A multi-period Mixed Integer Linear Program for design of residential distributed energy centres with thermal demand data discretisation

• A multi-period MILP framework proposed for synthesis of distributed energy centres.
• Framework accounts for technology part-loads.
• Integration of thermal storage includes in the methodology.
• Systematic methodology presented for thermal demand discretisation.
• Methodology applied to a case study.

Distributed Energy (DE) has gained significant interest in recent years as a way to maximise the efficient use of fuel for the production of electricity and heat. The concept of DE is to produce energy close to the end users. The increased fuel efficiency allows a significant reduction in carbon dioxide (CO22) emissions. In this paper, the sizes and the number of heat and power supply units are determined by an optimisation procedure that minimises the total annual cost. A Mixed Integer Linear Programming (MILP) model is developed to design new DE centres from a portfolio of possible technologies to service the thermal and power demand profiles of a geographic region. In this model, the partial load required for the combined heat and power (CHP) units and the equipment operating schedule in time intervals are selected to meet the demand data. The approach requires that energy demand be represented by discrete time bands to model the variations according to the time of day, day of the week and season of the year. Selection of inappropriate time bands can lead to misleading results. In this paper a systematic procedure for selecting time bands is proposed. The optimisation model is demonstrated in a case study. Results indicate that 70%–86% reduction in CO22 emissions is possible relative to individual building heating systems. Including thermal storage in the design of distributed energy centres achieves 54% reduction in CO22 emissions compared to design without thermal storage, since fossil fuelled units are not operated continuously.