Research on the construction of carbon emission model of power generation industry in Jilin province

Although Jilin Province has abundant forest reserves and has a relatively large carbon neutral advantage compared to other provinces, the installed capacity of thermal power is still relatively high, and the installed capacity of renewable energy such as wind power, photovoltaic and hydropower is insufficient. This paper builds a carbon emission model for the power generation industry in Jilin Province based on the characteristics of the power generation industry in Jilin Province and years of field test experience.

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The Various Impacts of Wind Power and Thermal Power Generation on Economic Development: A Case Study of Jilin Province

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.805-806.316 ◽

2013 ◽

Vol 805-806 ◽

pp. 316-319

Author(s):

Xiao Li Zhao ◽

Jin Yao ◽

Ya Nan Hu

Keyword(s):

Economic Growth ◽

Power Generation ◽

Wind Power ◽

Thermal Power ◽

Economic Value ◽

Jilin Province ◽

Analysis Method ◽

Output Analysis ◽

Thermal Power Generation

Based on a case study of Jilin province in Northeast China, this paper applied input-output analysis method to contrast different effects of wind power and thermal power generation on local economic growth. The results indicate that the driving effect of wind power on economic growth in the output of per ten thousand Yuan is lower 5205 Yuan than that of thermal power. However, taking serious environmental externalities produced by thermal power generation into account, thermal power economic value will be greatly decreased.

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Capacity optimization of renewable energy microgrid considering hydropower cogeneration

Journal of Physics Conference Series ◽

10.1088/1742-6596/2083/3/032068 ◽

2021 ◽

Vol 2083 (3) ◽

pp. 032068

Author(s):

Lijun Fan ◽

Jiedong Cui

Keyword(s):

Power Generation ◽

Renewable Energy ◽

Low Temperature ◽

Wind Power ◽

Power Plants ◽

Thermal Power ◽

Energy System ◽

Electric Heater ◽

Spare Capacity ◽

Thermal Power Generation

Abstract This paper proposes a renewable energy system based on photovoltaic power generation, wind power generation and solar thermal power generation, combining thermal power plants with low-temperature multi-effect distillation. Through the electric heater and the thermal storage system photovoltaic and wind power will spare capacity in the form of heat energy, at the same time by thermal power generation system to maintain the stability of the power supply, run under constant output scheduling policy, to the levelling of the smallest energy cost and the design of power rate of maximum satisfaction as the goal, using multi-objective particle swarm optimization (PSO) algorithm to find the best combination of capacity, this system is established. At the same time, combined with low-temperature multi-effect distillation, compared with reverse osmosis seawater desalination cost is lower, reduce energy consumption, has a good application prospect.

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A Coordinated Dispatching Model Considering Generation and Operation Reserve in Wind Power-Photovoltaic-Pumped Storage System

Energies ◽

10.3390/en13184834 ◽

2020 ◽

Vol 13 (18) ◽

pp. 4834

Author(s):

Dai Cui ◽

Fei Xu ◽

Weichun Ge ◽

Pengxiang Huang ◽

Yunhai Zhou

Keyword(s):

Power Generation ◽

Renewable Energy ◽

Power System ◽

Wind Power ◽

System Reliability ◽

Thermal Power ◽

Operating Cost ◽

Estimation Method ◽

Energy Output ◽

Pumped Storage

Large-scale grid integration of renewable energy increases the uncertainty and volatility of power systems, which brings difficulties to output planning and reserve decision-making of power system units. In this paper, we innovatively combined the non-parametric kernel density estimation method and scenario method to describe the uncertainty of renewable energy outputs, and obtained a representative set of renewable energy output scenarios. In addition, we proposed a new method to determine the reserve capacity demand. Further, we derived the quantitative relationship between the reserve demand and the power system reliability index, which was used as the constraint condition of a day-ahead power generation dispatch. Finally, a coordinated dispatching model of power generation and reserve was established, which had the lowest penalty for curtailment of wind power and photovoltaic, as well as the lowest total operating cost for thermal power units, gas power units, and pumped storage power station. By simulating three different working conditions, the proposed model was compared with the traditional deterministic model. Results showed that our proposed method significantly improved system efficiency while maintaining system reliability.

