Ideal scheme selection of an integrated conventional and renewable energy system combining multi-objective optimization and matching performance analysis

Integrating advanced renewable energy into traditional energy systems could be quite beneficial for reducing emissions of greenhouse gases. A solar and geothermal energy assisted integrated energy system (IES) is proposed employing a gas turbine, absorption and ground heat pump cycles, and electric and thermal storage units. The multi-objective optimization approach considering the energy, environmental and economic performance is employed to optimize the system using genetic algorithm (NSGA- II) in MATLAB software. The operating strategies of the IES are considered by introducing four operational modes based on following the thermal or electric loads modes (FTL/FEL) and prioritizing the use of non-grid electricity. The coupled weighted thermal and electric matching performance of the hybrid energy system is chosen as the decision-making parameter for finding the ideal system solution from the Pareto frontiers. The results demonstrate that the FEL mode obtains a better coupled matching performance than the FTL mode, but the goodness of the matching is also influenced by the weighting method employed. The best performance improvements obtained over a traditional system is 36.4% for the economic benefits, and the highest energy and environmental benefits found are 47.9% and 60.7%, respectively. The best coupled matching performance found is 90.6% with a thermal and electric matching of 68.7% and 89.1%, which corresponds to an ideal performance with benefits of 35.3% for energy, 51.2% for emissions, 36.3% for costs, respectively. The carbon tax has a major impact on the economic performance of the solutions and could improve the cost saving ratio up to 38.3% when using a higher CO₂ tax.