{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T18:36:02Z","timestamp":1773513362736,"version":"3.50.1"},"reference-count":29,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2017,10,1]],"date-time":"2017-10-01T00:00:00Z","timestamp":1506816000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Energies"],"abstract":"<jats:p>To address the static voltage stability issue and suppress the voltage fluctuation caused by the increasing integration of wind farms and solar photovoltaic (PV) power plants, a two-tier reactive power and voltage control strategy based on ARMA power forecasting models for wind and solar plants is proposed in this paper. Firstly, ARMA models are established to forecast the output of wind farms and solar PV plants. Secondly, the discrete equipment is pre-regulated based on the single-step prediction information from ARMA forecasting models according to the optimization result. Thirdly, a multi-objective optimization model is presented and solved by particle swarm optimization (PSO) according to the measured data and the proposed static voltage stability index. Finally, the IEEE14 bus system including a wind farm and solar PV plant is utilized to test the effectiveness of the proposed strategy. The results show that the proposed strategy can suppress voltage fluctuation and improve the static voltage stability under the condition of high penetration of renewables including wind and solar power.<\/jats:p>","DOI":"10.3390\/en10101518","type":"journal-article","created":{"date-parts":[[2017,10,2]],"date-time":"2017-10-02T13:10:05Z","timestamp":1506949805000},"page":"1518","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Two-Tier Reactive Power and Voltage Control Strategy Based on ARMA Renewable Power Forecasting Models"],"prefix":"10.3390","volume":"10","author":[{"given":"Jinling","family":"Lu","sequence":"first","affiliation":[{"name":"State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Baoding 071003, China"}]},{"given":"Bo","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Operation and Control of Renewable Energy &amp; Storage Systems, China Electric Power Research Institute, Beijing 100192, China"}]},{"given":"Hui","family":"Ren","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Baoding 071003, China"}]},{"given":"Daqian","family":"Zhao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Baoding 071003, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7332-9726","authenticated-orcid":false,"given":"Fei","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Baoding 071003, China"},{"name":"Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1691-5355","authenticated-orcid":false,"given":"Miadreza","family":"Shafie-khah","sequence":"additional","affiliation":[{"name":"C-MAST, University of Beira Interior, 6201-001 Covilh\u00e3, Portugal"}]},{"given":"Jo\u00e3o","family":"Catal\u00e3o","sequence":"additional","affiliation":[{"name":"C-MAST, University of Beira Interior, 6201-001 Covilh\u00e3, Portugal"},{"name":"INESC TEC and the Faculty of Engineering of the University of Porto, 4200-465 Porto, Portugal"},{"name":"INESC-ID, Instituto Superior T\u00e9cnico, University of Lisbon, 1049-001 Lisbon, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2017,10,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3114","DOI":"10.1109\/TSG.2015.2406879","article-title":"Realistic and transparent optimum scheduling strategy for hybrid power system","volume":"6","author":"Reddy","year":"2015","journal-title":"IEEE Trans. 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