India's electricity demand estimation using Genetic Algorithm

Saravanan, S.; Karman, Steve L.; Amosedinakaran, S.; Thangaraj, C.

doi:10.1109/iccpct.2014.7054814

Cited by 9 publications

(2 citation statements)

References 16 publications

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“…Similarly, an economic indicator-based work is presented by (Saravanan et al, 2012) where 11 variables per capita GDP, CO2 emission, population, national income, etc. are analyzed to forecast the electricity demand, as it is important in planning.…”

Section: Literature Reviewmentioning

confidence: 99%

Machine Learning-Based Electricity Load Forecast for the Agriculture Sector

Sharma

Mittal

Mishra³

et al. 2022

International Journal of Software Innovation

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A large section of the population has a source of income from the agriculture sector, but their share in the Indian GDP is low. Thus, there is a need to forecast energy to improve and increase productivity. The main sources of energy in agriculture are electricity, coal, and diesel. Among them, electricity plays an important role in land irrigation. Power forecasting is also essential for demand response management. Thus, any process that dissolves future consumption is favorable. This article presents a time series-based technique for forecasting medium-term load in agriculture. The aim is to find the peak periods of power consumption by months and seasons using statistical and machine learning-based techniques. The result shows that SARIMA has lower RMSE and exponential smoothing has lower RMSPE error than random forest and LSTM, which makes the statistical approach more efficient than intelligent approach for historical datasets. The season-wise peak demand occurs during the Rabi season. Finally, five-year ahead load in the agriculture sector was determined using the best models.

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Section: Literature Reviewmentioning

confidence: 99%

Machine Learning-Based Electricity Load Forecast for the Agriculture Sector

Sharma

Mittal

Mishra³

et al. 2022

International Journal of Software Innovation

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“…This problem is affecting nations with huge population and scare resources like India, which is growing in industrialization rapidly in recent years (Indian Electrical Equipment Industry Mission Plan, 2012-2022). Due to diversified loads, our conventional power system is unable to maintain constant voltage profile at the consumer end (Hingorani and Gyugyi, 2001;Wang et al, 2011;Lee et al, 2013;Saravanan et al, 2014). As a result of these constant voltage fluctuations which occur during peak load periods are the outcomes of uneven distribution of single-phase loads, an impedance of transmission lines and the loading types (Sensarma et al, 2001).…”

Section: Introductionmentioning

confidence: 99%

Power quality optimization through D-STATCOM in Aizawl, Mizoram, India

Lalhungliana¹,

Singh²,

Pareek³

2018

Proceedings of the Mizoram Science Congress 2018 (MSC 2018) - Perspective and Trends in the Development of Science Education An

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The power quality concerns are augmenting day by day due to the growth of loading requirements. In this paper, we address these concerns while trying to provide the solutions. With the advancement of technology, the power quality concerns can be handled efficiently by flexible alternating current transmission system (FACTS) devices such as distribution static shunt synchronous compensator (D-STATCOM), static volt-ampere reactive compensator (SVC), static synchronous series compensator (SSSC), thyristor-controlled series compensator (TCSC), unified power flow controller (UPFC), etc. This paper presents the solutions for power quality issues related to Mizoram with the help of D-STATCOM. D-STATCOM enhances the power quality by varying the various parameters of the system and make the system more flexible. We propose a MATLAB Simulink model of D-STATCOM which demonstrates the control of active and reactive power and hence maintains the voltage profile. In Mizoram, during peak hours Undervoltage is a frequent phenomenon which causes damage to various domestic appliances as well as it significantly affects the electrical equipment of small industries. By incorporating D-STATCOM in the existing system at the distribution level we can greatly improve the voltage profile of distribution system, which not only provide better power quality but also increase the lifespan of domestic as well as small industrial equipment, by this proposed modification in existing system the revenue of distribution, as well as customer satisfaction, can be improved.

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Fuel Consumption Estimation for Climbing Phase

Chen

Zhang

2018

Time Series Analysis and Forecasting

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India's electricity demand estimation using Genetic Algorithm

Cited by 9 publications

References 16 publications

Machine Learning-Based Electricity Load Forecast for the Agriculture Sector

Machine Learning-Based Electricity Load Forecast for the Agriculture Sector

Power quality optimization through D-STATCOM in Aizawl, Mizoram, India

Fuel Consumption Estimation for Climbing Phase

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