An improved particle swarm optimisation for unit commitment in microgrids with battery energy storage systems considering battery degradation and uncertainties
出版年份 2020 全文链接
标题
An improved particle swarm optimisation for unit commitment in microgrids with battery energy storage systems considering battery degradation and uncertainties
作者
关键词
-
出版物
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
Volume -, Issue -, Pages -
出版商
Wiley
发表日期
2020-09-01
DOI
10.1002/er.5867
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- (2020) Tae Hyun Kim et al. ENERGY
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- (2020) Farid Hamzeh Aghdam et al. Journal of Energy Storage
- Binary particle swarm optimisation with quadratic transfer function: A new binary optimisation algorithm for optimal scheduling of appliances in smart homes
- (2019) A. Rezaee Jordehi APPLIED SOFT COMPUTING
- Large-scale combined heat and power economic dispatch using a novel multi-player harmony search method
- (2019) Morteza Nazari-Heris et al. APPLIED THERMAL ENGINEERING
- Optimal operation of electrical and thermal resources in microgrids with energy hubs considering uncertainties
- (2019) Mohammad H. Shams et al. ENERGY
- Distribution system resilience enhancement by microgrid formation considering distributed energy resources
- (2019) Mohammad Amin Gilani et al. ENERGY
- Stochastic unit commitment in microgrids: Influence of the load forecasting error and the availability of energy storage
- (2019) Lázaro Alvarado-Barrios et al. RENEWABLE ENERGY
- A Comprehensive Battery Energy Storage Optimal Sizing Model for Microgrid Applications
- (2018) Ibrahim Alsaidan et al. IEEE TRANSACTIONS ON POWER SYSTEMS
- Introductory overview: Optimization using evolutionary algorithms and other metaheuristics
- (2018) H.R. Maier et al. ENVIRONMENTAL MODELLING & SOFTWARE
- Optimal energy management system based on stochastic approach for a home Microgrid with integrated responsive load demand and energy storage
- (2017) Mousa Marzband et al. Sustainable Cities and Society
- Time varying acceleration coefficients particle swarm optimisation (TVACPSO): A new optimisation algorithm for estimating parameters of PV cells and modules
- (2016) Ahmad Rezaee Jordehi ENERGY CONVERSION AND MANAGEMENT
- Stochastic Optimization of Renewable-Based Microgrid Operation Incorporating Battery Operating Cost
- (2016) Tu A. Nguyen et al. IEEE TRANSACTIONS ON POWER SYSTEMS
- Optimal scheduling of a microgrid with a fuzzy logic controlled storage system
- (2015) Juan P. Fossati et al. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
- State of the Art in Research on Microgrids: A Review
- (2015) Sina Parhizi et al. IEEE Access
- Microgrid Optimal Scheduling With Multi-Period Islanding Constraints
- (2014) Amin Khodaei IEEE TRANSACTIONS ON POWER SYSTEMS
- Stochastic scenario-based model and investigating size of battery energy storage and thermal energy storage for micro-grid
- (2014) Sirus Mohammadi et al. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
- Parameter selection in particle swarm optimisation: a survey
- (2013) A. Rezaee Jordehi et al. JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE
- Optimal control of a residential microgrid
- (2012) Phillip Oliver Kriett et al. ENERGY
- S-shaped versus V-shaped transfer functions for binary Particle Swarm Optimization
- (2012) Seyedali Mirjalili et al. Swarm and Evolutionary Computation
- Comparison of different approaches for lifetime prediction of electrochemical systems—Using lead-acid batteries as example
- (2007) Dirk Uwe Sauer et al. JOURNAL OF POWER SOURCES
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