Correlation Analysis Of Electricity Consumption With Socio-economic Indicators Based On System Dynamics

Power load as the energy consumption in the power system, has important influence for design, analysis and control of the power system. Long-term changes in the power system load is a ynamic process influenced by many uncertain factors such as social economy, policy and so on. Choosing a appropriate method for power system load relatively accurate predictions has the extremely vital significance for power system planning, electric power industry development and regional economic progress, reasonably for power system planning is extremely important.At first, the past methods of load forecasting usually analysis of the demand for electricity in the whole society and the demand of the each industry separately.This can ignores the connection between them. So this paper proposed a method of using system dynamics to analyze the relations of the social economic and electricity trend. Using system dynamics method to analyze the relationship between social economy and the trend of electricity can better reflect the economic factors and the whole society and the relationship between the industrial electricity. The model can respond in a timely manner When a variable in the model has been changed,then other variables will also change accordingly. So that we can better achieve the equilibrium between the industrial electricity change. Model consider the characteristics of each industrial electricity change also reflects the close link between each industry.At second,this paper build a model for the relationship of social economy and electricity consumption, based on the theory of system dynamics and giving foil consideration to the relationship between economic variables and demand change.There use Vensim PLE establish the correlation model between economic variables and electricity demand change on the whole society and each industry. Model consider the characteristics of each industrial electricity change and the reflects the close link between each industry at the same time.At third, this paper takes the less developed province A in southwestern China as the research object and builds a model in fully understanding of the present situation of its social economy and electricity demand. In addition,this paper use regression algorithm to estimate parameters in the model. It is concluded that the social economy and demand forecast of this province in2014～2020, and make an analysis for its future development trend. At last,this paper also analyze the the prediction results and the current situation of the development of the province to get the conclusion that model prediction results are accurate. This shows that system dynamics applied to the correlation analysis of social economy and the power consumption trend can get a accurate and balanced conclusion.