy Vector: A Performance Comparison with Hydrogen and Biodiesel in Italy

This study presents a comparative analysis of electricity, hydrogen, and biodiesel as energy vectors, with a focus on powering an aluminum smelter in southern Italy. It evaluates these vectors in terms of efficiency, land requirements for carbon-neutral energy production, and capital expenditure, providing insights throughout the entire supply chain (upstream, midstream, and downstream) into their feasibility for industrial applications. The research reveals that biodiesel, despite being carbon neutral, is impractical due to extensive land requirements and lower efficiency if compared to other vectors. Hydrogen, downstream explored in two forms as thermal power generation and fuel cell technology, shows lower efficiency and higher capital expenditure compared to electricity. Additionally, green hydrogen production’s land requirements significantly exceed those of electricity-based systems. Electricity emerges as the most viable option, offering an overall higher efficiency, lower land requirements for its green production, and comparatively lower capital expenditure. The study’s findings highlight the importance of a holistic assessment of energy vectors, considering economic, environmental, and practical aspects along the entire energy supply chain, especially in industrial applications where the balance of these factors is crucial for long-term sustainability and feasibility. This comprehensive analysis provides valuable guidance for similar industrial applications, emphasizing the need for a balanced approach in the selection of energy vectors.

Valorization of Agricultural Residues for Hydrogen-Based Electricity Generation towards Circular Bioeconomy

Global crises, notably climate shocks, degraded ecosystems, and growing energy demand, enforce sustainable production and consumption pathways. A circular bioeconomy offers the opportunities to actualize resource and eco-efficiency enhancement, valorization of waste streams, reduction of fossil energy and greenhouse gas (GHG) emissions. Albeit biomass resources are a potential feedstock for bio-hydrogen (bio-H2) production, Ghana’s agricultural residues are not fully utilized. This paper examines the economic and environmental impact of bio-H2 electricity generation using agricultural residues in Ghana. The bio-H2 potential was determined based on biogas steam reforming (BSR). The research highlights that BSR could generate 2617 kt of bio-H2, corresponding to 2.78% of the global hydrogen demand. Yam and maize residues contribute 50.47% of the bio-H2 produced, while millet residues have the most negligible share. A tonne of residues could produce 16.59 kg of bio-H2 and 29.83 kWh of electricity. A total of 4,705.89 GWh of electricity produced could replace the consumption of 21.92% of Ghana’s electricity. The economic viability reveals that electricity cost is $0.174/kWh and has a positive net present value of $2135550609.45 with a benefit-to-cost ratio of 1.26. The fossil diesel displaced is 1421.09 ML, and 3862.55 kt CO2eq of carbon emissions decreased corresponding to an annual reduction potential of 386.26 kt CO2eq. This accounts for reducing 10.26% of Ghana’s GHG emissions. The study demonstrates that hydrogen-based electricity production as an energy transition is a strategic innovation pillar to advance the circular bioeconomy and achieve sustainable development goals.

光伏发电项目LCOE的研究与思考

针对光伏发电项目的平准化度电成本(LCOE)展开研究,介绍了其相关概念,分析了其各个影响因素;并有针对性地提出了降低LCOE的相关方法和建议。研究结果显示:1)在目前的市场行情下,光伏发电项目LCOE的3个组成部分中,初始投资部分LCOE的占比最大,达到了72%~76%;2)发电量是项目LCOE非常敏感的影响因素,应寻找光照资源条件较好的地区建设光伏发电项目,并且减少弃光率,提升上网电量,有助于降低项目LCOE;3)折现率对项目LCOE的影响很大,但其与项目本身无关,主要取决于行业的基准收益率和项目投资者设定的项目预期收益率;4)光伏发电系统年衰减率和运维成本对项目LCOE的影响不大;5)寻找融资利率低的贷款可在一定程度上降低项目LCOE;6)降低项目初始投资和提升发电量是降低项目LCOE最主要的两个途径,也是光伏工作者最需要努力的两个方向。以期研究结果可为光伏发电技术的发展和光伏发电项目的开发建设提供参考。

新能源比传统能源成本更高吗?——基于LCOE方法的中国风电与火电成本比较

分别选取风电和传统煤电典型项目,使用LCOE方法比较新能源与传统能源项目的长期投资平均成本,结果表明,即使不考虑新能源发电的鼓励性政策补贴和传统能源发电的环境外部性,风电项目仍比火电项目具有明显的成本优势,否定了对新能源成本过高的固有认识。阻碍我国可再生能源如风电发展的根本因素不是发电成本,而是来自电网消纳和输送能力的制约,目前我国风能资源丰富地区大部分用电负荷较小,大规模风力发电面临当地电网难以消纳的问题。因此,应加大对智能电网建设的投入,加强风电配套设施建设与维护,并在有条件的电力需求中心附近发展风电。

