Dehghan, ShahabAleliw, Mohammed2023-12-122023-12-122023-10-25https://hdl.handle.net/20.500.14154/70175In the face of climate change mitigation challenges, CO2 emission, and escalating electricity demands, establishing a reliable and sustainable energy framework has become a critical imperative. This importance extends beyond energy production; it also includes the crucial aspect of economic sustainability. This study is centred on optimizing investment strategies within local energy systems, aiming to establish a resilient and dependable energy generation approach. This attempt involves the strategic integration of hybrid renewable energy sources, arranged through detailed optimization modelling, and complemented by cost-effective investment tactics. The primary objective is to ensure a robust energy supply and foster economic investments with the mitigation of uncertainties through Python-based optimization modelling. The research utilizes a static time frame methodology for decision-making, examining deterministic and stochastic scenarios, to investigate the optimal incorporation of hybrid renewable energy sources. The transmission network is modelled with a single-node approach, focusing on microgrid resilience, and a range of optimization analysis methods are employed to evaluate the proposed energy generation strategies. The investigation explores six distinct scenarios within the optimization framework. The baseline case implies deterministic parameters, featuring a 10-PU diesel generation unit and a load demand aligned with historical trends with a maximum of 1 PU. The remaining scenarios (cases 2 to 5) imply load demand increments of 25%, 50%, 75%, and 100%, respectively. The sixth case introduces a 100% load demand escalation coupled with a diesel unit capacity reduction to 5 PU. The investment for all scenarios amounts to $8.41 million, encompassing the deployment of 10 × 1 MW offshore wind units and 11 × 1 MW onshore wind units. Moreover, the operational cost of $252.04 per MWh for the diesel generation unit is included in this investment. The anticipated payback period is achieved within the first year, assisted by a remarkable lifetime cost of $−540.38 million and a profit of $28.51 million.23enCO2 emissionshybrid renewable energymicrogridPython-based optimizationsustainabilityuncertaintyThesis