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Optimisation Models and Methods in Energy Systems



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Autore: Antunes Carlos Henggeler Visualizza persona
Titolo: Optimisation Models and Methods in Energy Systems Visualizza cluster
Pubblicazione: MDPI - Multidisciplinary Digital Publishing Institute, 2019
Descrizione fisica: 1 electronic resource (192 p.)
Soggetto non controllato: mixed integer linear programming
fuzzy set theory
stochastic programming
mixed integer linear programing
variable renewable power
generation efficiency
optimization
flexibility option
portfolio analysis
firefighting
semi-mean-absolute deviation model
component outage
energy network
predicted mean vote (PMV)
generation expansion planning
building microgrid
demand side management
stochastic robust optimization
oil storage plants
long-term forecasting
multi-criteria decision making (MCDM)
life cycle cost
graph theory
scenario-based multistage stochastic programming
optimal power generation mix
heating ventilation and air-conditioning (HVAC)
intermittent sources
electric-power structure adjustment
technique for the order of preference by similarity to the ideal solution (TOPSIS)
integrated energy system
Markov chain Monte Carlo
nondominated sorting genetic algorithm (NSGA)
domino effect
energy system management model
electrical distribution systems
microgrid operation
influence diagram
net demand
wind power forecasting
energy conservation and emissions reduction
feasible operation region
meshed topology
occupancy-based control
islanded microgrids
combined heat and power
multi-objective optimization
re-optimization and rescheduling
Sommario/riassunto: 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.
Titolo autorizzato: Optimisation Models and Methods in Energy Systems  Visualizza cluster
ISBN: 3-03921-119-6
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910367569203321
Lo trovi qui: Univ. Federico II
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