Optimal Thermal Model Predictive Control for Demand Side Management Strategies Romanos P.1,*, Trianti E.1, Haritatos V.1, Kondili V.1, Madousi S.1, Papanikolaou K.1, Vassilaki M.1, Schmid J.2, Nestle D.2 1University of Patras, Rio Campus, 26504, Patras, Greece 2Fraunhofer-Institute for Wind Energy and Energy System Technology, IWES, Kenigstor 59, 34119, Kassel, Germany *E-mail: takis.romanson@gmail.com
Online published on 10 August, 2015. Abstract (Optimal Thermal Model Predictive Control For Demand Side Management Strategies) This paper aims to present the design, analysis and development of a control scheme named Thermal Model Predictive Control for Demand Side Management Strategies. The control is implemented on a building in Athens, whose thermal model is derived using the Finite Difference Calculation Method. The development and testing of the thermal model is implemented while the predictive controller for heating/cooling strategies is analysed through simulation results. The advantages of the scheme are described, including the ability of the predictive controller to consult the users for energy and cost savings during the peak demand, in an acceptable way by them regarding the thermal comfort issue. Demand Side Management (DSM) is a measure taken by electric utilities to influence the amount or timing of customers’ energy demand, in order to utilize scarce electric supply resources more efficiently. According to IEA Demand Side Management working group, the term “demand response” refers to a set of strategies which can be used in competitive electricity markets to increase the participation of the demand side in setting prices and clearing the market[1]. The net effect of the demand response is to ease system constraints and to generate security and economic benefits for the market as a whole. As far as the thermal comfort is concerned in order to reach the desired indoor temperature and humidity, the heating/cooling demand should be regulated thus satisfying a DSM strategy. In the framework of this paper “Thermal Model Predictive Controller” is developed implementing super cooling/heating strategies, through which a building or a building part is pre-cooled/pre-heated during low peak periods achieving peak shaving in an acceptable way by the users regarding the thermal comfort issue during summer. In addition, the development of a Bidirectional Energy Management Interface (BEMI) will offer Technical and Economical Integration of Distributed Energy Resources. The penetration of PVs in these smart buildings, with daylighting strategies using BEMI with KNX/EIB protocol is investigated. The system of prefabrication includes a selected set of bioclimatic (passive and hybrid) systems integrated to the building envelope, which are chosen by the environmental and economic cost/benefit parameters available before construction. Top Keywords Demand side management, demand response, building simulation, model predictive control, smart buildings, renewable energy sources, smart grids. Top |