Abstract:In the background of exhaustion of the traditional fossil energy sources, developing renewable energy has become a strategic choice for China to achieve energy sustainable utilization and energy security. The coordination between renewable energy generation and the traditional power grid is a problem that needs to be solved in the development of the power grid. The three sectors of power generation, transmission, distribution, and scheduling are considered comprehensively in this paper and an evaluation index system for the development of renewable energy and traditional power grid is designed. The traditional method of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is improved using the idea of matter element extension, and mathematical model of comprehensive evaluation is constructed. Combined with the development index data of a regional power grid and renewable energy sources in Ningxia province, this paper applied the evaluation model to empirical research. The results show that the model meets the real situation of development of the regional power grid and renewable energy generation and has certain reference and promotion significance.
Abstract:With the rapid development of renewable energy, power supply structure is changing. However, thermal power is still dominant. With the background in low carbon economy, reasonable adjustment and optimization of the power supply structure is the trend of future development in the power industry. It is also a reliable guarantee of a fast, healthy and stable development of national economy. In this paper, the sustainable development of renewable energy sources is analyzed from the perspective of power supply. Through the research on the development of power supply structure, we find that regional power supply structure development mode conforms to dynamic characteristics and there must exist a Markov chain in the final equilibrium state. Combined with the characteristics of no aftereffect and small samples, this paper applies a Markov model to the power supply structure prediction. The optimization model is established to ensure that the model can fit the historical data as much as possible. Taking actual data of a certain area of Ningxia Province as an example, the models proposed in this paper are applied to the practice and results verify the validity and robustness of the model, which can provide decision basis for enterprise managers.
Through the analysis of power transmission and transformation project cost, total cost can be decomposed into construction cost, equipment purchase cost, installation cost, and other costs. This paper proposes a decomposition-integration cost prediction model taking a substation project as an example by fully considering the cost characteristics. In decomposition module, the total cost is decomposed into four expenses. In prediction module, different forecasting models are selected to forecast different expense. In integrated module, choose different integration methods to get the predicting results of total cost. The empirical results show that decomposition-integration prediction algorithm has good effect which can effectively predict the cost of power transmission and transformation project and has practical application and popularization value.
Abstract. Since load forecasting plays an important role in the planning and operation of power industry, substantial efforts are made in improving the accuracy and reliability of load forecasting. In this paper, we develop a novel hybrid approach based on phase space reconstruction and least square support vector for the short-term load forecasting. However, the proper parameters in phase space reconstruction and least square vector machine have a significant effect on the forecasting performance, and there is no standard solution for the parameter estimation problem. Therefore, in this paper, the genetic algorithm (GA) approach is employed to optimize the parameters of both phase space reconstruction and least square support vector machine together. The experimental results suggest that the joint optimization parameter is superior to the separate optimization solutions.
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