dc.rights.license | CC-BY-NC-ND | |
dc.contributor.advisor | Akker, Marjan van den | |
dc.contributor.author | Hageraats, Jasper | |
dc.date.accessioned | 2023-03-02T01:01:24Z | |
dc.date.available | 2023-03-02T01:01:24Z | |
dc.date.issued | 2023 | |
dc.identifier.uri | https://studenttheses.uu.nl/handle/20.500.12932/43591 | |
dc.description.abstract | Abstract
I will present a novel way to model the hybrid Unit Commitment (UC) and Economic Dispatch (ED) problem as a variation of an interior point problem, which allows the problem to be tackled by common local-search metaheuristics. On top of that, my state representation is highly intuitive, adaptable and can accept any cost function and many constraints with relative ease. I will also compare my findings with the pre-existing literature and I will show that this method can find an improvement of a known optimum for at least one well known instance of the hybrid UC/ED problem. I will also show that this method exhibits interesting search behaviour which can be preferable in networks with renewable energy sources and various other robustness concerns. | |
dc.description.sponsorship | Utrecht University | |
dc.language.iso | EN | |
dc.subject | Abstract
I will present a novel way to model the hybrid Unit Commitment (UC) and Economic Dispatch (ED) problem as a variation of an interior point problem, which allows the problem to be tackled by common local-search metaheuristics. On top of that, my state representation is highly intuitive, adaptable and can accept any cost function and many constraints with relative ease. I will also compare my findings with the pre-existing literature and I will show that this method can find an improvemen | |
dc.title | Local Search for integrated Economic Dispatch and Unit Commitment problems | |
dc.type.content | Master Thesis | |
dc.rights.accessrights | Open Access | |
dc.subject.keywords | Unit;Commitment;Economic;Dispatch;Local;Search;Unit Commitment;Economic Dispatch;Local Search;Electricity Generation | |
dc.subject.courseuu | Computing Science | |
dc.thesis.id | 14501 | |