Assessing the performance and benefits of customer distributed generation developers under uncertainties

Zangiabadi, Mansoureh; Feuillet, R.; Lesani, Hamid; Hadjsaïd, Nourédine; Kvaløy, Jan Terje

doi:10.1016/j.energy.2010.12.058

Cited by 35 publications

(16 citation statements)

References 29 publications

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“…Distributed generation uncertainties (Zangiabadi et al 2011) have been taken in account for the placement of DG. Alonso et al (2012), Rahim et al (2012), DoagouMojarrad et al (2013) and Hosseini et al (2013) proposed evolutionary algorithms for the placement of distributed generation.…”

Section: Introductionmentioning

confidence: 99%

Optimal DG placement for benefit maximization in distribution networks by using Dragonfly algorithm

Suresh

Edward

2018

Renewables

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Distributed generation (DG) is small generating plants which are connected to consumers in distribution systems to improve the voltage profile, voltage regulation, stability, reduction in power losses and economic benefits. The above benefits can be achieved by optimal placement of DGs. A novel nature-inspired algorithm called Dragonfly algorithm is used to determine the optimal DG units size in this paper. It has been developed based on the peculiar behavior of dragonflies in nature. This algorithm mainly focused on the dragonflies how they look for food or away from enemies. The proposed algorithm is tested on IEEE 15, 33 and 69 test systems. The results obtained by the proposed algorithm are compared with other evolutionary algorithms. When compared with other algorithms the Dragonfly algorithm gives best results. Best results are obtained from type III DG unit operating at 0.9 pf.

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Section: Introductionmentioning

confidence: 99%

Optimal DG placement for benefit maximization in distribution networks by using Dragonfly algorithm

Suresh

Edward

2018

Renewables

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“…These advantages include deferred investment, easier permitting, no transmission and distribution costs, improved reliability and/or security, reduced reserve requirements and associated costs, lower operating costs due to peak shaving or reduced electricity purchases, and potentially increased efficiency through use of the waste heat via combined heat and power approaches [8][9][10][11][12]. These advantages include deferred investment, easier permitting, no transmission and distribution costs, improved reliability and/or security, reduced reserve requirements and associated costs, lower operating costs due to peak shaving or reduced electricity purchases, and potentially increased efficiency through use of the waste heat via combined heat and power approaches [8][9][10][11][12].…”

Section: Advantages Of Distributed Generationmentioning

confidence: 99%

The Case for Natural Gas Fueled Solid Oxide Fuel Cell Power Systems for Distributed Generation

et al. 2014

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Natural‐gas‐fueled solid oxide fuel cell (NGSOFC) power systems yield electrical conversion efficiencies exceeding 55% and may become a viable alternative for distributed generation (DG) if stack life and manufacturing economies of scale can be realized. Currently, stacks last approximately 2 years and few systems are produced each year because of the relatively high cost of electricity from the systems. PNNL has performed cost modeling for production of 270 kW (DC) NGSOFC power systems, sized for light industry or large box stores. If mass manufacturing (10.000 units per year) and a stack life of 15 years can be reached, the cost of electricity from an NGSOFC system is estimated to be about 8,2 ¢/kWh, well within the range of commercial and residential retail prices at the national level (9,9–10 ¢/kWh and 11–12 ¢/kWh, respectively). With 5 ¢/kWh in estimated additional benefits from DG, NGSOFC could be well positioned to replace the forecasted 59–77 gigawatts of capacity loss resulting from coal plant closures due to stricter emissions regulations and low natural gas prices.

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“…The integration of DERs into power system operation through participating in the ancillary service markets for providing regulation, reserve services and voltage regulation are considered in [11][12][13][14][15][16][17]. In [18], the performance of customer-owned DG units is quantified from different perspectives through an uncertainty study. Implications and planning aspects of the interconnection of decentralized renewable resources into distribution grids are studied in [19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Decision making of a virtual power plant under uncertainties for bidding in a day-ahead market using point estimate method

Peikherfeh

Seifi

Sheikh‐El‐Eslami

2013

International Journal of Electrical Power & Energy Systems

197

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Assessing the performance and benefits of customer distributed generation developers under uncertainties

Cited by 35 publications

References 29 publications

Optimal DG placement for benefit maximization in distribution networks by using Dragonfly algorithm

Optimal DG placement for benefit maximization in distribution networks by using Dragonfly algorithm

The Case for Natural Gas Fueled Solid Oxide Fuel Cell Power Systems for Distributed Generation

Decision making of a virtual power plant under uncertainties for bidding in a day-ahead market using point estimate method

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