An Enterprise Control Assessment Method for Variable Energy Resource-Induced Power System Imbalances--Part II: Parametric Sensitivity Analysis
In recent years, renewable energy has developed to address energy security and climate change drivers. However, as energy resources, they possess a variable and uncertain nature that significantly complicates grid balancing operations. As a result, an extensive academic and industrial literature has...
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| Format: | Article |
| Language: | en_US |
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Institute of Electrical and Electronics Engineers (IEEE)
2015
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| Online Access: | http://hdl.handle.net/1721.1/97751 |
| _version_ | 1811085706173349888 |
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| author | Muzhikyan, Aramazd Farid, Amro M. Youcef-Toumi, Kamal |
| author2 | Massachusetts Institute of Technology. Department of Mechanical Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Mechanical Engineering Muzhikyan, Aramazd Farid, Amro M. Youcef-Toumi, Kamal |
| author_sort | Muzhikyan, Aramazd |
| collection | MIT |
| description | In recent years, renewable energy has developed to address energy security and climate change drivers. However, as energy resources, they possess a variable and uncertain nature that significantly complicates grid balancing operations. As a result, an extensive academic and industrial literature has developed to determine how much such variable energy resources (VERs) may be integrated and how to best mitigate their impacts. While certainly insightful with the context of their application, many integration studies have methodological limitations because they are case specific, address a single control function of the power grid balancing operations, and are often not validated by simulation. The prequel to this paper presented a holistic method for the assessment of power grid imbalances induced by VERs based upon the concept of enterprise control. This paper now systematically studies these power grid imbalances in terms of five independent variables: 1) day-ahead market time step; 2) real-time market time step; 3) VER normalized variability; 4) normalized day-ahead VER forecast error; and 5) normalized short-term VER forecast error. The systematic study elucidates the impacts of these variables and provides significant insights as to how planners should address these independent variables in the future. |
| first_indexed | 2024-09-23T13:14:17Z |
| format | Article |
| id | mit-1721.1/97751 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T13:14:17Z |
| publishDate | 2015 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| record_format | dspace |
| spelling | mit-1721.1/977512022-09-28T12:48:22Z An Enterprise Control Assessment Method for Variable Energy Resource-Induced Power System Imbalances--Part II: Parametric Sensitivity Analysis Muzhikyan, Aramazd Farid, Amro M. Youcef-Toumi, Kamal Massachusetts Institute of Technology. Department of Mechanical Engineering Youcef-Toumi, Kamal In recent years, renewable energy has developed to address energy security and climate change drivers. However, as energy resources, they possess a variable and uncertain nature that significantly complicates grid balancing operations. As a result, an extensive academic and industrial literature has developed to determine how much such variable energy resources (VERs) may be integrated and how to best mitigate their impacts. While certainly insightful with the context of their application, many integration studies have methodological limitations because they are case specific, address a single control function of the power grid balancing operations, and are often not validated by simulation. The prequel to this paper presented a holistic method for the assessment of power grid imbalances induced by VERs based upon the concept of enterprise control. This paper now systematically studies these power grid imbalances in terms of five independent variables: 1) day-ahead market time step; 2) real-time market time step; 3) VER normalized variability; 4) normalized day-ahead VER forecast error; and 5) normalized short-term VER forecast error. The systematic study elucidates the impacts of these variables and provides significant insights as to how planners should address these independent variables in the future. 2015-07-16T13:36:38Z 2015-07-16T13:36:38Z 2015-03 2014-11 Article http://purl.org/eprint/type/JournalArticle 0278-0046 1557-9948 http://hdl.handle.net/1721.1/97751 Muzhikyan, Aramazd, Amro M. Farid, and Kamal Youcef-Toumi. “An Enterprise Control Assessment Method for Variable Energy Resource-Induced Power System Imbalances--Part II: Parametric Sensitivity Analysis.” IEEE Trans. Ind. Electron. 62, no. 4 (April 2015): 2459–2467. en_US http://dx.doi.org/10.1109/TIE.2015.2395380 IEEE Transactions on Industrial Electronics Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Institute of Electrical and Electronics Engineers (IEEE) MIT web domain |
| spellingShingle | Muzhikyan, Aramazd Farid, Amro M. Youcef-Toumi, Kamal An Enterprise Control Assessment Method for Variable Energy Resource-Induced Power System Imbalances--Part II: Parametric Sensitivity Analysis |
| title | An Enterprise Control Assessment Method for Variable Energy Resource-Induced Power System Imbalances--Part II: Parametric Sensitivity Analysis |
| title_full | An Enterprise Control Assessment Method for Variable Energy Resource-Induced Power System Imbalances--Part II: Parametric Sensitivity Analysis |
| title_fullStr | An Enterprise Control Assessment Method for Variable Energy Resource-Induced Power System Imbalances--Part II: Parametric Sensitivity Analysis |
| title_full_unstemmed | An Enterprise Control Assessment Method for Variable Energy Resource-Induced Power System Imbalances--Part II: Parametric Sensitivity Analysis |
| title_short | An Enterprise Control Assessment Method for Variable Energy Resource-Induced Power System Imbalances--Part II: Parametric Sensitivity Analysis |
| title_sort | enterprise control assessment method for variable energy resource induced power system imbalances part ii parametric sensitivity analysis |
| url | http://hdl.handle.net/1721.1/97751 |
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