A target oriented robust optimization approach of a microgrid system investment model

• Main Authors: Siy, Jhoenson S., Uy, Lanz Timothy G., Uy, Patrick Ellis C.
• Format: text
• Language: English
• Published: Animo Repository 2015
• Subjects: Electric power distribution; Power resources; Industrial Engineering
• Online Access: https://animorepository.dlsu.edu.ph/etd_bachelors/7170
• Institution: De La Salle University

Currently, there are 7 billion people worldwide and 1.3 billion people of whom have limited or totally no access to electricity. The said crisis does not only concern energy shortages as it is also compounded with environmental issues like pollution and climate change resulting to various negative effects worldwide. An emerging alternative solution to address the said concerns nowadays is through building a microgrid system. This study extends the existing mixed-integer linear programming microgrid investment model by using a target-oriented robust optimization approach on the uncertain demand while considering multi-period and multi-objective investment setups. Initially, the model was validated and analyzed through subjecting the model under different scenarios. As a result, it was seen that there were four factors that affect the model's decision: cost, budget, carbon emission, and useful life. Since the objective of the model is to maximize the net present value (NPV) of the system, the model would choose to prioritize the least cost among the different distribution energy resoures (DER). After the validation, the group further examined the need to consider load uncertainty through the use of Monte Carlo analysis. As a result, the deterministic model shows a solution that might be too optimistic and might not be achievable in a real life situation when it is subjected to uncertain demand. The issue with uncertainty was addressed through the application of target oriented robust optimization (TORO) approach. A profile of solutions is generated to serve as a guide to the investors in their decisions considering the uncertain demand. As a conclusion, the results show that pessimistic investors would have lower NPV targets since they would invest more in storage facilities incurring more electricity stock out costs. In contrary an optimistic investor would tend to be aggressive in buying electricity generating equipment to meet most of the demand incurring more storage stock out costs.