A two-level over-voltage control strategy in distribution networks with high PV penetration

Emarati, Mohammadreza; Barani, Mostafa; Farahmand, Hossein; Aghaei, Jamshid; Granado, Pedro Crespo del

doi:10.1016/j.ijepes.2021.106763

Cited by 29 publications

(10 citation statements)

References 35 publications

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“…An optimization technique is developed in [42] to coordinate fast dispatch of PV inverters with OLTCs in a decentralized manner due to computational burden in centralized systems. Meanwhile, a two-level control algorithm incorporating OLTCs and BESSs with decentralized RPC is proposed in [43]. Multiple works in the literature have also developed control mechanisms based on droop control [44]- [45].…”

Section: Multiple Methods Have Been Proposed In the Literature To Ove...mentioning

confidence: 99%

A Sensitivity Matrix Approach Using Two-Stage Optimization for Voltage Regulation of LV Networks with High PV Penetration

Hassan¹,

Marikkar²,

Prabhath³

et al. 2021

Preprint

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The occurrence of voltage violations are a major deterrent for absorbing more roof-top solar power to smart Low Voltage Distribution Grids (LVDG). Recent studies have focused on decentralized control methods to solve this problem due to the high computational time in performing load flows in centralized control techniques. To address this issue a novel sensitivity matrix is developed to estimate voltages of the network by replacing load flow simulations. In this paper, a Centralized Active, Reactive Power Management System (CARPMS) is proposed to optimally utilize the reactive power capability of smart photo-voltaic inverters with minimal active power curtailment to mitigate the voltage violation problem. The developed sensitivity matrix is able to reduce the time consumed by 48% compared to load flow simulations, enabling near realtime control optimization. Given the large solution space of power systems, a novel two-stage optimization is proposed, where the solution space is narrowed down by a Feasible Region Search (FRS) step, followed by Particle Swarm Optimization (PSO). The performance of the proposed methodology is analyzed in comparison to the load flow method to demonstrate the accuracy and the capability of the optimization algorithm to mitigate voltage violations in near real-time. The deviation of mean voltages of the proposed methodology from load flow method was; 6.5 × 10 −3 p.u for reactive power control using Q-injection, 1.02 × 10 −2 p.u for reactive power control using Q-absorption, and 0 p.u for active power curtailment case.

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Section: Multiple Methods Have Been Proposed In the Literature To Ove...mentioning

confidence: 99%

A Sensitivity Matrix Approach Using Two-Stage Optimization for Voltage Regulation of LV Networks with High PV Penetration

Hassan¹,

Marikkar²,

Prabhath³

et al. 2021

Preprint

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“…The sampling control period (in seconds or minutes) is sufficiently small to track changes in power generation. The PV power generation is estimated using a linear forecast model [29, 30] as follows:

\begin{equation}p_{g,i}^{p,t + 1} = p_{g,i}^t + (1 - \eta )p_{g,i}^{t - 1}.\end{equation}

where η is the linearization coefficient and the value range is [0,1]. The predicted value of PV power generation at the next time is approximately expressed through the combination of PV power generation at the current time and the previous time.…”

Section: Local Voltage Predictive Control Problemmentioning

confidence: 99%

“…Solar and wind power are widely developed renewable energy sources owing to their availability and low cost. Owing to the intermittence and randomness of renewable energy generation, large-scale integration of distributed generation (DG) into a distribution network results in frequent voltage fluctuations and voltages exceeding specified limits [1,2]. With the rapid development of renewable energy sources, there is a necessity for real-time voltage control in the distribution network to ensure voltage safety, increase economic benefits, and improve the penetration rate of DG [3,4].…”

Section: Introductionmentioning

confidence: 99%

Local voltage predictive control of high PV‐penetrated distribution network based on voltage decoupling

Zeng

Hua³

et al. 2022

IET Renewable Power Gen

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With the awareness of global environmental protection, the generation of photovoltaic (PV) power is increasing rapidly. Local voltage/Var control is widely studied to overcome the real-time change in PV power generation. The stability condition of local controls is strictly dependent on the system information, and the control parameter is chosen considering both the stability condition and dynamic performance, which limits its scalability and makes the parameter setting difficult. In this work, the coupling between node voltages is separated in the prediction time, and a local voltage predictive control strategy is proposed to reduce the voltage deviation with respect to the reference voltage. The proposed control is implemented by using historical local data and current local measurements. The control parameter is the data length, which has less correlation with the system information, and the control performance is less sensitive to the control parameter. The proposed control can be regarded as a conventional local control with dynamic compensation, which improves the dynamic performance and the steady-state error. The proposed local control is tested on a practical distribution system. The simulation result demonstrates the proposed control achieves better performance than the conventional local control under different application scenarios and weather conditions.

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“…The use of batteries allows for flexibility without incurring any operating costs.The reactive power compensation capability of PV inverters can be used to regulate the voltage magnitude [32]. In this paper, we discuss only active power sourced from batteries.…”

Section: B Storage Flexibility-batteriesmentioning

confidence: 99%

The Impact of Uncertainty and Time Structure on Optimal Flexibility Scheduling in Active Distribution Networks

et al. 2021

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The authors focus on a model for system operators that uses centralized scheduling of multiple flexibility assets and services to minimize the cost of managing problems with grid congestion, voltages, and losses. The model schedules flexibility assets using stochastic optimization for AC optimal power flow in an active distribution network. The novelty of the contribution lies in its focus on how the dynamic capabilities of the flexibility resources are defined with regard to how uncertainty is resolved in the model. The impact of uncertainty is studied by using well-known quality measures from stochastic programming, such as the value of the stochastic solution. Moreover, the authors introduce a new measure related to the impact of representing uncertainty and flexibility when considering reactive power. By changing the time attributes of flexibility assets, the authors show the impact of uncertainty and time structure on a scheduling problem. The uncertainties considered are price and load levels. The findings reveal that the quality of the scheduling of each flexibility resource depends on using a stochastic model with a rigorous consideration of time and uncertainty.INDEX TERMS Flexibility, active distribution networks, optimal power flow, scheduling, stochastic programming, uncertainty. NOMENCLATURE

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A two-level over-voltage control strategy in distribution networks with high PV penetration

Cited by 29 publications

References 35 publications

A Sensitivity Matrix Approach Using Two-Stage Optimization for Voltage Regulation of LV Networks with High PV Penetration

A Sensitivity Matrix Approach Using Two-Stage Optimization for Voltage Regulation of LV Networks with High PV Penetration

Local voltage predictive control of high PV‐penetrated distribution network based on voltage decoupling

The Impact of Uncertainty and Time Structure on Optimal Flexibility Scheduling in Active Distribution Networks

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