Distributed generation output control for network power flow management

Jupe, Samuel; Taylor, Phil

doi:10.1049/iet-rpg.2008.0029

Cited by 41 publications

(30 citation statements)

References 8 publications

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“…In particular the work presented in this paper draws on and extends the research by Jupe and Taylor [17] which linked PFSF with thermally vulnerable network components. However, instead of using PFSFs to developed distributed generation control strategies, the research presented in this paper applies part of the methodology in [17] to assess the value of applying real power reductions at different load points, using DSP, to relieve thermally constrained components and defer network reinforcement.…”

Section: B Stage 2: Power Flow Sensitivity Factors and Thermal Vulnementioning

confidence: 81%

An interdisciplinary method to demand side participation for deferring distribution network reinforcement

Lawson

Taylor

Bell

et al. 2011

2011 2nd IEEE PES International Conference and Exhibition on Innovative Smart Grid Technologies

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This paper presents an interdisciplinary sociotechnical methodology for quantifying the value of demand side participation (DSP) in deferring network reinforcement. The methodology forecasts how many years load growth a section of network can accommodate before components exceed their standard rating. The approach identifies components within the network which are thermally vulnerable and uses power flow sensitivity factors to assess the value of applying real power reductions, through demand side participation, at different substations to relieve thermally constrained components. The third stage of the methodology socially characterises the load points. This is achieved by using socio-demographic data to map out the number and type of customers connected to each load point. This information is used to gauge the potential social acceptance of demand side participation schemes for different types of consumer. The final stage combines the power flow sensitivity factors, calculated in stage 2, with the social findings, calculated in stage 3, to calculate the optimum socio-technical solution. The methodology is illustrated by a case study that uses an existing rural distribution network in northern England.

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Section: B Stage 2: Power Flow Sensitivity Factors and Thermal Vulnementioning

confidence: 81%

An interdisciplinary method to demand side participation for deferring distribution network reinforcement

Lawson

Taylor

Bell

et al. 2011

2011 2nd IEEE PES International Conference and Exhibition on Innovative Smart Grid Technologies

View full text Add to dashboard Cite

show abstract

“…The branches thermal loading sensitivities, which are obtained through the inverse Jacobian, lay the foundation of the nonfirm DG operating strategies in [18], [20], and [21]. The branches sensitivities are also used for the network thermal loading management in the nonfirm DWG operation model in [24] and [26].…”

Section: Branch Thermal Loading Sensitivitymentioning

confidence: 99%

Autonomous Curtailment Control in Distributed Generation Planning

Džamarija

Keane

2016

IEEE Trans. Smart Grid

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While enabling prominent growth of renewablebased distributed generation (DG) and matching energy harvesting, nonfirm connection policy requires accompanying active and reactive power dispatch control. Centralized control often implies comprehensive communication infrastructure and notable capital investment. Hence, DG planning models tailored for decentralized management of thermal and voltage constraints are found wanting. This paper presents a DG planning methodology, which successfully incorporates a new decentralized active power curtailment control and also includes decentralized voltage control. It optimizes autonomous control settings for each generator individually, such that the net energy export from the distribution to transmission level, per unit of installed capacity, is maximized. Comparative time series analysis validates the methodology.Index Terms-Distributed generation (DG), network planning, optimal power flow (OPF), power curtailment control.

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“…Dynamic line ratings, taking into account the cooling effect of the wind together with ambient temperature in determining the transmission constraints, can increase transmission capacity and/or delay the need for network expansion (Abdelkader et al, 2009;Hur et al, 2010). In the UK, some wind projects accept curtailments in order to lower the connection cost to the (distribution) grid that otherwise would need reinforcements (Jupe and Taylor, 2009;Jupe et al, 2010). Curtailment was particularly high in Texas in 2009 with 17% of all potential wind energy generation within the Electric Reliability Council of Texas curtailed (Wiser and Bolinger, 2010).…”

Section: Integration Experiencementioning

confidence: 99%