Please cite this article in press as: Fazlollahi, S., et al. Multi-objectives, multi-period optimization of district energy systems: II—Daily thermal storage. Computers and Chemical Engineering (2013), http://dx.doi.org/10.1016/j.compchemeng.2013.10.016 ARTICLE IN PRESS G Model CACE-4826; No. of Pages 15 Computers and Chemical Engineering xxx (2013) xxx–xxx Contents lists available at ScienceDirect Computers and Chemical Engineering jo u r n al homep age: www.elsevier.com/locate/compchemeng Multi-objectives, multi-period optimization of district energy systems: II—Daily thermal storage Samira Fazlollahi a,b,∗ , Gwenaelle Becker a , Franc ¸ ois Maréchal b a Veolia Environnement Recherche et Innovation (VERI), 291 Avenue Dreyfous Ducas, 78520 Limay, France b Industrial Energy Systems Laboratory, Ecole Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland a r t i c l e i n f o Article history: Received 15 February 2013 Received in revised form 9 October 2013 Accepted 22 October 2013 Available online xxx Keywords: Daily thermal storage District energy systems Mixed integer linear programming Evolutionary algorithm Multi-objective optimization CO2 mitigation a b s t r a c t District heating is an efficient way of providing heat to urban areas. The use of storage tanks integrated with district heating network would permit to increase the annual utilization of base load equipment, avoiding over estimation of the size of backup equipment, and balancing the energy demand fluctuation during day and night. In the present work a multi-objective optimization model for sizing and operation optimization of district heating systems with heat storage tanks is presented. The model includes process design and energy integration techniques for optimizing the temperature intervals, the volume and the operation strategy of thermal storage tanks. The proposed model is demonstrated by means of two test cases. Results show that the efficiency, environmental impacts and total costs of an urban system can be improved after integrating the thermal storage by 4.7%, 5% and 2% respectively. © 2013 Elsevier Ltd. All rights reserved. 1. Introduction District heating network is a rational way to provide heat to buildings (Verda & Colella, 2011). Heat requirement in such a sys- tem is typically brought about by centralized plants which are more efficient than decentralized domestic boilers (Lund, Mller, Mathiesen, & Dyrelund, 2010). The configuration of central plant, in terms of the base load and the back up equipment, usually depends on the shape of the annual cumulative demand curve. The base load equipment should oper- ate at maximum power for a large number of hours to reduce the payback time and to provide higher efficiency. The hourly and daily variations of consumers’ demand may affect the system efficiency. One way to overcome this issue is to integrate thermal storage systems between supply and demand sides. The thermal storage can be employed to increase the operating hours of base load technologies at maximum power. It preserves thermal energy during off-peak hours that can be used at on- peak hours. The aim is to balance the energy demand fluctuation, increase the utilization of base load technologies and to avoid over sizing of the backup equipment. ∗ Corresponding author at: Veolia Environnement Recherche et Innovation (VERI), 291 Avenue Dreyfous Ducas, 78520 Limay, France. E-mail addresses: Samira.Fazlollahi@epfl.ch (S. Fazlollahi), Gwenaelle.Becker@veolia.com (G. Becker), Francois.Marechal@epfl.ch (F. Maréchal). A systematic procedure is needed to optimize the size and the operation schedule of the thermal storage tank together with poly-generation technologies in the district energy system, where economic targets and environmental burdens should be consid- ered simultaneously (multi-objective optimization). In addition, the energy integration and pinch analysis techniques should be included to optimize the operating temperatures of the storage system. Researchers have paid much attention in the literature on thermo-economic simulations and synthesis of a thermal storage unit in batch processes. Stoltze, Mikkelsen, Lorentzen, Petersen, and Qvale (1995) studied the integration of heat storage units for waste-heat recovery. They proposed the “combinatorial method” for incorporation of the heat storage tank in batch processes. For a simple system, it was shown that the maximum energy-saving targets as calculated by the pinch-point method can be achieved by integrating storage units with process streams. Sadr-Kazemi and Polley (1996) discussed the optimal layout and the number of storage tanks in the batch process and proposed an iterative search method based on the composite curves to define the tem- perature levels of the storage tanks. They showed the possibility of heat recovery and decreasing the process’s costs through heat storage utilization. Becker and Maréchal (2012) developed the storage model optimization in the batch process based on the pinch analysis principles and restricted heat exchange between processes. Also using pinch analysis principles, Krummenacher and Favrat (2001) and Krummenacher (2001) proposed the evolutionary 0098-1354/$ – see front matter © 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.compchemeng.2013.10.016