| Title |
Study on Optimal Control Algorithm of Electricity Use in a Single Family House Model Reflecting PV Power Generation and Cooling Demand |
| Authors |
Jeong-Ah Seo ; Younggy Shin ; Kyoung-ho Lee |
| DOI |
http://dx.doi.org/10.6110/KJACR.2016.28.10.381 |
| Keywords |
신재생에너지 ; 최적화 ; 이차계획법 ; 태양광 전지 ; 모델 예측 제어 Renewable energy ; Optimization ; Quadratic programming ; PV arrays ; Model predictive control |
| Abstract |
An optimization algorithm is developed based on a simulation case of a single family house model equipped with PV arrays. To increase the nationwide use of PV power generation facilities, a market-competitive electricity price needs to be introduced, which is determined based on the time of use. In this study, quadratic programming optimization was applied to minimize the electricity bill while maintaining the indoor temperature within allowable error bounds. For optimization, it is assumed that the weather and electricity demand are predicted. An EnergyPlus-based house model was approximated by using an equivalent RC circuit model for application as a linear constraint to the optimization. Based on the RC model, model predictive control was applied to the management of the cooling load and electricity for the first week of August. The result shows that more than 25% of electricity consumed for cooling can be saved by allowing excursions of temperature error within an affordable range. In addition, profit can be made by reselling electricity to the main grid energy supplier during peak hours. |