{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T16:45:27Z","timestamp":1777394727321,"version":"3.51.4"},"reference-count":26,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2026,4,20]],"date-time":"2026-04-20T00:00:00Z","timestamp":1776643200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004608","name":"Natural Science Foundation of Jiangsu Province","doi-asserted-by":"publisher","award":["BK20221165"],"award-info":[{"award-number":["BK20221165"]}],"id":[{"id":"10.13039\/501100004608","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>With the high penetration of distributed photovoltaics (PV) in distribution areas, transformer capacity limits and source\u2013load fluctuations have become key factors constraining PV accommodation. To accurately assess the PV hosting capacity under energy storage regulation, this paper proposes an assessment method based on operating region analysis. First, a coordinated operation model for the distribution area is established, incorporating the transformer capacity, energy storage constraints, and power balance. On this basis, the calculation boundaries for the PV hosting capacity are discussed in two scenarios: Model 1 ignores power curve uncertainty, characterizing the geometry of the conventional operating region to find the maximum deterministic hosting capacity (S1) that keeps the region non-empty. Model 2 introduces box-type uncertainty sets for the source and load, proposes the concept of a \u201cSelf-Balanced Operating Region\u201d, and constructs a robust feasibility determination model (f3) based on a Min\u2013Max\u2013Min structure. To solve this multi-layer nested non-convex model, an iterative algorithm based on duality theory and Benders decomposition is employed to determine the robust hosting capacity under uncertainty (S2) at the critical point where f3 shifts from zero to non-zero. Case studies show that source\u2013load uncertainty leads to a significant contraction of the operating region, and the robust hosting capacity under uncertainty requirements is strictly less than the deterministic hosting capacity (S1 &gt; S2). This method quantifies the reduction effect of uncertainty on the accommodation capability, providing a theoretical basis for planning high-renewable penetration distribution areas and energy storage configuration.<\/jats:p>","DOI":"10.3390\/a19040320","type":"journal-article","created":{"date-parts":[[2026,4,20]],"date-time":"2026-04-20T13:22:47Z","timestamp":1776691367000},"page":"320","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Assessment of Distributed PV Hosting Capacity in Distribution Areas Based on Operating Region Analysis"],"prefix":"10.3390","volume":"19","author":[{"given":"Xiaofeng","family":"Dong","sequence":"first","affiliation":[{"name":"Suzhou Power Supply Company, State Grid Jiangsu Electric Power Co., Ltd., Suzhou 215004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Can","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Electrical and Power Engineering, Hohai University, Nanjing 211100, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junting","family":"Li","sequence":"additional","affiliation":[{"name":"Suzhou Power Supply Company, State Grid Jiangsu Electric Power Co., Ltd., Suzhou 215004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiong","family":"Zhu","sequence":"additional","affiliation":[{"name":"Suzhou Power Supply Company, State Grid Jiangsu Electric Power Co., Ltd., Suzhou 215004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuying","family":"Wang","sequence":"additional","affiliation":[{"name":"Suzhou Power Supply Company, State Grid Jiangsu Electric Power Co., Ltd., Suzhou 215004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junpeng","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Electrical and Power Engineering, Hohai University, Nanjing 211100, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,4,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"111146","DOI":"10.1016\/j.ecolind.2023.111146","article-title":"Evaluating provincial carbon emission characteristics under China\u2019s carbon peaking and carbon neutrality goals","volume":"156","author":"Yang","year":"2023","journal-title":"Ecol. 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