Optimisation Models and Methods in Energy Systems
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 o...
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| Format: | Book Chapter |
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MDPI - Multidisciplinary Digital Publishing Institute
2019
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| Subjects: | |
| Online Access: | Get Fullteks DOAB: description of the publication |
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| LEADER | 03308naaaa2200805uu 4500 | ||
|---|---|---|---|
| 001 | doab_20_500_12854_55325 | ||
| 005 | 20210211 | ||
| 020 | |a books978-3-03921-119-7 | ||
| 020 | |a 9783039211197 | ||
| 020 | |a 9783039211180 | ||
| 024 | 7 | |a 10.3390/books978-3-03921-119-7 |c doi | |
| 041 | 0 | |a English | |
| 042 | |a dc | ||
| 100 | 1 | |a Antunes, Carlos Henggeler |4 auth | |
| 245 | 1 | 0 | |a Optimisation Models and Methods in Energy Systems |
| 260 | |b MDPI - Multidisciplinary Digital Publishing Institute |c 2019 | ||
| 300 | |a 1 electronic resource (192 p.) | ||
| 506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
| 520 | |a 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. | ||
| 540 | |a Creative Commons |f https://creativecommons.org/licenses/by-nc-nd/4.0/ |2 cc |4 https://creativecommons.org/licenses/by-nc-nd/4.0/ | ||
| 546 | |a English | ||
| 653 | |a mixed integer linear programming | ||
| 653 | |a fuzzy set theory | ||
| 653 | |a stochastic programming | ||
| 653 | |a mixed integer linear programing | ||
| 653 | |a variable renewable power | ||
| 653 | |a generation efficiency | ||
| 653 | |a optimization | ||
| 653 | |a flexibility option | ||
| 653 | |a portfolio analysis | ||
| 653 | |a firefighting | ||
| 653 | |a semi-mean-absolute deviation model | ||
| 653 | |a component outage | ||
| 653 | |a energy network | ||
| 653 | |a predicted mean vote (PMV) | ||
| 653 | |a generation expansion planning | ||
| 653 | |a building microgrid | ||
| 653 | |a demand side management | ||
| 653 | |a stochastic robust optimization | ||
| 653 | |a oil storage plants | ||
| 653 | |a long-term forecasting | ||
| 653 | |a multi-criteria decision making (MCDM) | ||
| 653 | |a life cycle cost | ||
| 653 | |a graph theory | ||
| 653 | |a scenario-based multistage stochastic programming | ||
| 653 | |a optimal power generation mix | ||
| 653 | |a heating ventilation and air-conditioning (HVAC) | ||
| 653 | |a intermittent sources | ||
| 653 | |a electric-power structure adjustment | ||
| 653 | |a technique for the order of preference by similarity to the ideal solution (TOPSIS) | ||
| 653 | |a integrated energy system | ||
| 653 | |a Markov chain Monte Carlo | ||
| 653 | |a nondominated sorting genetic algorithm (NSGA) | ||
| 653 | |a domino effect | ||
| 653 | |a energy system management model | ||
| 653 | |a electrical distribution systems | ||
| 653 | |a microgrid operation | ||
| 653 | |a influence diagram | ||
| 653 | |a net demand | ||
| 653 | |a wind power forecasting | ||
| 653 | |a energy conservation and emissions reduction | ||
| 653 | |a feasible operation region | ||
| 653 | |a meshed topology | ||
| 653 | |a occupancy-based control | ||
| 653 | |a islanded microgrids | ||
| 653 | |a combined heat and power | ||
| 653 | |a multi-objective optimization | ||
| 653 | |a re-optimization and rescheduling | ||
| 856 | 4 | 0 | |a www.oapen.org |u https://mdpi.com/books/pdfview/book/1476 |7 0 |z Get Fullteks |
| 856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/55325 |7 0 |z DOAB: description of the publication |