Low-carbon Operation of Smart House Based on Dynamic CO2 Emissions Intensity Considering Power Generation Status of Electric Power System

Abstract

In recent years, the reduction of Carbon Dioxide (CO2) emissions has been desired due to the global warming issue. Therefore, it is important for consumers to accurately understand the CO2 emissions of the electricity they purchase from the power grid and to make efforts for low-carbon use of electricity. In this study, we propose a low-carbon operation of smart house based on dynamic CO2 emissions intensity created by considering the power generation status of the power grid. The optimization problem is mathematically modeled using mixed integer linear programming (MILP) and solved using the MATLAB toolbox. Simulation results show that the proposed method using Realtime Pricing (RTP) reflecting electricity market prices reduces CO2 emissions and operating costs by 15.85% and 16.96%, compared to the conventional method based on conventional CO2 emissions intensity using Time-of-use (TOU) tariffs.