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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Energy Res.</journal-id>
<journal-title>Frontiers in Energy Research</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Energy Res.</abbrev-journal-title>
<issn pub-type="epub">2296-598X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">885659</article-id>
<article-id pub-id-type="doi">10.3389/fenrg.2022.885659</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Energy Research</subject>
<subj-group>
<subject>Editorial</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Editorial: Advanced Technologies for Modeling, Optimization and Control of the Future Distribution Grid</article-title>
<alt-title alt-title-type="left-running-head">Dai et&#x20;al.</alt-title>
<alt-title alt-title-type="right-running-head">Editorial: Advanced Technologies for Distribution Grid</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Dai</surname>
<given-names>Ningyi</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1052970/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Ding</surname>
<given-names>Yi</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1165221/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Wang</surname>
<given-names>Jiawei</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1129172/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zhang</surname>
<given-names>Dongdong</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1155780/overview"/>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>State Key Laboratory of Internet of Things for Smart City</institution>, <institution>University of Macau</institution>, <addr-line>Macau</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>College of Electrical Engineering</institution>, <institution>Zhejiang University</institution>, <addr-line>Hangzhou</addr-line>, <country>China</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Department of Electrical Engineering</institution>, <institution>DTU</institution>, <institution>Technical University of Denmark</institution>, <addr-line>Lyngby</addr-line>, <country>Denmark</country>
</aff>
<aff id="aff4">
<sup>4</sup>
<institution>School of Electrical Engineering</institution>, <institution>Guangxi University</institution>, <addr-line>Nanning</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>
<bold>Edited and reviewed by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/558033/overview">ZhaoYang Dong</ext-link>, University of New South Wales, Australia</p>
</fn>
<corresp id="c001">&#x2a;Correspondence: Ningyi Dai, <email>nydai@um.edu.mo</email>
</corresp>
</author-notes>
<pub-date pub-type="epub">
<day>25</day>
<month>03</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="collection">
<year>2022</year>
</pub-date>
<volume>10</volume>
<elocation-id>885659</elocation-id>
<history>
<date date-type="received">
<day>28</day>
<month>02</month>
<year>2022</year>
</date>
<date date-type="accepted">
<day>09</day>
<month>03</month>
<year>2022</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2022 Dai, Ding, Wang and Zhang.</copyright-statement>
<copyright-year>2022</copyright-year>
<copyright-holder>Dai, Ding, Wang and Zhang</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these&#x20;terms.</p>
</license>
</permissions>
<related-article id="RA1" related-article-type="commentary-article" journal-id="Front. Energy Res." xlink:href="https://www.frontiersin.org/researchtopic/18273" ext-link-type="uri">Editorial on the Research Topic <article-title>Advanced Technologies for Modeling, Optimization and Control of the Future Distribution Grid</article-title>
</related-article>
<kwd-group>
<kwd>Distribution energy resource</kwd>
<kwd>distribution grid</kwd>
<kwd>integrated energy system</kwd>
<kwd>microgrid</kwd>
<kwd>resilience</kwd>
</kwd-group>
</article-meta>
</front>
<body>
<p>Future power grids face various challenges due to a rapidly increasing share of renewable energy resources and increasing interplay with other energy sectors. Distributed energy resources (DERs) such as wind, solar, energy storage, combined heat and power plants, electric vehicles, and smart loads become prevalent. As shown in <xref ref-type="fig" rid="F1">Figure&#x20;1</xref>, it has become an inevitable choice for the energy revolution to develop an integrated energy system that realizes the deep integration of new technologies with distributed energy and diversifies (cold, heat, electricity, gas, etc.) demand. Besides, we are moving towards an integrated energy system on an unprecedented scale. In the continuous development of integrated energy systems, the elements of participation and interaction are becoming more complex. The integration of variable sources and the efficient and synergistic utilization of these energies will be a key focus in the future development.</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption>
<p>Integrated energy system.</p>
</caption>
<graphic xlink:href="fenrg-10-885659-g001.tif"/>
</fig>
<p>This issue contains ten research articles focusing on modeling and analysis methods for IES, advanced technologies for DERs and microgrid, active distribution network, impact of DERs interconnection on the distribution network,&#x20;etc.</p>
<p>The paper by <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fenrg.2021.645017/full">Cao et&#x20;al.</ext-link> proposed the concept of shared ESS (Shared-ESS) for microgrid owner/operator and applied it to the economic optimal dispatch of a microgrid cluster. The microgrids can achieve the peer-to-peer (P2P) transaction among each other with the use of the Shared-ESS, which significantly improves the energy utilization efficiency. The numerical analysis shows that the Shared-ESS can significantly reduce the energy bills of microgrid owner/operator, shift the usage of energy during peak time, and facilitate the renewable energy consumption.</p>
