2014 Electric Power Quality and Supply Reliability Conference (PQ) 2014
DOI: 10.1109/pq.2014.6866796
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Optimal allocation of photovoltaic systems and energy storages in power systems considering power shortage and surplus

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Cited by 3 publications
(3 citation statements)
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“…A greedy algorithm is used in the aforementioned [22] to choose the nodes where to place storage devices, starting from storage available at all nodes, and shrinking their numbers while improving performances at each iteration. Genetic algorithmbased approaches for storage allocation are proposed in [23,31,32]. In [31], a market-based optimal power flow assuming generator marginal costs as an input determines the unit (de)commitment for each hour and local marginal prices to minimize the hourly social costs.…”
Section: Sizing and Siting Of Storage Systemsmentioning
confidence: 99%
“…A greedy algorithm is used in the aforementioned [22] to choose the nodes where to place storage devices, starting from storage available at all nodes, and shrinking their numbers while improving performances at each iteration. Genetic algorithmbased approaches for storage allocation are proposed in [23,31,32]. In [31], a market-based optimal power flow assuming generator marginal costs as an input determines the unit (de)commitment for each hour and local marginal prices to minimize the hourly social costs.…”
Section: Sizing and Siting Of Storage Systemsmentioning
confidence: 99%
“…In Ref [3], the authors determined the siting and sizing, in addition to the technology portfolios of ESSs. Moreover, some researchers have studied the allocation of DGs considering the contingencies in power systems [4][5][6][7]. A new method for the allocation of new generation capacity was presented, focusing on the fault level in power systems in Ref [4], but it did not consider the allocation of ESSs.…”
Section: Introductionmentioning
confidence: 99%
“…Furthermore, the curtailment of PV outputs was considered for alleviating power surpluses. Our previous study [7] focused on the above allocation problems under grid failures, but we did not consider the uncertainty in RE outputs. Moreover, the solution couldn't be precise because a genetic algorithm was employed on the large-scale optimization problem.…”
Section: Introductionmentioning
confidence: 99%