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Sensitivity analysis to reduce duplicated features in ANN training for district heat demand prediction

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Energy and AI 2020年第2期2卷 63-73页

作者： Si Chen yaxing ren Daniel Friedrich Zhibin Yu James Yu James Watt School of Engineering The University of GlasgowGlasgow G128QQUK School of Engineering The University of EdinburghEdinburgh EH93FBUK SP Distribution PLC Glasgow G720HTUK

Artificial neural network(ANN)has become an important method to model the nonlinear relationships between weather conditions,building characteristics and its heat *** to the large amount of training data re-quired for ANN training,data reduction and feature selection are important to simplify the ***,in building heat demand prediction,many weather-related input variables contain duplicated *** paper develops a sensitivity analysis approach to analyse the correlation between input variables and to detect the variables that have high importance but contain duplicated *** proposed approach is validated in a case study that predicts the heat demand of a district heating network containing tens of buildings at a university *** results show that the proposed approach detected and removed several unnecessary input variables and helped the ANN model to reduce approximately 20%training time compared with the traditional methods while maintaining the prediction *** indicates that the approach can be applied for analysing large num-ber of input variables to help improving the training efficiency of ANN in district heat demand prediction and other applications.

关键词： Building heat demand prediction Statistical modelling Artificial neural network Sensitivity analysis Feature selection

Prediction of office building electricity demand using artificial neural network by splitting the time horizon for different occupancy rates

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Energy and AI 2021年第3期5卷 159-170页

作者： Si Chen yaxing ren Daniel Friedrich Zhibin Yu James Yu James Watt School of Engineering the University of GlasgowGlasgow G128QQUK School of Engineering The University of EdinburghEdinburgh EH93FBUK SP Distribution PLC Glasgow G720HTUK

Due to the impact of occupants’activities in buildings,the relationship between electricity demand and ambient temperature will show different trends in the long-term and short-term,which show seasonal variation and hourly variation,*** makes it difficult for conventional data fitting methods to accurately predict the long-term and short-term power demand of buildings at the same *** order to solve this problem,this paper proposes two approaches for fitting and predicting the electricity demand of office *** first proposed approach splits the electricity demand data into fixed time periods,containing working hours and non-working hours,to reduce the impact of occupants’*** finding the most sensitive weather variable to non-working hour electricity demand,the building baseload and occupant activities can be predicted *** second proposed approach uses the artificial neural network(ANN)and fuzzy logic techniques to fit the building baseload,peak load,and occupancy rate with multi-variables of weather *** this approach,the power demand data is split into a narrower time range as no-occupancy hours,full-occupancy hours,and fuzzy hours between them,in which the occupancy rate is varying depending on the time and weather *** proposed approaches are verified by the real data from the University of Glasgow as a case *** simulation results show that,compared with the traditional ANN method,both proposed approaches have less root-mean-square-error(RMSE)in predicting electricity *** addition,the proposed working and non-working hour based regression approach reduces the average RMSE by 35%,while the ANN with fuzzy hours based approach reduces the average RMSE by 42%,comparing with the traditional power demand prediction *** addition,the second proposed approach can provide more information for building energy management,including the predicted baseload,peak load,and occupancy rate,without r

关键词： Building energy Electricity demand prediction Statistical modelling Artificial neural network Occupancy rate

Configurations and Control of Traction Motors for Electric Vehicles:A Review

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Chinese Journal of Electrical Engineering 2017年第3期3卷 1-17页

作者： Saqib Jamshed Rind yaxing ren Yihua Hu Jibing Wang Lin Jiang Department of Electrical Engineering and Electronics The University of LiverpoolL693BXUK Sicher Elevator Co. Ltd.Huzhou 313009China

In recent decades,worldwide global warming and reduction in petroleum resources have accelerated researcher’s attention to produce alternative sustainable and environmentally clean transportation *** of vehicular technology is capable of curbing the environmental pollution problem in an efficient and effective way,due to high efficiency electric motors,development and advancement in the field of power electronic devices,digital signal processing and advanced control *** article presents a comprehensive review on different configurations/architecture of electric vehicles(EVs)and hybrid electric vehicles(HEVs),traction motors for electric propulsion system and high performance speed sensorless control of traction *** basic architecture key components of hybrid vehicle and different power train configurations with respect to applications and limitations are *** integral part of electric propulsion system,traction motor classes for desired operational characteristics and limitations are summarized from a system perspective with the latest *** performance traction motor control techniques are discussed with respect to automotive ***,speed sensorless control techniques research trends as well as an extensive review on rotor speed estimation techniques for robust and efficient sensorless traction drive control are *** article provides state of the art key global trends and tradeoff of various technologies with future trends and potential areas of research.

