Techno-economic Modelling and Multi-Objective Optimisation of a New Stand-alone Hybrid CPSD-SE/HWT System in Microgrids Power Generation Under Jordan Climatic Conditions

A microgrid system comprising of hybrid renewable energy systems (HRES) integrated with power cycles, and energy storage is one of the most efficient energy alternatives that are expected to satisfy the energy demands of remote regions and resolve the environmental problems posed by the use of fossil fuels in energy production. The Stirling engine cycle (SEC) is one of the best-known and most efficient technologies to produce electricity from low-grade heat resources. This system is suitable for residential and small commercial applications. The Stirling engine (SE) combined with a solar thermal system, particularly concentrated parabolic solar dish Stirling engine (CPSD-SE), provides a significant advantage over the conventional photovoltaic system (PV) when the overall cost of energy storage is taken into consideration.
The current study proposes and applies a novel multi-dimensional modelling technique based on artificial neural networks (ANN) for hourly solar radiation and wind speed data forecasting over six locations in Jordan. The developed model is the first attempt to integrate two ANN models simultaneously by using enormous meteorological data points for both solar radiation and wind speed prediction. The developed model requires only three parameters as inputs, and it can predict solar radiation and wind speed data simultaneously with high accuracy. As a result, the model provides a user-friendly model interface that can be utilised in the energy systems design process. Consequently, this model facilitates the implementation of renewable energy technologies in remote areas in which gathering of weather data is challenging. Meanwhile, the accuracy of the model has been tested by calculating the mean absolute percentage error (MAPE) and the correlation coefficient (R). Therefore, the model developed in this study can provide accurate weather data and inform decision makers for future instalments of energy systems.
Further, a novel hybrid renewable energy-based microgrid power system is proposed, designed and techno-economically assessed. The system consists of a CPSD-SE and a horizontal axis wind turbine (HWT) integrated with a battery bank. The novelty of the study lies in replacing conventional hybrid systems, such as a typical PV/wind assembly, with a novel solar dish/wind turbine system that has the potential to achieve higher efficiencies and financial competitiveness. The CPSD-SE serves as the primary source of electrical power generation while the HWT, in conjunction with a battery bank, supplies backup electricity when the primary source of power is unavailable. The system has been designed through advanced modelling in the MATLAB/Simulink® environment that efficiently integrates the individual energy technologies. A technical sensitivity analysis has been performed for all the units in order to reduce the respective design limits and identify optimum operational windows. Further, the performance of the model has been tested at two locations in Jordan, and a thorough techno-economic analysis of the integrated system has been conducted.
The predicted power that is generated by the system is in the range of 100 kWe and 1500 kWe, and the system performance throughout one year has been investigated dynamically via rigorous modelling. In addition, a techno-economic sensitivity analysis has been carried out to study the performance of the integrated hybrid system under the meteorological data for the city of Mafraq, Jordan using MATLAB/Simulink®. The main aim of the study is to carry out a post-design analysis of the new hybrid CPSD-SE/HWT system and calculate the generated power and efficiency. Furthermore, a multi-objective optimisation-based genetic algorithm (GA) approach has been applied in which the total levelised cost of electricity (LCOEtot) and the average overall annual efficiency (ηtot) of the system are simultaneously optimised. The developed model is validated using published results. In conclusion, the obtained results reveal that the optimised model of the microgrid can substantially improve the overall efficiency and reduce the LCOEtot.