Design of a Fuzzy Logic Controller for Short-Term Load Forecasting With Randomly Varying Load
Short-term load forecasting (STLF) is an integral component of energy management systems. In this paper, fuzzy logic-based algorithm is used for short-term load forecasting. The load changes over time and the goal is to satisfy the shift in demand and to maintain a fault as low as possible between t...
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| Veröffentlicht in: | International journal of sociotechnology and knowledge development 2021-10, Vol.13 (4), p.32-49 |
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| container_title | International journal of sociotechnology and knowledge development |
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| creator | Ananth, D V. N Kumar, Lagudu Venkata Suresh Gorripotu, Tulasichandra Sekhar Azar, Ahmad Taher |
| description | Short-term load forecasting (STLF) is an integral component of energy management systems. In this paper, fuzzy logic-based algorithm is used for short-term load forecasting. The load changes over time and the goal is to satisfy the shift in demand and to maintain a fault as low as possible between the reference and real powers. The error in the load demand in mega-watt (MW) is compared with proposed technique as well as conventional methods. Three cases were investigated in which the load changes were 1) more random in nature, but the variance to the reference was more; 2) the random load changes were simpler, but a little different from the reference; and lastly, 3) the load changing was random, and the reference deviation was maximum. The results are analyzed for different load changes, and the corresponding results are verified using MATLAB. The deviation of the error value in load response is less experienced with a fuzzy logic controller than with a traditional system, and in fewer iterations, the objective function is also achieved. |
| doi_str_mv | 10.4018/IJSKD.2021100103 |
| format | Article |
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N ; Kumar, Lagudu Venkata Suresh ; Gorripotu, Tulasichandra Sekhar ; Azar, Ahmad Taher</creator><creatorcontrib>Ananth, D V. N ; Kumar, Lagudu Venkata Suresh ; Gorripotu, Tulasichandra Sekhar ; Azar, Ahmad Taher</creatorcontrib><description>Short-term load forecasting (STLF) is an integral component of energy management systems. In this paper, fuzzy logic-based algorithm is used for short-term load forecasting. The load changes over time and the goal is to satisfy the shift in demand and to maintain a fault as low as possible between the reference and real powers. The error in the load demand in mega-watt (MW) is compared with proposed technique as well as conventional methods. Three cases were investigated in which the load changes were 1) more random in nature, but the variance to the reference was more; 2) the random load changes were simpler, but a little different from the reference; and lastly, 3) the load changing was random, and the reference deviation was maximum. 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Three cases were investigated in which the load changes were 1) more random in nature, but the variance to the reference was more; 2) the random load changes were simpler, but a little different from the reference; and lastly, 3) the load changing was random, and the reference deviation was maximum. The results are analyzed for different load changes, and the corresponding results are verified using MATLAB. 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N</au><au>Kumar, Lagudu Venkata Suresh</au><au>Gorripotu, Tulasichandra Sekhar</au><au>Azar, Ahmad Taher</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Design of a Fuzzy Logic Controller for Short-Term Load Forecasting With Randomly Varying Load</atitle><jtitle>International journal of sociotechnology and knowledge development</jtitle><date>2021-10-01</date><risdate>2021</risdate><volume>13</volume><issue>4</issue><spage>32</spage><epage>49</epage><pages>32-49</pages><issn>1941-6253</issn><eissn>1941-6261</eissn><abstract>Short-term load forecasting (STLF) is an integral component of energy management systems. In this paper, fuzzy logic-based algorithm is used for short-term load forecasting. The load changes over time and the goal is to satisfy the shift in demand and to maintain a fault as low as possible between the reference and real powers. The error in the load demand in mega-watt (MW) is compared with proposed technique as well as conventional methods. Three cases were investigated in which the load changes were 1) more random in nature, but the variance to the reference was more; 2) the random load changes were simpler, but a little different from the reference; and lastly, 3) the load changing was random, and the reference deviation was maximum. The results are analyzed for different load changes, and the corresponding results are verified using MATLAB. 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| subjects | Algorithms Controllers Deviation Electrical loads Energy management systems Forecasting Fuzzy control Fuzzy logic Random loads |
| title | Design of a Fuzzy Logic Controller for Short-Term Load Forecasting With Randomly Varying Load |
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