Dealing with the stochastic prosumager problem with controllable loads
This paper focuses on the home energy management for a residential prosumager with flexible loads. In particular, three different types of controllable appliances (shiftable, interruptible, thermostatically controllable) have been considered, each one with a specific representation of energy consump...
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| Veröffentlicht in: | Soft computing (Berlin, Germany) Germany), 2023-09, Vol.27 (18), p.12913-12924 |
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| creator | Violi, Antonio Beraldi, Patrizia Carrozzino, Gianluca |
| description | This paper focuses on the home energy management for a residential prosumager with flexible loads. In particular, three different types of controllable appliances (shiftable, interruptible, thermostatically controllable) have been considered, each one with a specific representation of energy consumption profile and a potential discomfort rate for the user. The inherent uncertainty affecting the main model parameters (i.e., non- controllable loads, solar production, external temperature) is explicitly accounted for by adopting the two-stage stochastic programming modeling paradigm. The model solution provides the prosumager with the optimal scheduling of the controllable loads and the operation of the storage system that guarantee the minimum expected energy procurement cost, taking into account the overall discomfort. A preliminary computational experience has shown the effectiveness of the proposed approach in terms of cost savings and the advantage related to the use of a stochastic programming approach over a deterministic formulation. |
| doi_str_mv | 10.1007/s00500-022-06809-2 |
| format | Article |
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In particular, three different types of controllable appliances (shiftable, interruptible, thermostatically controllable) have been considered, each one with a specific representation of energy consumption profile and a potential discomfort rate for the user. The inherent uncertainty affecting the main model parameters (i.e., non- controllable loads, solar production, external temperature) is explicitly accounted for by adopting the two-stage stochastic programming modeling paradigm. The model solution provides the prosumager with the optimal scheduling of the controllable loads and the operation of the storage system that guarantee the minimum expected energy procurement cost, taking into account the overall discomfort. A preliminary computational experience has shown the effectiveness of the proposed approach in terms of cost savings and the advantage related to the use of a stochastic programming approach over a deterministic formulation.</description><subject>Alternative energy sources</subject><subject>Appliances</subject><subject>Artificial Intelligence</subject><subject>Computational Intelligence</subject><subject>Control</subject><subject>Control algorithms</subject><subject>Controllability</subject><subject>Discomfort</subject><subject>Electric rates</subject><subject>Electric vehicles</subject><subject>Electrical loads</subject><subject>Electricity</subject><subject>Electricity distribution</subject><subject>Energy consumption</subject><subject>Energy industry</subject><subject>Energy management</subject><subject>Energy resources</subject><subject>Energy storage</subject><subject>Engineering</subject><subject>Focus</subject><subject>Households</subject><subject>Mathematical Logic and Foundations</subject><subject>Mechatronics</subject><subject>Residential energy</subject><subject>Robotics</subject><subject>Scheduling</subject><subject>Stochastic programming</subject><issn>1432-7643</issn><issn>1433-7479</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9UEFOwzAQtBBIlMIHOEXibFivHTs9okILUiUucLY2jtOmSpMSu0L8HrdB4sZpR6uZ2Z1h7FbAvQAwDwEgB-CAyEEXMON4xiZCScmNMrPzE0ZutJKX7CqELQAKk8sJWzx5aptunX01cZPFjc9C7N2GQmxcth_6cNjR2g9HWLZ-N9Jc38Whb1tKq6ztqQrX7KKmNvib3zllH4vn9_kLX70tX-ePK-6klpGTFuR8rTFXTiiQpUJNzhUGyIOAoiSQRU7aK1lLiYrKskJX5UVd6dKgklN2N_qmfz4PPkS77Q9Dl05anIkC0AijEwtHlksBwuBrux-aHQ3fVoA99mXHvmzqy576sphEchSFRO5S5j_rf1Q_mLpt6w</recordid><startdate>20230901</startdate><enddate>20230901</enddate><creator>Violi, Antonio</creator><creator>Beraldi, Patrizia</creator><creator>Carrozzino, Gianluca</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>C6C</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><orcidid>https://orcid.org/0000-0002-1672-4033</orcidid></search><sort><creationdate>20230901</creationdate><title>Dealing with the stochastic prosumager problem with controllable loads</title><author>Violi, Antonio ; Beraldi, Patrizia ; Carrozzino, Gianluca</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c363t-a61acef6254c1403b426acc870ae0108ba0385a6e43f3324abbd2cd58fd6b7243</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Alternative energy sources</topic><topic>Appliances</topic><topic>Artificial Intelligence</topic><topic>Computational Intelligence</topic><topic>Control</topic><topic>Control algorithms</topic><topic>Controllability</topic><topic>Discomfort</topic><topic>Electric rates</topic><topic>Electric vehicles</topic><topic>Electrical loads</topic><topic>Electricity</topic><topic>Electricity distribution</topic><topic>Energy consumption</topic><topic>Energy industry</topic><topic>Energy management</topic><topic>Energy resources</topic><topic>Energy storage</topic><topic>Engineering</topic><topic>Focus</topic><topic>Households</topic><topic>Mathematical Logic and Foundations</topic><topic>Mechatronics</topic><topic>Residential energy</topic><topic>Robotics</topic><topic>Scheduling</topic><topic>Stochastic programming</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Violi, Antonio</creatorcontrib><creatorcontrib>Beraldi, Patrizia</creatorcontrib><creatorcontrib>Carrozzino, Gianluca</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><jtitle>Soft computing (Berlin, Germany)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Violi, Antonio</au><au>Beraldi, Patrizia</au><au>Carrozzino, Gianluca</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Dealing with the stochastic prosumager problem with controllable loads</atitle><jtitle>Soft computing (Berlin, Germany)</jtitle><stitle>Soft Comput</stitle><date>2023-09-01</date><risdate>2023</risdate><volume>27</volume><issue>18</issue><spage>12913</spage><epage>12924</epage><pages>12913-12924</pages><issn>1432-7643</issn><eissn>1433-7479</eissn><abstract>This paper focuses on the home energy management for a residential prosumager with flexible loads. 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| subjects | Alternative energy sources Appliances Artificial Intelligence Computational Intelligence Control Control algorithms Controllability Discomfort Electric rates Electric vehicles Electrical loads Electricity Electricity distribution Energy consumption Energy industry Energy management Energy resources Energy storage Engineering Focus Households Mathematical Logic and Foundations Mechatronics Residential energy Robotics Scheduling Stochastic programming |
| title | Dealing with the stochastic prosumager problem with controllable loads |
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