<p>The orderly deregulation of planned electricity generation and consumption is an important measure for electricity market reform in several countries. Under the plan-market double-track mechanism (PMDM) implemented, a modified linear bidding function of generation companies was first proposed by <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fenrg.2021.679365/full">He et&#x20;al.</ext-link>, and the unified clearing price of unilateral generation market is determined accordingly. Simulations based on data from a provincial electricity market in China illustrate that the market power can be reduced through a reasonable proportion of planned electricity designed by the power exchange.</p>
<p>The paper by <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fenrg.2021.712397/full">Chen et&#x20;al.</ext-link> discusses a passive sliding mode control strategy of MMC-UPFC to achieve the advantages of both the passive controller and sliding mode controller. An unbalanced grid treatment strategy is also presented with the series side of MMC-UPFC. Negative sequence components of the grid voltages are detected by the cross-decoupling method with second order generalized integrator and then compensated by the series side of MMC-UPFC. The series side converter controls the power flow and treats unbalanced grid conditions simultaneously.</p>
<p>The article by <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fenrg.2021.713510/full">Hu et&#x20;al.</ext-link> is an assessment report meant to address the step-less, and low-cost reactive power to reduce the increasing risks of voltage violations in distribution networks (DNs). Firstly, reactive power compensation models of PVs and EV chargers are investigated and voltage deviation indexes of the regulation results are proposed. Moreover, kernel density estimation (KDE) and slice sampling are adopted to provide the PV output and EV charging demand samples. Then, the risk assessment is carried out with a voltage regulation model utilizing OLTCs, SCs, and available smart inverters.</p>
<p>One study, <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fenrg.2021.717089/full">Wang et&#x20;al.</ext-link> explored an optimal placement model of voltage sag monitor, which considers the sag economic loss weight, realizes the redundant coverage of important customers, and reduces the risk of sag loss of them. Compared with traditional methods, this method can reduce the risk of loss and ensure the economic benefits of important customers.</p>
<p>Frequency regulation is a critical issue in the islanded microgrids. <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fenrg.2021.717327/full">Zhong et&#x20;al.</ext-link> proposes an equivalent rotor speed compensation control scheme of PMSG for frequency support in the islanded microgrids. A new variable combining pitch angle and rotor speed is defined as the equivalent rotor speed. The inertia control scheme is optimized by adding a virtual compensation variable to the equivalent rotor speed to obtain the reference of the machine-side converter control&#x20;loop.</p>
<p>
<ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fenrg.2021.718151/full">Chen and Bai</ext-link> proposes a mixed-integer nonlinear programming (MINLP) model combining electrical, natural gas, and heating systems, as well as the coupling components, such as CHP and gas-fired generators. The second-order cone and linearized techniques are used to transform the non-convex fundamental matrix formulation of multi-energy network equations to a mixed-integer convex multi-energy flow model, which can improve the computational efficiency significantly.</p>
<p>One study <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fenrg.2021.718859/full">Liu et&#x20;al.</ext-link>, focused on a weak-consistency&#x2013;oriented collaborative strategy, which was proposed for the practical implementation of the large-scale distributed demand response. Using case studies with different information transmission error rates and other conditions, the proposed strategy is demonstrated to be an effective solution for the large-scale distributed demand response implementation, with a robust response capability under even remarkable transmission errors.</p>
<p>In another study <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fenrg.2021.718916/full">Liu et&#x20;al.</ext-link>, a non-intrusive load disaggregation approach based on an enhanced neural network learning algorithm was proposed. The presented appliance enhances the flexibility and adaptability for diverse scenarios, leading to the improvement of disaggregation performance.</p>
<p>To manage a large scale of distributed energy resources (DERs) dispersed geographically and reduce the impact of DER uncertainties, <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fenrg.2021.734801/full">Zheng et&#x20;al.</ext-link> propose a distributed two-stage economic dispatch for a virtual power plant (VPP) to track a specified VPP schedule curve. The two-stage distributed optimization problems are solved by an improved exact diffusion algorithm which is proved to be robust to local communication failure.</p>
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<title>Author Contributions</title>
<p>All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.</p>
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<sec sec-type="COI-statement" id="s2">
<title>Conflict of Interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="disclaimer" id="s3">
<title>Publisher&#x2019;s Note</title>
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