Maximum Hosting Capacity Assessment of Distribution Systems With Multitype DERs Using Analytical OPF Method

Hassan, S Jarjees Ul; Gush, Teke; Kim, Chul‐Hwan

doi:10.1109/access.2022.3207488

Cited by 10 publications

(4 citation statements)

References 25 publications

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“…Based on the time-varying generations and demands from measurement devices, and historical data, the time series methods are applied easily in short-term timescales to avoid increasing complexity or computational times [93]. Various recent articles applied these approaches for estimating the DSF [94][95][96][97][98][99][100][101].…”

Section: Conventional Approachesmentioning

confidence: 99%

Recent developments of demand‐side management towards flexible DER‐rich power systems: A systematic review

Mousa,

Mahmoud,

Lehtonen

2024

IET Generation Trans & Dist

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Recently, various distributed energy resources are significantly integrated into the modern power systems. This introduction of distributed energy resource‐rich systems can cause various power quality issues, due to their uncertainties and capacity variations. Therefore, it is crucial to establish energy balance between generation and demand to improve power system's reliability and stability and to minimize energy costs without sacrificing customers’ comfort or utility. In this regard, power system flexibility concept is highlighted as a robust and cost‐effective energy management system, especially on the demand side, to provide consumers’ demands with an acceptable level of power quality. Accordingly, here, a comprehensive review of recent developments in the power system flexibility and demand‐side management strategies and demand response programs are provided to include mainly classifications, estimation methods, distributed energy resource modelling approaches, infrastructure requirements, and applications. In addition, current research topics for applying power system flexibility solutions and demand‐side management strategies based on modern power system operation are deliberated. Also, prominent challenges, research trends, and future perspectives are discussed. Finally, this review article aims to be an appropriate reference for comprehensive research trends in the power system flexibility concept in general and in demand‐side management strategies and demand response programs, specifically.

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Section: Conventional Approachesmentioning

confidence: 99%

Recent developments of demand‐side management towards flexible DER‐rich power systems: A systematic review

Mousa,

Mahmoud,

Lehtonen

2024

IET Generation Trans & Dist

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“…Wang et al [16] showed that the risk of system voltage is reduced through the allocation of VaR capacity of inverters in an economical way. Hassan et al [17] proposed the evaluation of network hosting capacity to integrate the maximum installed capacity of DERs in a distribution system by observing the operating range. The work presented in [18] dealt with the methods of evaluating and upgrading the hosting capacity of the distribution network through a comprehensive review of various research studies and practical projects.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Thus, the loading constraints are modeled by Equations ( 17)- (22). According to (17), a transformer's loading must not violate a specified limit, which is, from the authors' experience, about 80% of its rating. W ty is the rating of DT t at Year y, which is obtained as (18).…”

Section: Operational Constraintsmentioning

confidence: 99%

Developing an Integration of Smart-Inverter-Based Hosting-Capacity Enhancement in Dynamic Expansion Planning of PV-Penetrated LV Distribution Networks

et al. 2023

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With the penetration of distributed energy resources (DERs), new network challenges arise that limit the hosting capacity of the network, which consequently makes the current expansion-planning models inadequate. Smart inverters as a promising tool can be utilized to enhance the hosting capacity. Therefore, in response to technical, economic, and environmental challenges, as well as government support for renewable resources, especially domestic solar resources located at the point of consumption, this paper is an endeavor to propose a smart-inverter-based low-voltage (LV) distribution expansion-planning model. The proposed model is capable of dynamic planning, where multiple periods are considered over the planning horizon. In this model, a distribution company (DISCO), as the owner of the network, intends to minimize the planning and operational costs. Optimal loading of transformers is considered, which is utilized to operate the transformers efficiently. Here, to model the problem, a mixed-integer nonlinear programming (MINLP) model is utilized. Using the GAMS software, the decision variables of the problem, such as the site and size of the installation of distribution transformers, and their service areas specified by the LV lines over the planning years, and the reactive power generation/absorption of the smart inverters over the years, seasons, and hours are determined. To tackle the operational challenges such as voltage control in the points of common coupling (PCC) and the limitations in the hosting capacity of the network for the maximized penetration level of PV cells, a smart-inverter model with voltage control capability in PCC points is integrated into the expansion-planning problem. Then, a two-stage procedure is proposed to integrate the reactive power exchange capability of smart inverters in the distribution expansion planning. Based on the simulations of a residential district with PV penetration, results show that by a 14.7% share of PV energy generation, the loss cost of LV feeders is reduced by 28.3%. Also, it is observed that by optimally making use of the reactive power absorption capability of the smart inverters, the hosting capacity of the network is increased by 50%.

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“…Despite the simplifications of the network model and size to fit in the optimization formulation, it is time-consuming and impractical for large-scale feeders with single-or twophase laterals and split-phase LV systems. Similarly, the authors in [19] propose an optimal power flow formulation to estimate the HC with multitype distributed energy resources, only validated in small test systems.…”

mentioning

confidence: 99%

Hosting Capacity Estimation for Behind-the-Meter Distributed Generation

Pereira,

Parajeles,

Zúñiga

et al. 2024

IEEE Trans. Power Syst.

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Power utilities worldwide are facing a growing number of customers' requests to authorize the interconnection of behindthe-meter distributed generation. This paper presents a new practical methodology for power utilities to estimate the amount of small-scale distributed generation they can accommodate in the low-voltage level of distribution feeders without potential harm to the latter. It considers both medium-voltage and low-voltage levels limiting criteria to determine the locational hosting capacities.The proposed method uses detailed models of distribution feeders extracted from the geographical information system of power utilities and the location of existing customers. A new tool based on the proposed methodology is also described in the paper to show how the methodology can be easily integrated into existing planning tools of power utilities. It reports the circuits' total hosting capacity and provides hosting capacity maps with results per medium-voltage feeder section, distribution transformer, and low-voltage system. Results for real large-scale distribution feeder models demonstrate the practicality and potential of this methodology.

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Maximum Hosting Capacity Assessment of Distribution Systems With Multitype DERs Using Analytical OPF Method

Cited by 10 publications

References 25 publications

Recent developments of demand‐side management towards flexible DER‐rich power systems: A systematic review

Recent developments of demand‐side management towards flexible DER‐rich power systems: A systematic review

Developing an Integration of Smart-Inverter-Based Hosting-Capacity Enhancement in Dynamic Expansion Planning of PV-Penetrated LV Distribution Networks

Hosting Capacity Estimation for Behind-the-Meter Distributed Generation

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