Industrial process integration based on mixed integer linear programming has been used for decades to design and improve industrial processes. The technique has later been extended to solve multi-period and multi-scale problems for the design of urban energy systems. Assistance is indeed required for the elaboration of coordinated investment scheduling strategies to promote renewable and efficient urban energy infrastructure shaping the future energy context for the next decades. Major energy consumers, such as hospital complexes, airports, or educational campuses can act as a driving force for the development of renewable energy cities by attracting profitable large-scale energy networks and infrastructure. The proposed methodology generates optimal alternatives for the replacement, in a long-term perspective, of the various energy supply units and systems considering the evolution of the energy demand and the availability of the energy resources. Energy integration techniques are coupled to a parametric multi-objective optimization routine to select and size the energy equipment with both financial profitability and CO2 emission reduction as objectives. The originality of the developed method lies in the integration of a multi-period mixed integer linear programming formulation to generate long-term investment planning scenarios. The method has been demonstrated on a complex of eight hospitals totaling 466,000 m2 and an operating budget of 1.85 billion USD per year. The energy integration of new centralized and decentralized equipment has been evaluated on a monthly basis over four periods until the year 2035. The results show that among the four scenarios identified, the most optimistic alternative allows to decrease the final energy consumption of about 36%, cut the CO2 emissions by a half, multiply the renewable energy share by a factor 3.5 while reducing the annual total cost by 24%. This scenario considers mainly the integration of a very low temperature district heating with decentralized heat pumps to satisfy the heat requirements below 75°C, as well as heat recovery systems and the refurbishment of about 33% of the building stock.
Day‐ahead charging operation of electric vehicles with on‐site renewable energy resources in a mixed integer linear programming framework