关键词： Electric vehicle architecture vehicle powertrain configurations traction motors traction drive control motor sensorless control

Key Issues for Modelling, Operation, Management and Diagnosis of Lithium Batteries: Current States and Prospects

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Energy Engineering 2024年第8期121卷 2085-2091页

作者： Bo Yang Yucun Qian Jianzhong Xu yaxing ren Yixuan Chen Faculty of Electric Power Engineering Kunming University of Science and TechnologyKunming650500China State Key Laboratory of Alternate Electrical Power System with renewable Energy Sources North China Electric Power UniversityBeijing102206China School of Engineering University of LincolnLincolnLN67TSUK Department of Electrical and Electronic Engineering The University of Hong KongHong Kong999077China

1 *** the continuous growth of the global population,the energy demand continues to ***,due to the dominance of fossil fuels in global energy and fossil fuels are non-renewable,it has led to the global energy crisis[1].Besides,the use of fossil fuels will generate a mass of air pollutants(e.g.,carbon dioxide,sulfur dioxide,etc.),which will cause serious environmental pollution,climate change[2],*** resolve the aforementioned issues,countries around the world have implemented a variety of measures hoping to fundamentally adjust the global energy structure and achieve sustainable ***,“Paris Agreement”reached in 2015 under the framework of“United Nations Framework Convention on Climate Change”aims to control the increase in the average temperature of the globe to within 2°C below preindustrial levels,and thereafter to peak global greenhouse gas emissions as soon as possible,continuously decreasing thereafter[3].United Kingdom plans to reduce the average exhaust emissions of“new cars”to approximately 50–70 g/km by 20230,which is roughly half of what it is now[4].In addition,China proposed a plan at“United Nations General Assembly”in 2020 to peak carbon dioxide emissions by 2030 and strive to achieve carbon neutrality by *** is a fact that the whole world is committed to changing the current energy structure,protecting the Earth’s ecology,and achieving global sustainable development[5].

关键词： Lithium batteries optimization operation modelling state estimation life prediction fault diagnosis

Comprehensive summary of solid oxide fuel cell control:a state-of-the-art review

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Protection and Control of Modern Power Systems 2022年第1期7卷 523-553页

作者： Bo Yang Yulin Li Jiale Li Hongchun Shu Xinyu Zhao yaxing ren Qiang Li Faculty of Electric Power Engineering Kunming University of Science and TechnologyKunming 650500China School of Management and Economics Kunming University of Science and TechnologyKunming 650500China Warwick Manufacturing Group University of WarwickCoventry CV47ALUK China Southern Power Grid EHV Transmission Company DaliChina.

Hydrogen energy is a promising renewable resource for the sustainable development of *** a key member of the fuel cell(FC)family,the solid oxide fuel cell(SOFC)has attracted a lot of attention because of characteristics such as having various sources as fuel and high energy conversion efficiency,and being *** is a highly coupled,nonlinear,and multivariable complex system,and thus it is very important to design an appropriate control strategy for an SOFC system to ensure its safe,reliable,and efficient *** paper undertakes a comprehen-sive review and detailed summary of the state-of-the-art control approaches of *** approaches are divided into eight categories of control:proportional integral differential(PID),adaptive(APC),robust,model predictive(MPC),fuzzy logic(FLC),fault-tolerant(FTC),intelligent and *** SOFC control approaches are carefully evalu-ated in terms of objective,design,application/scenario,robustness,complexity,and ***,five perspectives are proposed for future research directions.

关键词： Solid oxide fuel cell Control Hydrogen energy Artificial intelligence

Key Optimization Issues for renewable Energy Systems under Carbon-Peaking and Carbon Neutrality Targets:Current States and Perspectives

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Energy Engineering 2022年第5期119卷 1789-1795页

作者： Bo Yang Zhengxun Guo JingboWang Chao Duan yaxing ren Yixuan Chen Faculty of Electric Power Engineering Kunming University of Science and TechnologyKunmingChina Department of Physics and Astronomy Northwestern UniversityIllinoisUSA Warwick Manufacturing Group The University ofWarwickCoventryUK The University of Hong Kong Hong KongChina

1 Introduction The United States,Japan,Canada,the European Union,and other developed countries and regions have all formulated climate strategies and pledged to achieve net-zero CO_(2) emissions by ***,meanwhile,has announced through the“carbon-peaking and carbon neutrality targets”in September 2020 that it aims to achieve“peak carbon use”by 2030 and“carbon neutrality”by 2060[1].According to statistical data from the International Energy Agency(IEA),Fig.1 illustrates the carbon intensity of electricity generation in various regions in the Announced Pledge Scenario(APS)from 2010 to 2040[2].One can easily observe that each region aims to accomplish a sharp decrease in the carbon intensity of electricity generation after 2020.

