Voltage regulation methods for active distribution networks considering the reactive power optimization of substations

Ma, Wei; Wang, Wei; Chen, Zhe; Wu, Xuezhi; Hu, Ruonan; Tang, Fen; Zhang, Weige

doi:10.1016/j.apenergy.2020.116347

Cited by 45 publications

(24 citation statements)

References 35 publications

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“…ESSs can charge from or discharge to the ADN, while satisfying the following operational constraints. Specifically, the temporal relationship between the energy and the power of the ESS is given in (21). The maximum and minimum allowable energy stored in the ESS is set by (22).…”

Section: Energy Storage Systemmentioning

confidence: 99%

“…) is a diagonal weight matrix; R t represents the reference trajectory corresponding to Y t at time span t; 0 denotes vector or matrix with all entries of 0; and I N ESS ∈ R N ESS ×N ESS and I N PV ∈ R N PV ×N PV are identity matrices. Note that the values of the matrices F X and F U are obtained according to (21) and the definition of the state variables X t and the control variables U t .…”

Section: Intra-day Corrective Adjustmentmentioning

confidence: 99%

“…Thus, reactive power dispatch and control are widely used to raise the voltage profiles and thereby pursue a better voltage stability, as in [18,19]. On the other hand, the inverter-interfaced distributed generations (DGs) can serve as reactive power sources, which have been used for volt ampere reactive (VAR) support, as in [20,21]. The process is driven by economic incentives or the reactive power ancillary service market [22] and is realized through the appropriate control of the power converters.…”

Section: Introductionmentioning

confidence: 99%

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Multi-Time-Scale Optimal Scheduling in Active Distribution Network with Voltage Stability Constraints

2021

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The uncertainty associated with loads and renewable-energy sources affects active distribution networks in terms of the operation and voltage stability on different time scales. To address this problem, a multi-time-scale voltage stability constrained optimal scheduling framework is proposed, which includes a day-ahead model with a coarse-grained time resolution and an intra-day model with a fine-grained time resolution. The day-ahead economic-scheduling model maps out a scheme to operate different types of devices with the aim of minimizing the network losses. Following the scheme, the intra-day corrective-adjustment model based on model predictive control is proposed to regulate the flexible devices, such as the energy storage systems and the photovoltaic converters. In particular, the proposed optimal scheduling framework embeds a voltage stability constraint which is constructed by using a novel index, defined based on the Distflow model Jacobian. As the index at each bus is a linear function of the locally measurable power flow variables, the proposed constraint does not introduce additional computational burdens. Simulation results demonstrate the necessity and effectiveness of the proposed multi-time-scale voltage stability constrained optimal scheduling model. The results also show that the variation trend of the proposed index is consistent with that of the commonly used voltage stability index.

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Section: Energy Storage Systemmentioning

confidence: 99%

Section: Intra-day Corrective Adjustmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multi-Time-Scale Optimal Scheduling in Active Distribution Network with Voltage Stability Constraints

2021

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“…Voltage control methodologies have been developed to ensure network voltage within acceptable limits [9]. Conventional voltage regulation methods that depend on an onload tap changer (OLTC) and VAR compensation devices, such as step voltage regulators (SVRs) and switched capacitor banks (SCBs), cannot effectively control the voltage profile as the devices have a slow response, and discrete actions and independent control mechanisms [9][10][11][12][13][14][15]. In an LV network, voltage is regulated by manual branch switches instead of automation.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Voltage and Reactive Power Algorithms in Low Voltage Networks

Stanelytė

Radziukynas

2022

Energies

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The rapid development of renewable energy sources and electricity storage technologies is further driving the change and evolution of traditional energy systems. The aim is to interconnect the different electricity systems between and within countries to ensure greater reliability and flexibility. However, challenges are faced in reaching it, such as the power grid complexity, the system control, voltage fluctuations due to the reverse power flow, equipment overloads, resonance, incorrect island setting, and the diversity of user needs. The electricity grid digitalization in the market also requires the installation of smart devices to enable real-time information exchange between the generator and the user. Inverter-based distributed generation (DG) may be used to control the grid voltage. Smart PV inverters have the capability to supply both inductive and capacitive reactive power to control the voltage at the point of interconnection with the grid, and only technical parameters of smart PV inverters limit this capability. Reactive power control is related to ensuring the quality of voltage in the electricity distribution network and compensating reactive power flows, which is a technical–economic aspect. The goal of this research is to present an analysis of controllers that supply reactive power to the electrical grid via PV systems. This research analyzes recent research on local, centralized, distributed, and decentralized voltage control models in distribution networks. The article compares various approaches and highlights their advantages and disadvantages. The voltage control strategies and methodologies mentioned in the article can serve as a theoretical foundation and provide practical benefits for PV system development in distribution networks. The results of the research show that the local voltage control approach, as well as linear and intelligent controllers, has great potential.

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“…Here, the PV inverter control settings were determined by the circuit loading, time of day and PV location in the network. A combination of centralized and decentralized control strategies utilising OLTCs and Capacitor Banks (CBs) was also proposed in [47,54]. It further analysed the impact on the substation end and the effect of unbalance in phases in PV integration.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2021

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The occurrence of voltage violations is a major deterrent for absorbing more rooftop solar power into smart Low-Voltage Distribution Grids (LVDGs). 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 was developed to estimate the 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 Photovoltaic (PV) inverters with minimal active power curtailment to mitigate the voltage violation problem. The developed sensitivity matrix is able to reduce the time consumed by 55.1% compared to load flow simulations, enabling near-real-time 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 failure of standalone PSO to converge to a feasible solution for 34% of the scenarios evaluated further validates the necessity of the two-stage optimization using FRS. The performance of the proposed methodology was analysed 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 deviations of the mean voltages of the proposed methodology from the load flow method were: 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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Voltage regulation methods for active distribution networks considering the reactive power optimization of substations

Cited by 45 publications

References 35 publications

Multi-Time-Scale Optimal Scheduling in Active Distribution Network with Voltage Stability Constraints

Multi-Time-Scale Optimal Scheduling in Active Distribution Network with Voltage Stability Constraints

Analysis of Voltage and Reactive Power Algorithms in Low Voltage Networks

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

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