Technoeconomic analysis of internal combustion engine – organic Rankine cycle systems for combined heat and power in energy-intensive buildings

Abstract

For buildings with low heat-to-power demand ratios, installation of internal combustion engines (ICEs) for combined heat and power (CHP) results in large amounts of unused heat. In the UK, such installations risk being ineligible for the CHP Quality Assurance (CHPQA) programme and incurring additional levies. A technoeconomic optimisation of small-scale organic Rankine cycle (ORC) engines is performed, in which the ORC engines recover heat from the ICE exhaust gases to increase the total efficiency and meet CHPQA requirements. Two competing system configurations are assessed. In the first, the ORC engine also recovers heat from the CHP-ICE jacket water to generate additional power. In the second, the ORC engine operates at a higher condensing temperature, which prohibits jacket-water heat recovery but allows heat from the condenser to be delivered to the building. When optimised for minimum specific investment cost, the first configuration is initially found to deliver 20% more power (25.8 kW) at design conditions, and a minimum specific investment cost (1600 £/kW) that is 8% lower than the second configuration. However, the first configuration leads to less heat from the CHP-ICE being supplied to the building, increasing the cost of meeting the heat demand. By establishing part-load performance curves for both the CHP-ICE and ORC engines, the economic benefits from realistic operation can be evaluated. The present study goes beyond previous work by testing the configurations against a comprehensive database of real historical electricity and heating demand for thirty energy-intensive buildings at half-hour resolution. The discounted payback period for the second configuration is found to lie between 3.5 and 7.5 years for all of the buildings considered, while the first configuration is seen to recoup its costs for only 23% of the buildings. The broad applicability of the second configuration offers attractive opportunities to increase manufacturing volumes and reduce unit costs. The findings are relevant to a range of buildings with heat-to-power demand ratios from 20% to 100%.

Parametric optimisation of a combined supercritical CO2 (S-CO2) cycle and organic Rankine cycle (ORC) system for internal combustion engine (ICE) waste-heat recovery

“…The interior-point algorithm in MATLAB's fmincon function, which has been proven as an effective algorithm for power-cycle optimisation [6,7,40,45,46], has been chosen as the solver to maximise the net ORC power output under each condition of the topping S-CO2 cycle under nonlinear constraints imposed on the pinch point temperature differences in all heat exchangers, as well as on operating parameters of the ORC system including the evaporation pressure and the maximum turbine inlet temperature. The model of the system was further validated against data reported by Akbari and Mahmoudi [37].…”

“…In a typical ICE, more than half of the total energy from fuel combustion is rejected via the engine's exhaust gases and jacket water [4,5]. Waste-heat recovery and conversion to power is acknowledged as an effective pathway for increasing overall ICE power output and reducing fuel consumptions and emissions [6][7][8][9].…”

On the value of combined heat and power (CHP) systems and heat pumps in centralised and distributed heating systems: Lessons from multi-fidelity modelling approaches

“…A CHP system is made of two main components: the prime mover, which is connected to a generator to produce electricity, and the heat recovery module, which collects waste heat and transfers it to water for hot water or space heating purposes. Recovering heat from the exhaust gases and jacket water of ICEs is the most-studied option [33,34] for electricity and heat cogeneration. The electricity generated from CHP systems can be used to either meet electrical demand or can be sold back to the grid, producing revenues.…”

Stochastic real-time operation control of a combined heat and power (CHP) system under uncertainty

“…where f , th , el , f , th and el are the gradient and intercept parameters. It must be noted that the linear relationship is a significant assumption in the model; for more accurate analysis and specifically for CHP engine design problems, detailed approaches which capture non-linear efficiency characteristics and include promising heat recovery technologies [37][38][39] would be required.…”