Optimisation Models and Methods in Energy Systems
| dc.contributor.author | Antunes, Carlos Henggeler | * |
| dc.date.accessioned | 2021-02-11T21:46:11Z | |
| dc.date.available | 2021-02-11T21:46:11Z | |
| dc.date.issued | 2019 | * |
| dc.date.submitted | 2019-12-09 11:49:15 | * |
| dc.identifier | 42467 | * |
| dc.identifier.uri | https://directory.doabooks.org/handle/20.500.12854/55325 | |
| dc.description.abstract | Challenging problems arise in all segments of energy industries—generation, transmission, distribution and consumption. Optimization models and methods play a key role in offering decision/policy makers better information to assist them in making sounder decisions at different levels, ranging from operational to strategic planning. | * |
| dc.language | English | * |
| dc.subject | TA1-2040 | * |
| dc.subject | T1-995 | * |
| dc.subject.classification | thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology | en_US |
| dc.subject.other | mixed integer linear programming | * |
| dc.subject.other | fuzzy set theory | * |
| dc.subject.other | stochastic programming | * |
| dc.subject.other | mixed integer linear programing | * |
| dc.subject.other | variable renewable power | * |
| dc.subject.other | generation efficiency | * |
| dc.subject.other | optimization | * |
| dc.subject.other | flexibility option | * |
| dc.subject.other | portfolio analysis | * |
| dc.subject.other | firefighting | * |
| dc.subject.other | semi-mean-absolute deviation model | * |
| dc.subject.other | component outage | * |
| dc.subject.other | energy network | * |
| dc.subject.other | predicted mean vote (PMV) | * |
| dc.subject.other | generation expansion planning | * |
| dc.subject.other | building microgrid | * |
| dc.subject.other | demand side management | * |
| dc.subject.other | stochastic robust optimization | * |
| dc.subject.other | oil storage plants | * |
| dc.subject.other | long-term forecasting | * |
| dc.subject.other | multi-criteria decision making (MCDM) | * |
| dc.subject.other | life cycle cost | * |
| dc.subject.other | graph theory | * |
| dc.subject.other | scenario-based multistage stochastic programming | * |
| dc.subject.other | optimal power generation mix | * |
| dc.subject.other | heating ventilation and air-conditioning (HVAC) | * |
| dc.subject.other | intermittent sources | * |
| dc.subject.other | electric-power structure adjustment | * |
| dc.subject.other | technique for the order of preference by similarity to the ideal solution (TOPSIS) | * |
| dc.subject.other | integrated energy system | * |
| dc.subject.other | Markov chain Monte Carlo | * |
| dc.subject.other | nondominated sorting genetic algorithm (NSGA) | * |
| dc.subject.other | domino effect | * |
| dc.subject.other | energy system management model | * |
| dc.subject.other | electrical distribution systems | * |
| dc.subject.other | microgrid operation | * |
| dc.subject.other | influence diagram | * |
| dc.subject.other | net demand | * |
| dc.subject.other | wind power forecasting | * |
| dc.subject.other | energy conservation and emissions reduction | * |
| dc.subject.other | feasible operation region | * |
| dc.subject.other | meshed topology | * |
| dc.subject.other | occupancy-based control | * |
| dc.subject.other | islanded microgrids | * |
| dc.subject.other | combined heat and power | * |
| dc.subject.other | multi-objective optimization | * |
| dc.subject.other | re-optimization and rescheduling | * |
| dc.title | Optimisation Models and Methods in Energy Systems | * |
| dc.type | book | |
| oapen.identifier.doi | 10.3390/books978-3-03921-119-7 | * |
| oapen.relation.isPublishedBy | 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 | * |
| oapen.relation.isbn | 9783039211197 | * |
| oapen.relation.isbn | 9783039211180 | * |
| oapen.pages | 192 | * |
| oapen.edition | 1st | * |
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