Browse > Article
http://dx.doi.org/10.6110/KJACR.2016.28.10.381

Study on Optimal Control Algorithm of Electricity Use in a Single Family House Model Reflecting PV Power Generation and Cooling Demand  

Seo, Jeong-Ah (Department of Mechanical Engineering, Graduate School Sejong University)
Shin, Younggy (Department of Mechanical Engineering, Graduate School Sejong University)
Lee, Kyoung-ho (Solar Thermal Laboratory, Korea Institute of Energy Research)
Publication Information
Korean Journal of Air-Conditioning and Refrigeration Engineering / v.28, no.10, 2016 , pp. 381-386 More about this Journal
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.
Keywords
Renewable energy; Optimization; Quadratic programming; PV arrays; Model predictive control;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Deng, K, Sun, Y., Li, S., Lu, Y., Brouwer, J., Mehta, P. G., Zhou, M., and Chakraborty, A., 2015, Model Predictive Control of Central Chiller Plant With Thermal Energy Storage Via Dynamic Programming and Mixed-Integer Linear Programming, Ieee Transactions on Automation Science and EngiNeering, Vol. 12, No. 2, pp. 565-579.   DOI
2 Harish, V. S. K. V. and Kumar, A., 2016, Reduced order modeling and parameter identification of a building energy system model through an optimization routine, Applied Energy, Vol. 162, pp. 1010-1023.   DOI
3 Kim, S. D., 2012, Study on a phase-in strategy of introducing time of use pricing, Korea Research Council for Electric Power Industry.
4 K-MEG Project, G-Valley Smart Energy Management Service, http://g-vally.k-meg.org/tou.html.
5 Commission for Energy Regulation, CER National Smart Metering Programme Time of Use Tariffs Mandate, CER/13/152, www.cer.ie, 2013.
6 https://en.wikipedia.org/wiki/Quadratic_progr amming.