Multi-stage voltage control in high photovoltaic based distributed generation penetrated distribution system considering smart inverter reactive power capability

Tatikayala, Vinay Kumar; Dixit, Shishir

doi:10.1016/j.asej.2023.102265

Cited by 4 publications

(2 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Heuristic algorithms, valued for their ease of programming implementation, find widespread use in solving optimization problems in DNs. In the VVC problem of DNs, commonly used intelligent optimization algorithms include Genetic Algorithm [12], Particle Swarm Optimization [13], etc. However, heuristic algorithms are prone to converging towards local optima and have exponential time complexity in solving problems, making them inadequate for handling large-scale VVC problems.…”

Section: Introductionmentioning

confidence: 99%

Volt-VAR Control in Active Distribution Networks Using Multi-Agent Reinforcement Learning

Su,

Zhan,

Zhang

et al. 2024

Electronics

View full text Add to dashboard Cite

With the advancement of power systems, the integration of a substantial portion of renewable energy often leads to frequent voltage surges and increased fluctuations in distribution networks (DNs), significantly affecting the safety of DNs. Active distribution networks (ADNs) can address voltage issues arising from a high proportion of renewable energy by regulating distributed controllable resources. However, the conventional mathematical optimization-based approach to voltage reactive power control has certain limitations. It heavily depends on precise DN parameters, and its online implementation requires iterative solutions, resulting in prolonged computation time. In this study, we propose a Volt-VAR control (VVC) framework in ADNs based on multi-agent reinforcement learning (MARL). To simplify the control of photovoltaic (PV) inverters, the ADNs are initially divided into several distributed autonomous sub-networks based on the electrical distance of reactive voltage sensitivity. Subsequently, the Multi-Agent Soft Actor-Critic (MASAC) algorithm is employed to address the partitioned cooperative voltage control problem. During online deployment, the agents execute distributed cooperative control based on local observations. Comparative tests involving various methods are conducted on IEEE 33-bus and IEEE 141-bus medium-voltage DNs. The results demonstrate the effectiveness and versatility of this method in managing voltage fluctuations and mitigating reactive power loss.

show abstract

Section: Introductionmentioning

confidence: 99%

Volt-VAR Control in Active Distribution Networks Using Multi-Agent Reinforcement Learning

Su,

Zhan,

Zhang

et al. 2024

Electronics

View full text Add to dashboard Cite

show abstract

“…The optimization problem is multi-objective and the authors propose four different algorithms to transform this problem into a single-objective and solve it. In [29], CB and OLTC are optimized on the hourly scale and PV-DSTATCOM are optimized on the intra-hourly scale. The main goal is to minimize active and reactive power losses.…”

Section: Introductionmentioning

confidence: 99%

Multi-Stage Operation Optimization of PV-Rich Low-Voltage Distribution Networks

Dubravac,

Žnidarec,

Fekete

et al. 2023

Applied Sciences

View full text Add to dashboard Cite

The high expansion of a variable and intermittent nature of distributed generation, such as photovoltaics (PV), can cause technical issues in existing distribution networks (DN). In addition to producing electrical energy, PVs are inverter-based sources, and can help conventional control mechanisms in mitigating technical issues. This paper proposes a multi-stage optimal power flow (OPF)-based mixed-integer non-linear programming (MINLP) model for improving an operation state in LV PV-rich DN. A conventional control mechanism such as on load tap changer (OLTC) is used in the first stage to mitigate overvoltage caused by PVs. The second stage is related to reducing losses in DN using reactive power capabilities from PVs, which defines the optimization problem as a fully centralized observed from the distribution system operator’s (DSO) point of view. The optimization problem is realized under the co-simulation approach in which the power system analyzer and computational intelligence (CI) optimization method interact through an interface. This approach allows keeping the original MINLP model without approximations and using any computational intelligence method. OpenDSS is used as a power system analyzer, while particle swarm optimization (PSO) is used as a CI optimization method in this paper. Detailed case studies are performed and analyzed over a single-day period. To study validation and feasibility, the proposed model is evaluated on the IEEE LV European distribution feeder. The obtained results suggest that a combination of conventional control mechanisms (OLTC) and inverter-based sources (PVs) represent a promising solution for DSO and can serve as an alternative control method in active distribution networks.

show abstract

A Comprehensive Review on Recent Developments of Hosting Capacity Estimation and Optimization for Active Distribution Networks

Mousa,

Mahmoud,

Lehtonen

2024

IEEE Access

View full text Add to dashboard Cite

Recently, several types of distributed energy resources (DERs) have been developed to reduce the environmental impact and support the global demand for electrical energy. However, the continuous penetration of the DERs into modern power systems (MPSs) may cause several adverse impacts in terms of operation performance indices (PIs) and power quality issues, especially in low-voltage distribution systems (LVDSs). To cope with these serious impacts and achieve optimal control, the hosting capacity (HC) of DERs must be accurately estimated and optimally optimized. However, it requires an extensive communication infrastructure, which is hardly offered without clear financial benefits. In this regard, this article investigates the historical developments of HC definitions as well as the recent developments in terms of operational performance indices, and estimation methods for active distribution networks (ADNs) with the highpenetration level existence of the DERs, energy storage systems (ESSs), electric vehicle (EV) charging systems, sector coupling, hydrogen technologies, and multi-carrier energy systems (MESs) to deal with electrical, thermal, and cooling demands. In this regard, this review article is intended to exhibit an appropriate reference for comprehensive research trends in HC estimation and optimization based on ADNs. Additionally, it involves and covers most current research HC topics in detail compared to other published review articles. Moreover, the authors deliberate the recent approaches for evaluating and improving the HC, especially concerning data-driven methods, with the aid of various software for simulating real systems. Moreover, modern research trends and main factors of MPS operations are deliberated with current energy market developments. Also, prominent challenges, current status, and future aspects are discussed.

show abstract

Multi-stage voltage control in high photovoltaic based distributed generation penetrated distribution system considering smart inverter reactive power capability

Cited by 4 publications

References 35 publications

Volt-VAR Control in Active Distribution Networks Using Multi-Agent Reinforcement Learning

Volt-VAR Control in Active Distribution Networks Using Multi-Agent Reinforcement Learning

Multi-Stage Operation Optimization of PV-Rich Low-Voltage Distribution Networks

A Comprehensive Review on Recent Developments of Hosting Capacity Estimation and Optimization for Active Distribution Networks

Contact Info

Product

Resources

About