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Demand-side management using a distributed initialisation-free optimisation in a smart grid
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DOI：10.1049/iet-rpg.2018.5858.png)
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摘要
En 中文
Due to the integration of the renewable generation and the distributed load that inherently uncertain and unpredictable, developing an efficient distributed management structure of such a complex system remains a challenging issue. Most of the existing works on the demand-side management concentrate on the centralised methods or need a proper initialisation process. This study proposed a demand-side management strategy that can solve the optimisation problem in a distributed manner without initialisation. The objective of the designed demand management system is to maximise the social welfare of a smart grid by controlling the active power economically. The proposed optimisation strategy that generates the optimal power references uses the neighbouring information while considering the local feasible constraints by using a projection operation. Furthermore, the optimisation algorithm is initialisation free, which avoids any initialisation process when plugging-in new customers or plugging-out power units, such as demand loads, battery energy storage systems and distributed generators. The proposed strategy only uses the neighbouring information, so that the proposed approach is scalable and potentially applicable to large-scale smart grids. The effectiveness and scalability of the proposed algorithm are established and verified through case studies.
Keyword:
distributed power generation
optimisation
power system management
smart power grids
power generation economics
energy storage
distributed initialisation-free optimisation
smart grid
renewable generation
distributed load
efficient distributed management structure
complex system
challenging issue
existing works
demand-side management concentrate
centralised methods
proper initialisation process
demand-side management strategy
large-scale smart grids
generators
battery energy storage systems
demand loads
power units
optimisation algorithm
local feasible constraints
neighbouring information
optimal power references
optimisation strategy
active power
social welfare
designed demand management system
distributed manner
optimisation problem
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