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Retraction Notice: The Synergistic Scheduling Optimization Model for Wind Power and Thermal Power with Energy Storage System Under the Carbon Emission Trade

The Open Fuels & Energy Science Journal ◽

10.2174/1876973x01710010068 ◽

2017 ◽

Vol 10 (1) ◽

pp. 68-68

Author(s):

Liu Hai-Bo ◽

Xin He ◽

Wu Hongliang ◽

Zhou Bao-Rong ◽

Dong Nan ◽

...

Keyword(s):

Energy Storage ◽

Wind Power ◽

Optimization Model ◽

Carbon Emission ◽

Storage System ◽

Thermal Power ◽

Energy Storage System ◽

Scheduling Optimization ◽

Retraction Notice ◽

Carbon Emission Trade

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Hybrid Forecasting Methodology for Wind Power-Photovoltaic-Concentrating Solar Power Generation Clustered Renewable Energy Systems

Sustainability ◽

10.3390/su13126681 ◽

2021 ◽

Vol 13 (12) ◽

pp. 6681

Author(s):

Simian Pang ◽

Zixuan Zheng ◽

Fan Luo ◽

Xianyong Xiao ◽

Lanlan Xu

Keyword(s):

Power Generation ◽

Renewable Energy ◽

Wind Power ◽

Solar Power ◽

Prediction Method ◽

Random Fluctuation ◽

Concentrating Solar Power ◽

Short Term ◽

Hybrid Forecasting ◽

Energy Cluster

Forecasting of large-scale renewable energy clusters composed of wind power generation, photovoltaic and concentrating solar power (CSP) generation encounters complex uncertainties due to spatial scale dispersion and time scale random fluctuation. In response to this, a short-term forecasting method is proposed to improve the hybrid forecasting accuracy of multiple generation types in the same region. It is formed through training the long short-term memory (LSTM) network using spatial panel data. Historical power data and meteorological data for CSP plant, wind farm and photovoltaic (PV) plant are included in the dataset. Based on the data set, the correlation between these three types of power generation is proved by Pearson coefficient, and the feasibility of improving the forecasting ability through the hybrid renewable energy clusters is analyzed. Moreover, cases study indicates that the uncertainty of renewable energy cluster power tends to weaken due to partial controllability of CSP generation. Compared with the traditional prediction method, the hybrid prediction method has better prediction accuracy in the real case of renewable energy cluster in Northwest China.

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Solar thermal power generation technology research

E3S Web of Conferences ◽

10.1051/e3sconf/201913602016 ◽

2019 ◽

Vol 136 ◽

pp. 02016

Author(s):

Yudong Liu ◽

Fangqin Li ◽

Jianxing Ren ◽

Guizhou Ren ◽

Honghong Shen ◽

...

Keyword(s):

Power Generation ◽

Renewable Energy ◽

Renewable Resources ◽

Solar Power ◽

Thermal Power ◽

Solar Photovoltaic ◽

Photovoltaic Power ◽

Power Generation Technology ◽

Generation Technology ◽

Solar Thermal Power Generation

China is a big consumer of energy resources. With the gradual decrease of non-renewable resources such as oil and coal, it is very important to adopt renewable energy for economic development. As a kind of abundant renewable energy, solar power has been widely used. This paper introduces the development status of solar power generation technology, mainly introduces solar photovoltaic power generation technology, briefly describes the principle of solar photovoltaic power generation, and compares and analyzes four kinds of solar photovoltaic power generation technology, among which photovoltaic power generation technology is the most mature solar photovoltaic power utilization technology at present.

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The Study of Wind Turbine Based on Fuzzy Logic

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.385-386.1122 ◽

2013 ◽

Vol 385-386 ◽

pp. 1122-1126

Author(s):

Yue Hua Huang ◽

Qian Cheng Li ◽

Chen Chen ◽

Na Peng ◽

Zuo Dong Duan ◽

...

