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energy planning of Beijing Towards Low-carbon,Clean and Efficient Development in 2035

CSEE Journal of Power and energy Systems 2024年第3期10卷 913-928页

作者： Chengzhou Li Ningling Wang Xiaohu Shen Yumeng Zhang Zhiping Yang Xiaofeng Tong François Maréchal Ligang Wang Yongping Yang Institute of energy Power Innovation North China Electric Power UniversityBeijing 102206China School of energy Power and Mechanical Engineering and National Research Center for Thermal Power Engineering and TechnologyNorth China Electric Power UniversityBeijing 102206China Industrial Process and energy Systems Engineering Swiss Federal Institute of Technology in LausanneSionSwitzerland

energy transition towards clean,efficient energy supply has been a common sense of the government and public in ***,lacking reasonable planning will lead to undisciplined development,resource waste,and excessive *** this context,this paper investigates potential pathways of Beijing energy transition towards a high-level low-carbon,clean and efficient energy system in 2035 with an extended energysocpe ***,based on available data,future energy demands are predicted by a newly proposed hybrid forecasting method,which combines the traditional regression model,grey model,and support vector machine model with an entropy-based weighted ***,the superstructure-based optimization model is employed to investigate the system configuration and operation strategy of the future Beijing energy ***,the uncertainty impact of electricity price,natural gas price,hydrogen price,and the capital expenditures of electrolyzer and steam methane reforming for hydrogen applications are *** forecasting results show that all walks of life will witness a continuously increasing energy demand in multiple sectors of Beijing towards *** planning results suggest that the imported electricity and natural gas will dominate the energy supply of Beijing in 2035 with a contribution of 86%of the energy resources consumption of 384 ***,the energy system presents a high end-use electrification level of 65%and high penetration of efficient technologies,which supply 119 TWh via combined heat and power,26 TWh via heat pump and 95 TWh via district heating *** energy use of various sectors of energy resources,technologies and end-use are closely *** will have an increased penetration in the private mobility sector,but the locally generated hydrogen is mainly from steam methane reforming technology.

关键词： energy transition energy planning carbonneutral demand forecasting energyscope

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Deep excavation of the impact from endogenous and exogenous uncertaintieson long-term energy planning

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能源与人工智能(英文) 2023年第1期11卷 150-160页

作者： Xiang Li François Maréchal Industrial Process and energy Systems Engineering Ecole Polytechnique Fédérale de LausanneRue de l’industrie 17Sion1950Switzerland

Endogenous and exogenous uncertainties exert significant influences on energy planning. In this study,we propose a systematic methodology to excavate the uncertainty space, by combining mix-integer linearprogramming (MILP), Monte Carlo simulation, and machine learning for quantification of the uncertaintyimpacts on a national-level energy system from global and local perspectives. This approach allows in-depthcorrelation analysis highlighting potential synergies and risks in the energy transition, and can be easily applie for assisting policy making. The case study for Switzerland shows that both carbon neutrality (even negativeemissions) and energy autonomy can be achieved by 2050, but the energy system’s configuration variessignificantly under uncertainty. Through conditional distribution analyses, carbon capture and storage (CCS),Photovoltaic (PV), and wood gasification show the most strong correlation for decarbonization. This study isbased on the whole uncertainty space taking into account heterogeneous uncertainties, leading to increasedreliability compared to sensitivity analysis from single scenarios’ comparisons. The synergy between energymodels and artificial intelligence (AI) is promising to be widely applied in energy planning area, particularlyfor emerging technologies with large uncertainty in development.

