Two-Tier Optimization Model of Home Energy Considering Time-of-Use Electricity Price and Incentive Subsidy Mechanism

doi:10.12204/j.issn.1000-7229.2021.11.012

Abstract

Abstract:

A two-tier model is proposed to control the peak-valley difference of daily load curve of users and to optimize electricity consumption for smart home. This model takes demand-side response as the means and household energy optimization as the strategy to realize the interaction between the power supply end and the power consumption end, and describes the interactive relationship among the price of electricity, incentive mechanism and users’ power consumption behavior. In the environment of time-of-use (TOU) price, the outer model adopts FCM algorithm to analyze the power consumption of users, and designs the power package including incentive subsidy and peak-valley coefficient with the goal of peak-valley load curve clipping. The inner layer model realizes the intelligent management of household appliances applying the power package, simulates the daily load curve of residents before and after the implementation of the power package, adjusts the electricity consumption plan in real time, and enables the daily load curve of users to meet the peak-valley coefficient of the power package. Through simulation, it is verified that the two-tier optimization model proposed in this paper can effectively reduce the peak-valley difference of the daily load curve of users, and the designed power package is practical to a certain extent on the user side, which is beneficial for users to participate more actively in the optimization scheduling of the power grid and meet the requirements of peak load reduction and valley filling of the power grid.

Key words: two-tier optimization model, time-of-use electricity price, incentive mechanism, daily load curve, smart home power optimization scheduling, FCM clustering algorithm

CLC Number:

TM73

FU Zhixin, LI Ziyan, LI Hanbing, ZHU Junpeng, YUAN Yue. Two-Tier Optimization Model of Home Energy Considering Time-of-Use Electricity Price and Incentive Subsidy Mechanism[J]. ELECTRIC POWER CONSTRUCTION, 2021, 42(11): 108-116.

Figures/Tables 12

Table 1 Characteristic indices of load curve

Fig.1 General idea chart of optimizing daily load curve and rationally scheduling power consumption for the combined power supply and consumption

Fig.2 Flow chart of optimizing daily load curve and rationally scheduling power consumption for the combined power supply and consumption

Table 2 Time-of-use price

Table 3 Cluster quality analysis

Fig.3 Clustering results of daily load curve from FCM algorithm

Table 4 Optimal power plan

Table 5 Residents’ satisfaction with electricity bills and response to the grid after using electricity plans

Table 6 Power consumption information of the dispatching equipment

Fig.4 Load curve before and after implementation of power package

Fig.5 Unplanned operation of home appliances

Fig.6 Home appliance operation considering the dynamic priority and meeting the peak-valley coefficient of the standard value

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