Keyword(s):

Power Generation ◽

Fuzzy Logic ◽

Renewable Energy ◽

Wind Turbine ◽

Wind Power ◽

Control Method ◽

Wind Power Generation ◽

Generation System ◽

Pitch Control ◽

Power Generation System

Due to the lack of fossil fuels, people are paying more and more attention to renewable energy. Wind energy is one of the important renewable energy. Unpredictability and volatility of the wind source make the output power unstable, so we need to control the active Power. This paper uses fuzzy control method, and the simulation results show that fuzzy control method mentioned in this paper is better than the conventional PI control for Wind power, the nonlinear system. Based on the analysis of pitch control theory and control process, we design fuzzy pitch controller and its model. We simulates gust wind speed imitates, wind turbine control and verifies the effects of the blur pitch control in a constant speed and constant frequency wind power generation system. According to the results of the simulation, we know the pitch controller of fuzzy logic has a better effect on the active control of the generator of the wind power generation system.

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Integration Capability Evaluation of Wind and Photovoltaic Generation in Power Systems Based on Temporal and Spatial Correlations

Energies ◽

10.3390/en12010171 ◽

2019 ◽

Vol 12 (1) ◽

pp. 171 ◽

Cited By ~ 1

Author(s):

Hua Zhou ◽

Huahua Wu ◽

Chengjin Ye ◽

Shijie Xiao ◽

Jun Zhang ◽

...

Keyword(s):

Power Generation ◽

Renewable Energy ◽

Power Systems ◽

Wind Power ◽

Energy Generation ◽

Copula Model ◽

Spatial Correlations ◽

Temporal And Spatial ◽

Renewable Energy Generation ◽

Pv Power Generation

With the rapid growth of renewable energy generation, it has become essential to give a comprehensive evaluation of renewable energy integration capability in power systems to reduce renewable generation curtailment. Existing research has not considered the correlations between wind power and photovoltaic (PV) power. In this paper, temporal and spatial correlations among different renewable generations are utilized to evaluate the integration capability of power systems based on the copula model. Firstly, the temporal and spatial correlation between wind and PV power generation is analyzed. Secondly, the temporal and spatial distribution model of both wind and PV power generation output is formulated based on the copula model. Thirdly, aggregated generation output scenarios of wind and PV power are generated. Fourthly, wind and PV power scenarios are utilized in an optimal power flow calculation model of power systems. Lastly, the integration capacity of wind power and PV power is shown to be able to be evaluated by satisfying the reliability of power system operation. Simulation results of a modified IEEE RTS-24 bus system indicate that the integration capability of renewable energy generation in power systems can be comprehensively evaluated based on the temporal and spatial correlations of renewable energy generation.

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China Power Source Structure and CO2 Emissions Reduction

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.361-363.946 ◽

2011 ◽

Vol 361-363 ◽

pp. 946-953

Author(s):

Yu Ze Jiang ◽

Yan Zhao Yang ◽

Qing Wei Guo

Keyword(s):

Wind Power ◽

Energy Production ◽

Nuclear Power ◽

Thermal Power ◽

Clean Energy ◽

Power Source ◽

Emissions Reduction ◽

Hydroelectric Power ◽

Installed Capacity ◽

Source Structure

According to the statistics data and planning material from the authority, the power source structure of China is analyzed and the clean power prospect is forecasted, which aim to explore occurring to CO2emissions reduction in the power industry. Based on The national greenhouse gas list guide published by Inter-governmental Panel on Climate Change (IPCC) in 2006, the trend of clean energy reduction CO2is predicted. In recent years, the clean energy power is developing quickly, while the share of thermal power gradually declines. By the end of 2010, the percent of thermal power in the total installed capacity is 73.44%, while the hydropower, and wind power and nuclear power accounts for 26.53%. The contribution of thermal power to generated energy is 80.76%, while the clean power is 19.22%. The capacity of thermal power unit with above 300 MW is predominate, accounting for 80%. In 2020, the installed capacity of hydroelectric power, wind power and nuclear power will reach 402 million kW, 150 million kW and 70 million kW, respectively. The corresponding annual energy production of three kinds of clean energy can reach 1.75 trillion kW•h, 314.55 billion kW•h, and 554.68 billion kW•h, which can reduce CO2emissions 1534, 276, 486 million tons, respectively. It is estimated that a total of 2.296 billion tons CO2emissions will be reduced in 2020.

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