关键词： Uncertainty energy planning Monte Carlo simulation Machine learning

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energy-Efficiency Economics as a Resource for energy planning

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Open Journal of energy Efficiency 2013年第1期2卷 22-28页

作者： Fabio Correa Leite Decio Cicone Jr Luiz Claudio Ribeiro Galvao Miguel Edgar Morales Udaeta energy Group of Electric energy and Automation Engineering Department Polytechnic SchoolUniversity of Sao PauloSao PauloBrazil

The objective of this work is a multi-criteria decision-making assessment that aims to facilitate the energy-Efficiency Economics, introducing the Analytic Hierarchy Process (AHP) as part of power-system planning tool for an energy-efficiency application. It addresses to include qualitative aspects in the decision-making agendas of energy-efficiency projects. The manuscript details the limitations of non-rigorous financial analysis and proposes an alternative for including energy-efficiency measures in discussions pertaining to the financial opportunities available to any investor, and it presents the methodology that supports the qualitative aspects and the software package used to execute this methodology. As case study a complete example including a sensitivity analysis is presented.

关键词： energy Conservation energy planning Power Economics Analytic Hierarchy Process (AHP)

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Economic Dispatch Considering Hourly Capacity Allocation with a Variable Renewable and Hydro-Based Generation Portfolio

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energy and Power Engineering 2022年第10期14卷 594-614页

作者： Roney N. Vitorino Dorel S. Ramos Karen Tapia-Ahumada Sergey Paltsev John M. Reilly energy Research Office Rio de Janeiro Brazil Polytechnic School University of Sao Paulo Sao Paulo Brazil Massachusetts Institute of Technology Cambridge USA

The objective of this paper is to assess an economic dispatch considering a power system portfolio, which includes predominant amount of hydro power and increasing quantities of intermittent renewables in relation to the total electric capacity. With growing importance of intermittent wind and solar generation taking part into power systems worldwide, there is need for greater chronological resolution to estimate the flexibility of the power system to offer firm capacity. In this way, a linear optimization model operating hourly is developed to calculate the minimum power system cost, while stablishing the capacity allocation to meet the projected load throughout one-year simulation, as an estimation of how the hourly economic dispatch impacts the scheduling of generators belonging to a power system with this portfolio composition. A central focus is how to operate the available hydro capacity to back up intermittent renewables, evaluating the physical hydro operating constraints, monthly energy balance and maximum power availability. A case study was simulated based on the Brazil’s power system configuration, showing that existing hydro capacity provide hourly flexibility to back-up intermittent renewables, potentially saving 1.2 Billion R$, about 3.6% of total system cost referred to 2019. It is worthwhile to realize that the developed methodology can be employed to other power systems with similar capacity portfolio structure for the purpose of calculating its optimum allocation for a specified region and target year.

关键词： Economic Dispatch energy planning Operation Flexibility Power System Transmission System Variable Renewable energy

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An Application of Decision Trees Algorithm to Project Hourly Electricity Spot Price as Support for Decision Making on Electricity Trading in Brazil

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energy and Power Engineering 2022年第8期14卷 327-342页

作者： Cosme Rodolfo R. dos Santos Roberto Castro Rafael Marques State University of Campinas School of Electrical and Computer Engineering Campinas Brazil Independent Consultant Vinhedo/SP Brazil Brazilian Association of Photovoltaic Solar energy (ABSOLAR) S&atilde o Paulo Brazil

Estimating the price of a financial asset or any tradable product is a complex task that depends on the availability of a reasonable amount of data samples. In the Brazilian electricity market environment, where spot prices are centrally calculated by computational models, the projection of hourly energy prices at the spot market is essential for decision-making, and with the particularities of this sector, this task becomes even more complex due to the stochastic behavior of some variables, such as the inflow to hydroelectric power plants and the correlation between variables that affect electricity generation, traditional statistical techniques of time series forecasting present an additional complexity when one tries to project scenarios of spot prices on different time horizons. To address these complexities of traditional forecasting methods, this study presents a new approach based on Machine Learning methodology applied to the electricity spot prices forecasting process. The model’s Learning Base is obtained from public information provided by the Brazilian official computational models: NEWAVE, DECOMP, and DESSEM. The application of the methodology to real cases, using back-testing with actual information from the Brazilian electricity sector demonstrates that the research is promising, as the adherence of the projections with the realized values is significant.

