Thermo-economic and environmental optimization using PSO of solar organic Rankine cycle with flat plate solar collector.

The use of solar energy is considered a potential strategy for the production of electrical energy through thermal heat sources. This article portrays a study framed to be energetic, economic, and environmental fields. This study was carried out in two thermal configurations: the Regenerative Rankine Cycle (RORC) and the Simple Organic Rankine Cycle (SORC), which use solar energy to supply electrical power to a building. The thermodynamic and economic models were proposed for each subsystem of the thermal process, allowing hourly simulations to know the economic indicators such as the payback period (PBP), the levelized cost of energy (LCOE), the specific investment cost (SIC), and the initial investment cost ( C I n v ). The effect of operational variables such as the pressure ratio (rp), the evaporator pinch point temperature (Ap), the condensation pinch point temperature (Tcond), and the solar collector area (Ac) on the Relative Annual Benefit (RAB) were studied. Finally, the Particle Swarm Optimization (PSO) algorithm was implemented to optimize the economic indicators and the environmental impact of the thermal configurations. Results showed that the RORC configuration presented a better performance in terms of generation, purchase, and hourly sale of energy. However, in terms of RAB, the SORC (39,833 USD/year) showed better results in contrast to the RORC (39,604 USD/year) for an evaporator pinch point temperature of 35 °C. Finally, the application of the PSO optimization algorithm allowed the reduction of the LCOE (11.64%), SIC (11.67%), and PBP (11.81%) thermo-economic indicators from the base condition for the SORC, and the reductions obtained in the RORC were LCOE (18.11%), SIC (10.67%), and PBP (11.11%). However, the decrease in environmental Impact for both systems was less than 1% as a consequence of the high contribution of thermal oil in the construction phase of the system.

Thermoeconomic analysis of a combined supercritical CO2 reheating under different configurations of Organic Rankine cycle ORC as a bottoming cycle.

Supercritical Brayton cycles have been considered as one of the technologies that present high thermal efficiencies in a wide range of energy conversion systems. Also, these systems can even increase their efficiency by incorporating a suitable bottoming cycle. In this article, a combined supercritical Brayton cycle with an Organic Rankine cycle (ORC) was analyzed. The influence of key system parameters such as the Brayton circuit high-pressure (Phigh), the turbine-1 inlet temperature (TIT), the turbine-1 efficiency ( n t ), and the evaporation pressure ( P e v a p ) on the economic indicators such as the Levelized Cost of Energy (LCOE), the Payback Period (PBP), the Specific Investment Cost (SIC), and net work ( W ˙ n e t ) was studied. Besides, the effect of these parameters on the exergo-economic indicator r k and the relative cost difference r k were studied. Finally, a thermo-economic optimization of the proposed configurations was carried out. The study revealed that the turbine-1 inlet temperature (TIT) was the variable with the most significant effect on the economic and energy indicators of the configurations analyzed. The increase in the turbine temperature up to 850 °C caused a rise of 63.8% for both configurations. Also, the results revealed that the Brayton/SORC configuration presented the best economic performance compared to the Brayton/RORC system. The thermo-economic optimization revealed that temperatures above 800 °C and pressures between 25-30 MPa increase system performance. In addition, the Brayton/SORC configuration has a comparative reduced levelized energy costs and low payback periods, which makes it more attractive.

Operational data set of a 2 MW natural gas-fired generation engine at shutdown times.

In this paper, operational data of a natural gas-fired generation engine at 2 MW of power is presented. This engine is used as part of the power supply system of a flexible packaging transformation and conversion plant. This plant, besides having the power supply generated by the engine, receives electrical energy from the network. The data collected from this engine corresponds to measurements taken before, during and after engine stops, whether due to engine maintenance stops, engine failures or external power grid failures. The measurement was made every 10 seconds, and for the storage of these data a data acquisition software was used, which, besides allowing to take these data, shows in real time the electrical behavior of the electrical supply system, as well as the mechanical behavior of the engine.

A phenomenological base semi-physical thermodynamic model for the cylinder and exhaust manifold of a natural gas 2-megawatt four-stroke internal combustion engine.

This paper presents the application of a systematic methodology to obtain a semi-physical model of phenomenological base for a 2 MW internal combustion engine to generate electric power operating with natural gas, as a function of the average thermodynamic value normally measured in industrial applications. Specifically, the application of the methodology is focused on the cylinders, exhaust manifold, and turbocharger turbine sections. The proposed model was validated with actual operating data, obtaining an error rate not exceeding 5%, which allow a thermal characterization of the Jenbacher JMS 612 GS-N based on the model. A parametric analysis is conducted; considering the volumetric efficiency, the output electric power, the effective efficiency, the exhaust gas temperature, the turbine mass flow, the specific fuel consumption under the nominal operation conditions, which is 1.16 bar in the gas pressure, 65 °C in the cooling water temperature, 35 °C in the average ambient temperature, and 1500 rpm. The results of this model can be used to evaluate the thermodynamic performance parameters of waste heat recovery systems. On the other hand, new control strategies and the implementation of state observers for the detection and diagnosis of failures can be developed based on the proposed model.