Y.X. He

Risk comprehensive evaluation of urban network planning based on fuzzy Bayesian LS_SVM

Purpose – The purpose of this paper is to use artificial intelligence to evaluate the risks of urban power network planning.Design/methodology/approach – A fuzzy Bayesian least squares support vector machine (LS_SVM) model is established in this paper, which can learn the risk information of urban power network planning through artificial intelligence and acquire expert knowledge for its risk evaluation. With the advantage of possessing learning analog simulation precision and speed, the proposed model can be effectively applied in conducting a risk evaluation of an urban network planning system. First, fuzzy theory is applied to quantify qualitative risk factors of the planning to determine the fuzzy comprehensive evaluation value of the risk factors. Then, Bayesian evidence framework is utilized in LS_SVM model parameter optimization to automatically adjust the LS_SVM regularization parameters and nuclear parameters to obtain the best parameter values. Based on this, a risk comprehensive evaluation of u...

Urban Electric Load Forecasting in China Using Combined Cellular Automata

With the high-speed economic development in China, the transition of structural function in the urban land system highly effects the development of the urban electric load. Forecasting the urban electric load accurately is the foundation of decision making scientifically for the development and planning of the urban power grid in China. This paper improves the decision method of Transition Matrices of Land Use and Cover Change though integrating Cellular Automation with Markov Model firstly. Then, the combined cellular automation model is used to simulate the urban land function evolvement and forecast the land functions in the future as the start point for electric load forecasting. Considering the changes of urban land functions, electric load density, the urban electric load forecasting model is proposed. Finally, the model validation is performed by comparing model predictions with the load data though case study. The results obtained show the accuracy of the adopted methodology for urban load forecasting.

Assessment the connecting style of power distribution network based on fuzzy and blind number theory

The selection of the distribution network connection mode is the precondition and key base work for improving the technical and economic of the distribution system. To take into account the influence of uncertainties in power network expansion planning, the fuzzy and blind number theory is deduced and used for measurement and calculation of uncertain information which influence the final decision. Then an evaluation method has been used to evaluate technical and economic indicators of projects. Case study shows that, based on fuzzy and blind theory used to selection of network connection mode, the validity and practicability of the proposed method is verified.

Analysis of Influencing Factors of Electricity Price Chain Based on Interpretative Structural Modeling

Firstly, influencing factors of chain of electricity price were analyzed, and hierarchical structure chart for the relationship between influencing factors based on Interpretative Structural Modeling (ISM) was constructed. Then through delaminating influencing factors that graph, the levels and relationships among influencing factors of electricity price were shown intuitively, which provide basis for electric price management.

Load forecast of industries in Beijing based on system dynamics simulation method

Power consumption is influenced by many factors. A great deal of events such as the 2008 Beijing Olympic Games will greatly accelerate the increase of power consumption of Beijing. From the view of system dynamics, this paper analyses the causal relationship of these factors and constructs the simulation system for electricity and the economy to forecast power demand, which is composed of GDP and electricity consumption intensity, etc. Finally, the model was used to forecast the power consumption for Beijing and proved to be comprehensive, accurate and practical.