Edinburgh Napier University

  A waste heat recovery system (WHRS) on a process with variable output, is an example of an intermittent renewable process. WHRS recycles waste heat into usable energy. As an example, waste heat produced from refrigeration can be used to provide hot water. However, consistent with most intermittent renewable energy systems, the likelihood of waste heat availability at times of demand is low. For this reason, the WHRS may be coupled with a hot water reservoir (HWR) acting as the energy storage system that aims to maintain desired hot water temperature Td (and therefore energy) at time of demand. The coupling of the WHRS and the HWR must be optimised to ensure higher efficiency given the intermittent mismatch of demand and heat availability. Efficiency of an WHRS can be defined as achieving multiple objectives, including to minimise the need for back-up energy to achieve Td, and to minimise waste heat not captured (when the reservoir volume Vres is too small). This paper investigates the application of a Multi Objective Evolutionary Algorithm (MOEA) to optimise the parameters of the WHRS, including the Vres and depth of discharge (DoD), that affect the WHRS efficiency. Results show that one of the optimum solutions obtained requires the combination of high Vres, high DoD, low water feed in rate, low power external back-up heater and high excess temperature for the HWR to ensure efficiency of the WHRS.