Power Transformer is an important and vital equipment for Power Supply System in a transmission grid. It’s back -down leads to commercial losses and inconvenience to the public.
• Today, we have a vast transmission network with lakhs of power transformer in the grid. The Power transformer fleet is maintained by each state utility in its domain. The failure rate of transformer has been a matter of concern and it is attributable mainly to the maintenance of the transformer.
• There are good practices of maintenance- both preventive and predictive.
Predictive maintenance has gone far ahead in terms of knowledge and technology today in the area of power transformer and we have condition monitoring equipment, both off-line and on-line.
• It is proved over a period of time that these condition monitoring predictive maintenance has saved million of Rupees for utility and successfully provided uninterrupted power supply.
• Inspite of having advance off-line and on-line condition monitoring, it is quite challenging for utility to precisely look at each and every transformer. In a way, it is manual assessment. Utility is like to miss the right time intervention to take corrective action based on condition monitoring data recorded in the off-line and on-line monitoring equipment.
With above background, following software is required:-
Like a health check in human being on regular basis, one can know the health parameters and recommend the required medicine and remedial actions to overcome the development and worsening of health. The similar concept is proposed for power transformer fleet. The recorded off-line and on-line condition monitoring parameters will be the base to work-out the health index of each transformer. It will be done by assigning a grade depending on the impact of each condition monitoring parameters. The final health index value of each transformer has to be worked out based on all conditions monitoring attributes. We need to develop a software which will have transformer fleet data base and give a health index of each transformer based on off-line and on-line condition monitoring attributes fed to the software on regular basis.
Benefits: 1) Utility will be able to predict the pre-matured failure of transformer and take corrective action
2) Plan predictive maintenance investment based on health index of each transformer.
3) In totality, it will ensure uninterrupted power supply and save millions of Rupees against replacement of failed transformers.
Traditional (conventional) sources of power generation are Thermal (Coal), Hydro, Gas and Nuclear, but they are depleting and causing carbon emission. Many countries are taking harsh decision to close down thermal and nuclear. An alternative source, catching the attention of everyone is renewable energy from Solar and wind, which require no fuel and abundantly available according to geographical location.
However, it has its own characteristic and throw upon challenges to integrate into transmission and distribution grid.
1. Solar Energy is available only during daytime and quantum of power varies according to time in bell shape form. This bell shape will change according to season.
2. Solar Energy is variable in the cloudy weather conditions.
1. Though available throughout the year. Wind potential varies location to location (that’s why installed in specific areas mostly in remote locations) and season to season.
2. Wind is variable, intermittent and unpredictable during 24 hrs. of the day.
Location wise wind potential makes the task of transmission and distribution utility/grid operation more difficult in absence of local consumption as well as adequate network.
Wind Energy is at peak during monsoon. This is the season when power demand is low. Grid operation has a challenge of handling the excess renewal energy. Grid operation is planned day ahead by taking supply (generator) and demand (utility) commitment. Grid operator is bound to control supply-demand balance to maintain frequency, but it becomes challenging when wind energy is accounted as part of supply in the day ahead planning due to variable and intermittent nature of wind. Grid operator is compelled to back-down conventional sources of generation to minimum level (inefficient operation) for load balancing.
With above background of renewable energy generation, there is need of software solution/modes in the hands of grid operator to predict solar and wind energy generation day ahead as well as during grid operation on hourly basis to guide them for load management.
Benefits: Right solar and wind energy prediction model will enable grid operator to plan dispatches and manage load balancing and efficient operation of power plant.
Problem Statement Type
20th November , 2018
20th November , 2018
Software - Mobile App development
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