并网光伏发电项目的LCOE分析

围绕并网光伏发电系统的度电成本/平准化电力成本(LCOE)水平进行了分析讨论。针对LCOE的评估依据和测算方法,提出一种适用于我国光伏发电项目的 LCOE评估模型。利用该模型对影响LCOE的几个典型因素进行了敏感性分析;测算了我国光伏发电项目的 LCOE水平;预测了光伏发电项目的 LCOE发展。

基于LCOE模型的光伏发电经济效益分析:以宜昌农村地区光伏扶贫电站项目为例

光伏发电是我国重要的清洁能源发展战略,也是资产收益扶贫的重要方式.为了探讨光伏发电项目对政策的依赖性及其在经济上的可持续性,采用平准化度电成本(LCOE)模型开展研究,并开发出平准化度电净现值(LNPVE)模型用于研究光伏发电项目的长期经济效益及其影响因素.将上网电价与补贴作为效益指标引入LCOE模型,即得到LNPVE,LNPVE为折现度电收入和折现度电成本之差.LNPVE模型不仅能将政策因素引入经济效益分析中,同时还能考虑效益变动,从而分析光伏发电项目的经济可持续性.以宜昌市长阳土家族自治县渔峡口镇村级光伏扶贫电站项目为案例的分析表明,从LCOE模型结果来看,案例项目能够实现经济效益;然而从LNPVE模型结果来看,现行补贴上网电价下案例项目的长期经济效益仍存在不确定性,且这种不确定性随着光伏发电上网电价补贴“退坡”政策的出台而有所强化.敏感性分析结果表明,影响案例项目经济效益的首要因素是技术因素,其次是政策因素,再者是经济因素.若案例项目以无补贴标杆电价平价上网,则需将单位造价降低19.3%或者年利用小时数提高14.8%;若要进一步实现以燃煤发电上网电价平价上网,则需将单位造价降低97.0%或者年利用小时数提高182.1%.因此,应当针对光伏发电特别是村级光伏扶贫项目实施必要的电价补贴,将补贴“退坡”与提高光伏发电效率相结合,并将有针对性地提高补贴效率作为光伏电价补贴的重点,同时高度重视技术改进及推广应用和运营维护的成本降低及质量提高,以持续实现光伏发电项目的经济效益.

基于LCOE的分布式光伏发电并网效益分析

为供应低碳可靠的电能,分布式光伏发电并网发展具有显著意义。结合核证减排单位收入因子,改进度电成本模型,并对度电成本的影响因素作敏感性分析;分析了包括贷款行为等激励机制对项目经济效益的影响;基于独立发电商和配电公司角度,通过实例全面分析了典型运营模式下的并网发电效益。结果表明,分布式光伏发电给配电公司同时带来负向收益和正向收益,自发自用模式能为独立投资商带来更高收益;发电量的变化对度电成本影响最大,在考虑核证减排单位(CERs)收入后,有效光照小时数和光伏组件衰减率对平准化电力成本(LCOE)的影响在增大;碳排放效益对项目的经济效益有一定的影响,碳交易市场的完善和有效的激励机制将推动光伏产业的发展。

基于LabVIEW的拖拉机电气故障诊断系统设计

设计了一种基于LabVIEW的拖拉机电气故障诊断系统,其采用模块化设计,可以自动检测和诊断拖拉机的电气故障,并提供可视化的诊断结果。系统由数据采集模块、信号处理模块、故障诊断模块和用户界面模块组成。数据采集模块负责采集拖拉机各个部件的电气参数数据,信号处理模块对采集到的数据进行处理和分析,故障诊断模块通过分析处理后的数据来判断拖拉机是否存在故障,并给出相应的诊断结果,用户界面模块提供友好的交互界面。试验结果表明:系统可以准确地诊断拖拉机的电气故障,具有良好的应用前景和推广价值。

基于LCOE地图的斋堂岛海域潮流能发电站规划选址研究

基于LCOE地图新工具,通过将Delft 3D潮流数值模型与经济参数LCOE相结合,将资源可利用性和经济性结合来进行潮流能发电站的规划选址,并结合LCOE地图参数的变化,对比分析不同参数对潮流能发电成本的影响。结果表明:斋堂岛东南部海域是规划潮流能发电站较为理想的区域;提高功率系数和降低建设成本是降低潮流能发电成本应首先考虑的因素。