Analytical Estimation of Reactive Power Capability of a Radial Distribution System

Stanković, Stefan; Söder, Lennart

doi:10.1109/tpwrs.2018.2849875

Cited by 17 publications

(7 citation statements)

References 22 publications

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“…Assuming that DSOs and DGs are integrated, the TSO cannot access the DGs of the ADN. The DGs do not only take responsibility for local network constraints but also provide the RPAS for the transmission network as the main body [39]. To address the different clearing periods between the energy market and RPAS markets, the energy market‐clearing results are taken as the active power generation plan and the input data of the RPAS market.…”

Section: Problem Descriptionmentioning

confidence: 99%

An integrated market solution to enable active distribution network to provide reactive power ancillary service using transmission–distribution coordination

Chen

Lin

et al. 2021

IET Energy Syst Integration

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The active distribution network (ADN) can provide the reactive power ancillary service (RPAS) to improve the operations of the transmission network operations (such as voltage control and network loss reduction) as distribution generation grows. In this context, an RPAS market is required to motivate the ADN to provide the RPAS to the transmission network since the transmission system operator (TSO) and the distribution system operator (DSO) are different entities. Hence, to obtain the TSO–DSO coordination in the RPAS market, this study proposes a two‐stage market framework on the basis of the successive clearing of the energy and RPAS markets. Additionally, a distributed market‐clearing mechanism based on an alternating direction method of multipliers (ADMM) is adopted to guarantee TSO's and DSO's information privacy. Furthermore, a binary expansion (BE) method is used to linearise the non‐convex bilinear terms in the market‐clearing model. The effectiveness of the proposed RPAS market framework and distributed market‐clearing mechanism is validated using two different test systems with different system scales.

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Section: Problem Descriptionmentioning

confidence: 99%

An integrated market solution to enable active distribution network to provide reactive power ancillary service using transmission–distribution coordination

Chen

Lin

et al. 2021

IET Energy Syst Integration

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“…Standards for the connection of distribution systems to the transmission system in the European Union [67,68] allow the import and export of reactive energy at the connection points with the transmission system only to a limited extent. Moreover, reactive energy is generated in cable lines that are increasingly implemented in medium-and low-voltage networks [69][70][71].…”

Section: Introductionmentioning

confidence: 99%

Determination of the Optimal Level of Reactive Power Compensation That Minimizes the Costs of Losses in Distribution Networks

Andruszkiewicz,

Lorenc,

Weychan

2023

Energies

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The objective of the presented paper is to verify economically justified levels of reactive energy compensation in the distribution network in the new market conditions, including the extensive use of smart metering systems, new types of load, or distributed generation. The proposed methodology is based on the minimization of annual costs of losses caused by the flow of reactive energy to the supplied loads through the equivalent resistance of the distribution system determined on the basis of statistical energy losses in this network. The costs of losses are compared to the costs of using compensating devices expressed by the levelized costs of reactive energy generation. The results are the relations describing the optimal annual average value of the tgφ factor to be maintained by customers to optimize the cost of loss of the distribution network caused by reactive energy flows. The dependence of the optimal tgφ value on the analyzed load and network parameters is also discussed. The resulting optimal tgφ levels should be considered in the tariffication process of services offered by distribution system operators to improve capacity and limit the costs of power network operation due to reactive energy transmission.

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“…Stanković et. al., [4] The control of reactive power trade between frameworks of various voltage levels has dependably been a worry for system administrators. With creation moving from the transmission to the distribution level, its significance increments.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Approach for Reactive Power Compensation of Distribution Networks Using Particle Swarm Optimization

Dubey¹,

Ranvijay²

2020

IJOSCIENCE

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The power compensation is the one of the problem in distribution network. The power compensation is done by maintain the reactive power in distribution network. The power is maintain the state of the UPQC (Uni?ed power quality conditioner). The UPAC controlled by the STATCOM or DSTATCOM. Different approaches use to maintain the power at needed level in the power distribution network the process done by MOPSO optimization method the MOPSO is the best for this process because we consider the lot of objective function to optimize the place of the UPQC. In our proposed work we find the power level in distribution network using optimization algorithm. The optimization algorithm is used to optimization the power and find which place is suitable for place the STATCOM or DSTATCOM. This is used to maintain the reactive power in distribution network.

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Analytical Estimation of Reactive Power Capability of a Radial Distribution System

Cited by 17 publications

References 22 publications

An integrated market solution to enable active distribution network to provide reactive power ancillary service using transmission–distribution coordination

An integrated market solution to enable active distribution network to provide reactive power ancillary service using transmission–distribution coordination

Determination of the Optimal Level of Reactive Power Compensation That Minimizes the Costs of Losses in Distribution Networks

An Efficient Approach for Reactive Power Compensation of Distribution Networks Using Particle Swarm Optimization

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