Provision of Voltage Ancillary Services Through Enhanced TSO-DSO Interaction and Aggregated Distributed Energy Resources

Rousis, Anastasios Oulis; Tzelepis, Dimitrios; Pipelzadeh, Yousef; Štrbac, Goran; Booth, Campbell; Green, Tim

doi:10.1109/tste.2020.3024278

Cited by 27 publications

(11 citation statements)

References 30 publications

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“…Some of the reviewed papers added reactive power to MGs bidding strategy; for instance, in [20] arbitrage strategy of virtual power plants in coupled energy, reactive, and spinning reserve markets is modeled by considering power systems reliability and MGs profit. The first goal of [21] is to present a strategy to coordinate DER and traditional resources for providing a stable voltage and having safe and stable power system. In [22], a novel control scheme is presented to illustrate the undeniable effect of renewable AS in systems with high penetration of RES by using smart inverters of PV systems and limiting the voltage and frequency fluctuations.…”

Section: B Literature Reviewmentioning

confidence: 99%

Stochastic-Risk Based Approach for Microgrid Participation in Joint Active, Reactive, and Ancillary Services Markets Considering Demand Response

Nikpour

Nateghi

Shafie‐khah

2023

IEEE Open J. Power Energy

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In the restructured power systems, renewable energy sources (RES) have been developed. Uncertainties of these generators reduce the reliability and stability of power systems. The frequency and voltage for the correct operation of the power systems must always be maintained within a nominal value. Ancillary services (AS), energy storage systems (ESS), and demand response programs (DRPs) can be effective solutions for mentioned problems. Microgrids (MG) can make an improvement in their profits and efficiency by participating in various markets. This paper provides an optimal scheduling for the simultaneous participation of MGs in coupled active, reactive power and AS markets (regulation, spinning reserve and non-spinning reserve) by considering ESS, DRPs, call for deploying AS, and the uncertainties of wind and solar productions. Capability diagrams; mathematical equations are used to model active and reactive power of generation units. Risk management in this paper is done by the conditional value at risk (CVaR) method and probability distribution functions (PDF) are used for modeling uncertainties of wind speed and solar radiation. The ERCOT (Electric Reliability Council of Texas) market is simulated with real world data.

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Section: B Literature Reviewmentioning

confidence: 99%

Stochastic-Risk Based Approach for Microgrid Participation in Joint Active, Reactive, and Ancillary Services Markets Considering Demand Response

Nikpour

Nateghi

Shafie‐khah

2023

IEEE Open J. Power Energy

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“…wind farm) [33]. The SG has been modelled as a standard salient-pole synchronous machine rated at 102 MVA, integrating automatic voltage regulator, a power system stabilizer and over-excitation limiters [34]. The wind farm consists of the 50 × 2 MVA variable speed wind turbines, yielding a total of 100 MVA.…”

Section: B Power Systems Modelmentioning

confidence: 99%

Time-Domain Protection of Superconducting Cables Based on Artificial Intelligence Classifiers

et al. 2022

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Fault detection and protection of Superconducting Cables (SCs) is considered a challenging task due to the effects of the quenching phenomenon of High Temperature Superconducting (HTS) tapes and the prospective magnitude of fault currents in presence of highly-resistive faults and converter-interfaced generation. This paper presents a novel, time-domain method for discriminative detection of faults in a power system incorporating SCs and high penetration of renewable energy sources. The proposed algorithms utilises feature extraction tools based on Stationary Wavelet Transform (SWT), as well as artificial intelligence (AI) classifiers to discriminate between external and internal faults, and other network events. The performance of the proposed schemes has been validated in electromagnetic transient simulation environment using a verified model of SC. Simulation results revealed that the proposed algorithms can effectively and within short period of time discriminate internal faults occurring on SC, while remain stable to external faults and other disturbances. The suitability of the proposed algorithms for real-time implementation has been verified using software and hardware in the loop testing environment. To determine the best options for real-time deployment, two different artificial intelligence classifiers namely Artificial Neural Network (ANN) and Support Vector Machine (SVM) have been deployed. The extensive assessment of their performance revealed that the ANN classifier is advantageous in term of prediction speed.

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“…An interesting aspect of the flexibility offered by DERs lies in their reactive power capabilities and how they can be utilized to provide coordinated voltage ancillary services at the points of interconnection between the distribution and transmission network [12], [13]. It should be ensured that the activation of this flexibility does not violate the distribution network constraints or has undesirable effects in the distribution network operation.…”

Section: Introductionmentioning

confidence: 99%

An Effective Method to Estimate the Aggregated Flexibility at Distribution Level

Savvopoulos

Hatziargyriou

2023

IEEE Access

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The exploitation of flexibility services provided by distributed energy resources (DERs) located in the distribution grid becomes increasingly important for the secure and reliable operation of power systems. These resources are typically small-scale and located close to end-users, however their aggregated flexibility can offset the imbalance caused by the stochastic variations of the renewable power sources. This paper proposes a methodology to estimate with increased accuracy the available flexibility of DERs in an Active Distribution Grid (ADG) at the points of interconnection with the transmission system. An optimization-based approach is used to estimate the available maximum active and reactive power flexibility at each TSO-DSO substation for specific directions formed by constant active to reactive power ratios. In order to keep calculations manageable and calculate the available flexibility with high accuracy, the search directions are sampled from a distribution that is iteratively updated at each step. Three variations are proposed for the angle sampling, both in the angle domain and in the p-q domain. Each variation is tested on a modified 18-bus radial distribution system and its effectiveness and convergence is compared.

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Provision of Voltage Ancillary Services Through Enhanced TSO-DSO Interaction and Aggregated Distributed Energy Resources

Cited by 27 publications

References 30 publications

Stochastic-Risk Based Approach for Microgrid Participation in Joint Active, Reactive, and Ancillary Services Markets Considering Demand Response

Stochastic-Risk Based Approach for Microgrid Participation in Joint Active, Reactive, and Ancillary Services Markets Considering Demand Response

Time-Domain Protection of Superconducting Cables Based on Artificial Intelligence Classifiers

An Effective Method to Estimate the Aggregated Flexibility at Distribution Level

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