关键词： Carbon-peaking and carbon neutrality targets renewable energy optimization modeling power forecast planning and dispatching reliability and security analysis

Enhancing hourly heat demand prediction through artificial neural networks:A national level case study

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Energy and AI 2024年第1期15卷 288-299页

作者： Meng Zhang Michael-Allan Millar Si Chen yaxing ren Zhibin Yu James Yu James Watt School of Engineering University of GlasgowGlasgowG128QQUK University of Lincoln Brayford PoolLincolnLN67TSUK Scottish Power GlasgowG28DQUK

Meeting the goal of zero emissions in the energy sector by 2050 requires accurate prediction of energy consumption,which is increasingly ***,conventional bottom-up model-based heat demand forecasting methods are not suitable for large-scale,high-resolution,and fast forecasting due to their complexity and the difficulty in obtaining model *** paper presents an artificial neural network(ANN)model to predict hourly heat demand on a national level,which replaces the traditional bottom-up model based on extensive building simulations and *** ANN model significantly reduces prediction time and complexity by reducing the number of model input types through feature selection,making the model more realistic by removing non-essential *** improved model can be trained using fewer meteorological data types and insufficient data,while accurately forecasting the hourly heat demand throughout the year within an acceptable error *** model provides a framework to obtain accurate heat demand predictions for large-scale areas,which can be used as a reference for stakeholders,especially policymakers,to make informed decisions.

关键词： Heating demand in buildings National level forecast Feature selection Machine learning Artificial neural network

Assessment on Fault Diagnosis and State Evaluation of New Power Grid:AReview

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Energy Engineering 2023年第6期120卷 1287-1293页

作者： Bo Yang Yulin Li yaxing ren Yixuan Chen Xiaoshun Zhang Jingbo Wang Faculty of Electric Power Engineering Kunming University of Science and TechnologyKunming650500China School of Engineering University of LincolnLincolnLN67TSUK The University of Hong Kong Hong Kong999077China College of Information Science and Engineering Northeastern UniversityShenyang110819China Department of Electrical Engineering and Electronics University of LiverpoolLiverpoolL693GJUK

1 Introduction The proposal of the concept of“New Power System”aims to illustrate the transform direction of the traditional power system,acting as the development core of the future new power *** achieve this,the proposed strategic targets of“carbon neutralization and carbon peaking”must be implemented and insisted[1].The core feature of the new power system is that renewable energy plays a leading role and becomes the main source of energy supply,meanwhile,the goal of green energy utilization has also been put forward on the *** energy utilization includes two aspects,one is the exploitation and promotion of various green energy technologies,and the other is the digitalization of energy *** this trend,stochastic and fluctuating energy sources such as wind power and photovoltaic power replace deterministic controllable power sources such as thermal power,bringing challenges to power grid regulation and dispatching,as well as flexible *** large-scale integration of renewable energy and increasingly high proportion of power electronic equipment tend to bring about fundamental changes in the operation characteristics,safety control,and production mode of the power system.

关键词： Carbon neutrality and carbon peak goals renewable energy fault diagnosis state evaluation new power grid

A critical survey of technologies of large offshore wind farm integration: summary, advances, and perspectives

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Protection and Control of Modern Power Systems 2022年第1期7卷 233-264页

作者： Bo Yang Bingqiang Liu Hongyu Zhou Jingbo Wang Wei Yao Shaocong Wu Hongchun Shu yaxing ren Faculty of Electric Power Engineering Kunming University of Science and TechnologyKunming 650500China State Key Laboratory of Advanced Electromagnetic Engineering and Technology (Huazhong University of Science and Technology)Wuhan 430074Hubei ProvinceChina Warwick Manufacturing Group University of WarwickCoventry CV47ALUK

Offshore wind farms(OWFs)have received widespread attention for their abundant unexploited wind energy poten-tial and convenient locations *** are rapidly developing towards having large capacity and being located further away from *** is thus necessary to explore effective power transmission technologies to connect large OWFs to onshore *** present,three types of power transmission technologies have been proposed for large OWF *** are:high voltage alternating current(HVAC)transmission,high voltage direct current(HVDC)transmission,and low-frequency alternating current(LFAC)or fractional frequency alternating current *** work undertakes a comprehensive review of grid connection technologies for large OWF *** with previous reviews,a more exhaustive summary is provided to elaborate HVAC,LFAC,and five HVDC topologies,consisting of line-commutated converter HVDC,voltage source converter HVDC,hybrid-HVDC,diode rectifier-based HVDC,and all DC transmission *** fault ride-through technologies of the grid connection schemes are also presented in detail to provide research references and guidelines for *** addition,a comprehensive evalu-ation of the seven grid connection technologies for large OWFs is proposed based on eight specific ***,eight conclusions and six perspectives are outlined for future research in integrating large OWFs.

关键词： Offshore wind farm HVAC HVDC LFAC Fault ride-through