Forecasting CO2 emissions of power system in China using Grey-Markov model
نویسندگان
چکیده
The greenhouse effect and its extension affecting is one of the key issues to governments and academics currently. Study shows, CO2 produced from burning fossil fuels are liable 2/3 of the above-mentioned problems. CO2 emissions in China are mainly concentrated in the power plants. In this paper, Gray Markov method is used for long-term load forecasting, combined with the prediction of power generation coal consumption value. Meanwhile, the carbon emissions of power system in 2020-2050 are estimated through the prediction. The results show that: the power system 2020, 2030, 2040 and 2050 carbon emissions are:7.7254 billion tons, 20.0616 billion tons, 51.0740 billion tons and 131.3582 billion tons. Basis on that, we analyze the trend of power system low-carbon development. Then provide some suggestions to reduce CO2 emissions of power system from the level of the national policy, the level of power generation components, power grid optimize and dispatching in the future.
منابع مشابه
Modelling and forecasting CO2 emissions in the BRICS (Brazil, Russia, India, China, and South Africa) countries using a novel multi-variable grey model
This study reexamines the relationship between energy consumption, urban population, economic growth and CO2 emissions in the BRICS countries (i.e., Brazil, Russia, India, China, and South Africa) during the period 2004e2010, by using a novel multi-variable grey model. The results indicate that the economic growth has a decreasing effect on the CO2 emissions in Brazil and Russia and has an incr...
متن کاملDevelopment of Markov Chain Grey Regression Model to Forecast the Annual Natural Gas Consumption
Accurate forecasting of annual gas consumption of the country plays an important role in energy supply strategies and policy making in this area. Markov chain grey regression model is considered to be a superior model for analyzing and forecasting annual gas consumption. This model Markov is a combination of the Markov chain and grey regression models. According to this model, the residual er...
متن کاملA novel grey–fuzzy–Markov and pattern recognition model for industrial accident forecasting
Industrial forecasting is a top-echelon research domain, which has over the past several years experienced highly provocative research discussions. The scope of this research domain continues to expand due to the continuous knowledge ignition motivated by scholars in the area. So, more intelligent and intellectual contributions on current research issues in the accident domain will potentially ...
متن کاملForecasting of CO2 emissions, energy consumption and economic growth in China using an improved grey model
Analyses and forecasts of carbon emissions, energy consumption and real outputs are key requirements for clean energy economy and climate change in rapid growth market such as China. This paper employs the nonlinear grey Bernoulli model (NGBM) to predict these three indicators and proposes a numerical iterative method to optimize the parameter of NGBM. The forecasting ability of NGBM with optim...
متن کاملForecasting Carbon Dioxide Emissions in China Using Optimization Grey Model
Carbon dioxide (CO2) is one of the most important anthropogenic greenhouse gases (GHG) that caused global environmental degradation and climate change. China has been the top carbon dioxide emitter since 2007, surpassing the USA by an estimated 8%. So, forecasting future CO2 emissions trend in China provides the basis for policy makers to draft scientific and rational energy and economic develo...
متن کامل