Quantitative Risk Management by Demand Response in Distribution Networks

Sgouras, Kallisthenis I.; Dimitrelos, Dimitrios I.; Bakirtzis, Anastasios G.; Labridis, Dimitris P.

doi:10.1109/tpwrs.2017.2728610

Cited by 21 publications

(14 citation statements)

References 45 publications

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“…This paper utilises an expected load not served (ELNS) index for measuring the reliability of the system as presented in [32]. Equation (34) [28] and divided into three categories, low consumption (2-8), offpeak (1, 9, 14-16, 23, 24) and peak (10)(11)(12)(13)(17)(18)(19)(20)(21)(22) h. Furthermore, the price elasticity matrices are extracted from [18]. The value of the maximum incremental cost of energy generation of each production unit is supposed as the deployed up-and down-spinning reserves.…”

Section: Reliability Assessmentmentioning

confidence: 99%

“…Although the problem formulation is a 'two stage' problem, it is solved in one step. It is noteworthy that the solving engine of MATPOWER Optimal Scheduling Tool (MOST) can be also CPLEX as a high-performance solver to study stochastic day-ahead (SCUC) and DR problems [21,22]. Therefore, the solving engine of both MOST and GAMS can be the same.…”

Section: Introductionmentioning

confidence: 99%

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Power system flexibility improvement with a focus on demand response and wind power variability

Dadkhah¹,

Vahidi²,

Shafie‐khah³

et al. 2020

IET Renewable Power Generation

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Unpredictable system component contingencies have imposed vulnerability on power systems, which are under high renewables penetration nowadays. Intermittent nature of renewable energy sources has made this unpredictability even worse than before and calls for excellent adaptability. This study proposes a flexible security-constrained structure to meet the superior flexibility by coordination of generation and demand sides. In the suggested model, demand-side flexibility is enabled via an optimum real-time (RT) pricing program, while the commitment of conventional units through providing up and down operational reserves improves the flexibility of supply-side. The behaviour of two types of customers is characterised to define an accurate model of demand response and the effect of customers' preferences on the optimal operation of power networks. Conclusively, the proposed model optimises RT prices in the face of contingency events as well as wind power penetration. System operators together with customers could benefit from the proposed method to schedule generation and consumption units reliably.

show abstract

Section: Reliability Assessmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Power system flexibility improvement with a focus on demand response and wind power variability

Dadkhah¹,

Vahidi²,

Shafie‐khah³

et al. 2020

IET Renewable Power Generation

View full text Add to dashboard Cite

show abstract

“…[7] and [8]. Recent studies have explored the use of utility owned DERs to manage outages and improve the reliability of distribution systems, especially when these DERs comprise dispatchable technologies, such as battery storage [9], electric vehicles (EV) [10,11] and demand response (DR) [12,13], or when located in active portions of the distribution system, e.g. microgrids [14].…”

Section: Introductionmentioning

confidence: 99%

The effect of rate design on power distribution reliability considering adoption of distributed energy resources

2020

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Electricity rates are a main driver for adoption of Distributed Energy Resources (DERs) by private consumers. In turn, DERs are a major component of the reliability of energy access in the long run. Defining reliability indices in a paradigm where energy is generated both behind and in front of the meter is part of an ongoing discussion about the future role of utilities and system operators with many regulatory implications. This paper contributes to that discussion by analyzing the effect of rate design on the long term reliability indices of power distribution. A methodology to quantify this effect is proposed and a case study involving photovoltaic (PV) and storage technology adoption in California is presented. Several numerical simulations illustrate how electricity rates affect the grid reliability by altering dispatch and adoption of the DERs. We further document that the impact of rate design on reliability can be very different from the perspective of the utility versus that of the consumers. Our model affirms the positive connection between investments in DERs and the grid reliability and provides an additional tool to policy-makers for improving the reliability of the grid in the long term.

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“…In this request side, with the improvement of double correspondence, estimation &demand reaction innovation, the controllability of the mechanical and private burden is hugely upgraded [7][8]. When the framework is in a crisis task express, the system topology modification strategy, for example, load move is likewise a powerful methods for hazard control, particularly the network dynamic division innovation can rapidly and precisely search and alter explicit crisis plans So as to adapt to the referenced issue of PV incorporated power framework chance appraisal and control, the current investigations primarily center around the accompanying viewpoints: 1) a few researchers make a solid examination of network operational hazard sources and segregate hazard variables as per the key components in the PV power plant and power lattice [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Enhancing the Performance of DPFC on Dc Side Using Reboost Converter

2020

jcr

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Quantitative Risk Management by Demand Response in Distribution Networks

Cited by 21 publications

References 45 publications

Power system flexibility improvement with a focus on demand response and wind power variability

Power system flexibility improvement with a focus on demand response and wind power variability

The effect of rate design on power distribution reliability considering adoption of distributed energy resources

Enhancing the Performance of DPFC on Dc Side Using Reboost Converter

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