Investment Planning in Local Energy Systems
Date
2023-10-25
Authors
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Publisher
Saudi Digital Library
Abstract
In 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.
Description
Keywords
CO2 emissions, hybrid renewable energy, microgrid, Python-based optimization, sustainability, uncertainty