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The Flexible Operation Stochastic Optimal Of Carbon Capture Plant Under Low-Carbon Economy

Posted on:2016-11-18Degree:MasterType:Thesis
Country:ChinaCandidate:Z Y LiuFull Text:PDF
GTID:2322330488481274Subject:Electrical engineering
Abstract/Summary:PDF Full Text Request
Power industry is facing tremendous pressure to reduce emission, which is a focus area for carbon dioxide emissions. The carbon-capture plant is a large scale and efficient method to reduce carbon dioxide emissions for developing develop the low-carbon electricity systems. However, there are the necessary to study the economic operation strategy for the carbon-capture plant due to the high energy consumption and big cost of carbon capture. Moreover, the carbon trading market and electricity market bring the carbon-capture plant a range of uncertainties, and the analysis that the uncertainties affect the optimized operation of the carbon-capture plant has great realistic significance.The carbon capture rates are influenced by electricity price, emission cutting policies and price of carbon emission permit. The optimization models of carbon-capture rates and planed power with the electricity selling prices, fuel costs and carbon emission permit price as the objective function, is built. Furthermore, under emission-cutting policies and carbon prices, the planed powers and carbon-capture rates for carbon-capture units are analyzed, and the economy of units and the characteristics of carbon emission are discussed. The results manifest the reasonable carbon emission permit allocation quota and carbon emission allowance which can encourage the generator to capture carbon.The electricity prices and carbon-emission allowance have randomness, and the impact on the operation of carbon capture unit could not be ignored. To solve this randomness problem, some relevant uncertainty optimization methods are used in the paper. The methods are mainly made up of stochastic programming and robust optimization. The superquantile method has some excellent mathematical properties, such as convexity and monotonicity, and widely uses to solve the uncertain problems for electric system. Hence, aimed at the mathematical properties, it is necessary to improve the single variable superquantile method to propose the multiple random variable superquantile method for solving the stochastic optimization problem considered the randomness of electricity prices and carbon-emission allowance.The multiple random variable superquantile method is used to describe the influence randomness of electricity prices and carbon-emission allowance for the electricity selling costs and carbon emissions trading costs. The optimization model of carbon capture rates with the fuel costs, carbon emission permit price and electricity selling costs as the objective function, is built. Through exponential analysis, the results indicate that the reasonable confidence level and flexible regulation of carbon capture can reduce the total operation costs of carbon capture units and achieve the low-carbon and economical operation for carbon capture units, which actively responded to the electric power market and carbon trading market, and considered the fluctuation of electricity prices and carbon-emission allowance.
Keywords/Search Tags:stochastic programming, multiple random variable superquantile, uncertainty optimization method, Carbon capture and storage, carbon capture rate, carbon emission permit price, electricity price
PDF Full Text Request
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