Parametric multi-objective optimization of an Organic Rankine Cycle with thermal energy storage for distributed generation

Elio Antonio Bufi, Sergio Camporeale, Francesco Fornarelli, Bernardo Fortunato, Antonio Marco Pantaleo, Arianna Sorrentino, Marco Torresi
2017 Energy Procedia  
This paper focuses on the thermodynamic modelling and parametric optimization of an Organic Rankine Cycle (ORC) which recovers the heat stored in a thermal energy storage (TES). A TES with two molten-salt tanks (one cold and one hot) is selected since it is able to operate in the temperature range useful to recover heat from different sources such as exhaust gas of Externally Fired Gas Turbine (EFGT) or Concentrating Solar Power (CSP) plant, operating in a network for Distributed Generation
more » ... . The thermal storage facilitates a flexible operation of the power system operating in the network of DG, and in particular allows to compensate the energy fluctuations of heat and power demand, increase the capacity factor of the connected plants, increase the dispatchability of the renewable energy generated and potentially operate in loa d following mode. The selected ORC is a regenerative cycle with the adoption of a Heat Recovery Vapour Generator (HRVG) that recovers heat from molten salts flowing from the Hot Tank to the Cold Tank of the TES. By considering the properties of molten salt mixtures, a ternary mixture able to operate between 200 and 400 °C is selected. The main ORC parameters, namely the evaporating pressure/temperature and the evaporator/condenser pinch point temperature differences, are selected as variables for the thermodynamic ORC optimization. An automatic optimization procedure is set up by means of a genetic algorithm (GA) coupled with an in-house code for the ORC calculation. Firstly, a mono-objective optimization is carried out for two working fluids of interest (Toluene and R113) by maximization of the cycle thermal efficiency. Afterwards, a multi-objective optimization is carried out for the fluid with the best performance by means of a Non-dominated Sorting Genetic Algorithm (NSGA) in order to evaluate the cycle parameters which maximize the thermal efficiency and minimise the heat exchanger surface areas. Toluene results able to give the best tadeoff between efficiency and heat exchanger dimensions for the present application, showing that by with respect to the best efficiency point, the heat exchange area can be reduced by 36% with only a penalty of 1% for the efficiency. .
doi:10.1016/j.egypro.2017.08.239 fatcat:a2gvgmphd5ewlbsbvnyis63w4y