Research On Energy Demand Of Office Buildings Based On Spot Electricity Transaction

With the reform of the electricity market,the spot electricity market has gradually formed,and more and more energy demand side will participate in the power operation and electricity trading.It is of great significance to grasp the difference of power consumption law between different users,accurately predict the power load on the energy side,and provide scientific and reasonable power management scheme for users,so as to ensure that users can participate in power spot transaction safely and smoothly.At present,the prediction object of electricity consumption is generally the power grid system,the overall regional electricity consumption or a single user,while there are few studies on the analysis of the electricity consumption demand of a certain type of building.Therefore,this paper takes office buildings as the research object,and on the basis of analyzing the characteristics of the electricity market transaction mechanism,studies the power consumption characteristics of this type of building on the energy side,and uses intelligent algorithms to establish an office building energy consumption prediction model.First of all,the paper introduces the reform process of power market,medium and long-term trading and spot trading mechanism,and analyzes the impact of spot trading market on energy demand side from two aspects of deviation power assessment and time of use price.Secondly,the office buildings in Chengdu area are selected as the research object,and the physical model is established.According to the influence of building envelope parameters,indoor thermal disturbance and air conditioning system equipment on energy consumption,the orthogonal experimental design was carried out on 16 factors and 4 levels.then,DeST software is used to simulate the annual hourly energy consumption of 64 orthogonal experimental combination schemes,and the office building energy consumption model was verified to ensure the rationality and reliability of the simulation research.Then,the grey relation-cluster analysis method is used to study the difference in the degree of energy consumption and the energy consumption characteristics of the influencing factors between different building users of the same type of office building.Thirdly,starting from the overall electricity consumption behavior,this paper analyzes the typical electricity consumption law of office buildings,studies the different energy consumption modes of office buildings and the seasonal and time-consuming laws of electricity consumption,and divides the total electricity consumption of large office buildings into three different typical patterns.so as to provide the basis for the construction of the subsequent energy consumption prediction model.Then,the power consumption forecasting model of lighting socket is established by formula method.Based on the seasonal variation of air conditioning load,the LM-BP neural network algorithm is compiled by using Python software to establish the forecasting models of air conditioning power consumption in summer and winter.the average absolute percentage error between the predicted and simulated values in summer and winter is 5.74% and 5%,respectively.And Taking a certain office building in chengdu for the measured object,the reliability of the air conditioning load prediction model of LM-BP neural network has carried on the inspection,the relative error is 6.6.%.The results show that the LM-BP neural network prediction model has high prediction accuracy in office building air conditioning power prediction.Finally,according to the peak and valley time-of-use electricity prices in the electricity market,the demand response effect of office buildings and the control strategy of electrical equipment are analyzed,so as to guide the energy side to adjust the power structure in time after load forecasting and reduce the power cost.The results show that time-of-use electricity prices can incentivize users to reduce electricity consumption and electricity costs.Based on the development demand of electricity spot trading market,this paper analyzes the law of power consumption of large office buildings and establishes a prediction model of power consumption.So that it can grasp the power consumption situation and judge the change trend of energy consumption,which can provide reference for the optimization of power consumption structure of office buildings,the reasonable adjustment of power consumption mode and the participation of users in electricity market trading.