Optimum design and control of grid integrated electrical hubs considering lifecycle cost and emission
(2016) 2016 IEEE International Energy Conference, ENERGYCON 2016- Abstract
Grid connected renewable energy systems are becoming popular due to reasons such as rapid escalation of energy prices, depletion of fossil fuel resources and pollutant emitted by conventional energy sources. Therefore, technologies for incorporating renewable energy technologies into the existing electricity grid needs to be researched more considering the changes in grid architecture. This study presents a novel method for optimum design and control of an Electric-Hub (EH) which consist of Solar PV panels, wind turbines, battery bank operating in a grid (low voltage) integrated mode. This study reports the simulation based optimization algorithm developed to obtain optimum system configuration and operation strategy considering two... (More)
Grid connected renewable energy systems are becoming popular due to reasons such as rapid escalation of energy prices, depletion of fossil fuel resources and pollutant emitted by conventional energy sources. Therefore, technologies for incorporating renewable energy technologies into the existing electricity grid needs to be researched more considering the changes in grid architecture. This study presents a novel method for optimum design and control of an Electric-Hub (EH) which consist of Solar PV panels, wind turbines, battery bank operating in a grid (low voltage) integrated mode. This study reports the simulation based optimization algorithm developed to obtain optimum system configuration and operation strategy considering two conflicting objectives; i.e. Levelized Energy Cost (LEC) and Leveliyed CO2 emission (LCO2). A detail energy flow model is developed to evaluate energy flow through wind turbines and SPV panels on hourly basis. Interaction with the battery bank and the Low-Voltage Grid (LVG) is determined using an expert system. Operating state of the system is determined based on renewable energy generation, Cost of Electricity (COE) in the LVG, state of charge of the battery bank. Subsequently, operating states of the expert system and configuration of the EH; i.e. type and capacity of SPV panels, wind turbines and battery bank is optimized using steady state ϵ-multi objective optimization technique. Seven Pareto solutions are selected at the end and analyzed the system configuration and control strategy.
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- author
- Perera, A. T D ; Nik, Vahid M. LU ; Mauree, Dasaraden and Scartezzini, Jean Louis
- organization
- publishing date
- 2016-07-14
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Electrical Hub, Energy-economic Dispatch, Evolutionary Algorithms, Multi Objective Optimization
- host publication
- 2016 IEEE International Energy Conference, ENERGYCON 2016
- article number
- 7513968
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 2016 IEEE International Energy Conference, ENERGYCON 2016
- conference location
- Leuven, Belgium
- conference dates
- 2016-04-04 - 2016-04-08
- external identifiers
-
- scopus:84982867293
- ISBN
- 9781467384636
- DOI
- 10.1109/ENERGYCON.2016.7513968
- language
- English
- LU publication?
- yes
- id
- 606ed879-da15-4a41-acf2-23482bf8a65f
- date added to LUP
- 2017-01-12 12:40:20
- date last changed
- 2022-04-01 05:38:39
@inproceedings{606ed879-da15-4a41-acf2-23482bf8a65f, abstract = {{<p>Grid connected renewable energy systems are becoming popular due to reasons such as rapid escalation of energy prices, depletion of fossil fuel resources and pollutant emitted by conventional energy sources. Therefore, technologies for incorporating renewable energy technologies into the existing electricity grid needs to be researched more considering the changes in grid architecture. This study presents a novel method for optimum design and control of an Electric-Hub (EH) which consist of Solar PV panels, wind turbines, battery bank operating in a grid (low voltage) integrated mode. This study reports the simulation based optimization algorithm developed to obtain optimum system configuration and operation strategy considering two conflicting objectives; i.e. Levelized Energy Cost (LEC) and Leveliyed CO2 emission (LCO2). A detail energy flow model is developed to evaluate energy flow through wind turbines and SPV panels on hourly basis. Interaction with the battery bank and the Low-Voltage Grid (LVG) is determined using an expert system. Operating state of the system is determined based on renewable energy generation, Cost of Electricity (COE) in the LVG, state of charge of the battery bank. Subsequently, operating states of the expert system and configuration of the EH; i.e. type and capacity of SPV panels, wind turbines and battery bank is optimized using steady state ϵ-multi objective optimization technique. Seven Pareto solutions are selected at the end and analyzed the system configuration and control strategy.</p>}}, author = {{Perera, A. T D and Nik, Vahid M. and Mauree, Dasaraden and Scartezzini, Jean Louis}}, booktitle = {{2016 IEEE International Energy Conference, ENERGYCON 2016}}, isbn = {{9781467384636}}, keywords = {{Electrical Hub; Energy-economic Dispatch; Evolutionary Algorithms; Multi Objective Optimization}}, language = {{eng}}, month = {{07}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, title = {{Optimum design and control of grid integrated electrical hubs considering lifecycle cost and emission}}, url = {{http://dx.doi.org/10.1109/ENERGYCON.2016.7513968}}, doi = {{10.1109/ENERGYCON.2016.7513968}}, year = {{2016}}, }