{"title":"Two-stage robust voltage/var control strategy of active distribution networks with hybrid distribution transformers","authors":"Yanting Xue , Yibin Liu , Qidong Wen , Yuanhang Zhang , Mingyang Mei , Lianchao Yu , Lishi Zhang , Deliang Liang","doi":"10.1016/j.ijepes.2025.111077","DOIUrl":null,"url":null,"abstract":"<div><div>This paper addresses the challenge of integrating Hybrid Distribution Transformers (HDTs) into the unbalanced Active Distribution Networks (ADNs). A two-stage robust VVC strategy is proposed to coordinate the operation of HDTs with a full spectrum of existing grid assets, including legacy devices such as on-load tap changers (OLTCs) and capacitor banks (CBs), and other flexible resources like Energy Storage Systems (ESS) and Demand Response (DR). The first stage determines a robust day-ahead schedule for slow-acting resources (OLTCs, CBs, ESS, DR), while the second stage performs real-time adjustments of HDTs to counteract uncertainties from PV generation and load demand. An accurate HDT power injection model, based on the auxiliary branch method, is developed to ensure modeling fidelity by incorporating internal impedance and series converter dynamics. The framework is built upon the coupled-phase second-order cone programming branch flow model (CP-SOCP-BFM) to accurately manage the network’s three-phase unbalance. To solve the resulting large-scale, non-convex problem, a computationally efficient solution framework combining the Inexact Column-and-Constraint Generation (i-CCG) algorithm and the Alternating Optimization Procedure (AOP) is proposed, which guarantees robust global optimality. The effectiveness of the proposed strategy is validated on a modified IEEE 33-bus system. Comprehensive comparative studies demonstrate its superiority over deterministic, heuristic-based, and standard robust optimization methods in terms of both robustness and computational efficiency.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"172 ","pages":"Article 111077"},"PeriodicalIF":5.0000,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Electrical Power & Energy Systems","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0142061525006258","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
This paper addresses the challenge of integrating Hybrid Distribution Transformers (HDTs) into the unbalanced Active Distribution Networks (ADNs). A two-stage robust VVC strategy is proposed to coordinate the operation of HDTs with a full spectrum of existing grid assets, including legacy devices such as on-load tap changers (OLTCs) and capacitor banks (CBs), and other flexible resources like Energy Storage Systems (ESS) and Demand Response (DR). The first stage determines a robust day-ahead schedule for slow-acting resources (OLTCs, CBs, ESS, DR), while the second stage performs real-time adjustments of HDTs to counteract uncertainties from PV generation and load demand. An accurate HDT power injection model, based on the auxiliary branch method, is developed to ensure modeling fidelity by incorporating internal impedance and series converter dynamics. The framework is built upon the coupled-phase second-order cone programming branch flow model (CP-SOCP-BFM) to accurately manage the network’s three-phase unbalance. To solve the resulting large-scale, non-convex problem, a computationally efficient solution framework combining the Inexact Column-and-Constraint Generation (i-CCG) algorithm and the Alternating Optimization Procedure (AOP) is proposed, which guarantees robust global optimality. The effectiveness of the proposed strategy is validated on a modified IEEE 33-bus system. Comprehensive comparative studies demonstrate its superiority over deterministic, heuristic-based, and standard robust optimization methods in terms of both robustness and computational efficiency.
期刊介绍:
The journal covers theoretical developments in electrical power and energy systems and their applications. The coverage embraces: generation and network planning; reliability; long and short term operation; expert systems; neural networks; object oriented systems; system control centres; database and information systems; stock and parameter estimation; system security and adequacy; network theory, modelling and computation; small and large system dynamics; dynamic model identification; on-line control including load and switching control; protection; distribution systems; energy economics; impact of non-conventional systems; and man-machine interfaces.
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