关键词： Artificial Intelligence Machine Learning Price Estimation energy planning Spot Electricity Market Spot Prices Forecast

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Potential Impact of Biomass Cogeneration Plants on Achieving Climate Neutrality of BIH until 2050

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American Journal of Climate Change 2022年第3期11卷 250-264页

作者： Azrudin Husika Nurin Zecevic Ejub Dzaferovic Faculty of Mechanical Engineering University of Sarajevo Sarajevo Bosnia and Herzegovina

The paper analyzes the potential of Biomass Combined Heat and Power (BCHP) plants in Bosnia and Herzegovina (BiH) in achieving climate neutrality until 2050. Two scenarios for reducing GHG emissions from the power generation sector in BiH until 2050 were developed. Scenarios were developed using LEAP, a software tool for energy policy analysis and climate change mitigation assessment. The complete final energy consumption and existing primary energy mix in BiH were included. Both scenarios imply a significant reduction in electricity generation from coal-fired power plants (CFPP). The first scenario (S1) involves the construction of a substitute CFPP unlike the second scenario in which there is no construction of a new CFPP, but part of the reduction in electricity generation from the CFPPs is compensated by BCHPs. The second scenario (S2) achieves a significantly higher reduction in GHGs emissions and provides an answer to the question of how much wood biomass is needed for the operation of BCHP for enabling the decarbonization of the power generation sector by 2050. S1 also represents a step toward reducing GHG emissions. Emissions from power generation in 2030 are about 60% lower than in 2015, i.e. by closing part of the existing CFPPs fleet, while in 2050 GHG emissions will be reduced by 12.26 million tons of CO2eq compared to 2015. The main advantage of S2 is the gradual phase-out of CFPPs and construction of BCHPs, which means incomparably lower GHG emissions, negligible in 2050, representing a key argument for the deployment of biomass potential for power generation. The technical potential of unused wood biomass in BiH is 7.44 PJ annually or 620,620 t annually. These quantities would be sufficient for the levels of electricity production in Scenario 2 by 2035. After that, the existing available technical potential is not enough. This means that BiH needs to increase biomass production and its technical potential to enable the implementation of tha

关键词： GHG Emissions Cogeneration Wood Biomass Climate Neutrality energy planning

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Modelling and analysis of decentralized energy systems with photovoltaic, micro-hydro, battery and diesel technology for remote areas of Nepal

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Clean energy 2021年第4期5卷 690-703页

作者： Nawaraj Sanjel Bivek Baral Department of Mechanical Engineering Kathmandu UniversityDhulikhelNepal

Remote areas of Nepal suffer from limited or no access to *** electricity access in remote areas is one of the foremost challenges of any developing *** purpose of this study is to develop and propose a reliable and low-cost model for *** study presents an optimized choice between decentralized renewable-energy systems and grid *** for an analytical method for the modelling and analysis of electrification options based on life-cycle cost(LCC)and economic distance limit,each energy system for varied load conditions is compared for a better option.A framework for energy-system selection based on available resources is *** compares the grid-expansion option with potential isolated renewable-energy systems to ensure energy access to the area under ***,off-grid configurations that rely on renewable energy sources are also considered for the necessity of backup supply to ensure continuous power to the research ***-economic assessment is carried out for different off-grid and hybrid configurations proposed in this study and their feasibility checks are carefully *** efficacy of the proposed hybrid energy systems is assessed by comparing the life cycle and energy cost and by performing different additional sensitivity *** study concludes that reduced generation cost supports the increasing penetration of *** LCC for grid expansion is the most economical under high-load conditions,whereas for the isolated and sparsely settled populations with low-load conditions,photovoltaic power backed up with a diesel generator is the most economical.

关键词： decentralized energy system energy planning rural electrification economic distance limit life-cycle cost

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