| Affiliation: | 1. Department of Energy Technology, Aalto University School of Engineering, P.O. BOX 14100, FI-00076, Aalto, Finland;2. School of Municipal & Environmental Engineering, Harbin Institute of Technology, Harbin 150090, PR China;1. Department of Planning, Aalborg University, Rendsburggade 14, 9000 Aalborg, Denmark;2. Energy Systems Department, EMD International A/S, Niels Jernes Vej 10, 9220 Aalborg Ø, Denmark;1. Department of Mechanical Engineering, Aalto University, School of Engineering, P.O. BOX 14100, FI-00076 Aalto, Finland;2. Institute of Building Environment and Facility Engineering, School of Civil Engineering, Dalian University of Technology, Dalian 116024, China;3. Department of Mathematics and Systems Analysis, Aalto University, School of Science, P.O. BOX 14100, FI-00076 Aalto, Finland;1. Department of Renewable Energies and Environment, Faculty of New Sciences & Technologies, University of Tehran, Tehran, Iran;2. Faculty of Mechanical Engineering, Shahrood University of Technology, Shahrood, Iran;1. Department of Power Engineering, North China Electric Power University, Baoding, Hebei, 071003, PR China;2. Institute of Building Environment and Energy, China Academy of Building Research, Beijing, 100013, PR China |
| Abstract: | The future energy system in community level should be more ‘smart’ to secure reliability, enhance market service, minimize environmental impact, reduce costs and improve the use of renewable energy source (RES). Therefore, this paper proposes an energy integration system – smart hybrid renewable energy for communities (SHREC). It considers both thermal (heating and cooling) and electricity market in a large community level and highlight the interactions between them through utilizing RES, combined heat and power (CHP) and energy storages. A planning model based on CHP modelling is developed for the SHREC system. A linear programming (LP) algorithm is developed to optimize the SHREC system in a weekly period and the results are compared with an existing energy optimization software. We also demonstrate the model in a sample SHREC system during three typical weeks with cold, warm and mid-season weather in the year 2011. The results indicate that the developed modelling and optimization method is more efficient and flexible for the smart hybrid renewable energy systems. |
