An electrifying find can help with stability in the electric grid

An electrifying find can help with stability in the electric grid
Researchers have established a technique that will help ensure a stable supply of electricity even as new renewable energy sources come on line. The trick is helping all of the subsystems to work in concert.
You definitely want to have a stable supply of electricity, because without it, all your gadgets could stop working, or even worse, if the variation in voltage and frequency is too large.
But delivering a stable supply of electricity is getting more and more difficult, especially as households begin to contribute with electricity from solar panels and small wind turbines.
Analyzing and controlling the electric power grid requires precise measurements that are presented correctly. A new method may help ensure this. Photo: Thinkstock
One of the most important aspects of ensuring the reliable operation in any electric grid is getting correct measurements and information from the system. Those measurements affect everything else.
In practice, an entirely stable frequency is nearly impossible. No system is perfect, and the frequency of the electricity supply is actually constantly changing.
The challenges posed by these variations have led researchers at the Norwegian University of Science and Technology (NTNU) to use a new method to analyse this phenomenon in electric power systems.
More precise descriptions
The NTNU researchers’ method can provide a more precise description of variations in the voltage frequency of the electric grid. These variations may oscillate around a mean value, but the lengths of their periods may differ. If these differences are not accounted for, they can, in the worst case, result in a system collapse.
Small systems like wind turbines or solar cells on roofs will become more and more common over time. But the electric grid needs to be able to handle the challenges these pose. Photo: Thinkstock
To analyse and manage a power grid, you have to have precise measurements and represent them correctly. Everything else is based on those measurements and their interpretation being accurate.
“The new analysis method for time-varying frequency has big advantages over methods used previously and may have significant impact,” said Olav B. Fosso, a professor in the Department of Electric Power Engineering.
Assumptions are inadequate
Today, the most widely used methods for analysing periodic variations in grid voltage measurements are based on the Fourier series. This approach relies on assumptions that are not always met in practice, but that have worked well enough with the structure of the electrical grid up to now.
However, the extensive use of power electronics with inverters that has blossomed in recent years due to the increased penetration of renewable energy sources poses challenges for both small and large electricity networks.
Some large wind farms, for example, have been shut down for long periods because the control and regulation subsystems haven’t worked together properly. But finding the reasons behind these kinds of problems has thus far been difficult.
The strength of the new analysis method is that it can more reliably identify different parts of the grid voltage frequency, so that they can be factored into the design of control systems.
Ensuring reliable operation of microgrids
Frequency time variations are more significant in determining the reliable operation of small systems, such as solar panels on your house or windmills that constitute a microgrid.
The new method is well-suited to the challenges posed by adding renewable energy sources to the existing electric power grid. Photo: Thinkstock
The power supply in many parts of the world operates at a frequency of 50 Hz, and is considered stable within a small range of variations. All electrical household appliances depend on the quality of the voltage supply, and on frequency variations being within the norms. If the quality isn’t good enough, the appliances either run less efficiently than they should, or simply stop working.
Small electrical systems such as rooftop solar panels and wind turbines are now a familiar sight. In the future, the norm may be that every household generates and uses its own power or contributes electricity to a larger network. Under this future scenario, it will be essential for each of these small players to deliver power that meets quality standards.
Collaboration with Norden Huang
The method was originally developed to analyse ocean waves, but has since become much more widely used, including in the measurement of brain signals. This is the first time HHT has been used to analyse the frequency variations of the voltage in electrical power systems.
The NTNU researchers are working with Professor Norden Huang at National Central University in Taiwan, for whom HHT was named.
Professor Huang has been responsible for the Data Analysis unit of NASA Goddard Institute for Space Studies and today collaborates with Harvard, Johns Hopkins, MIT and Oxford universities. He also works with researchers and students from NTNU, including Geir Kulia, a master’s student in the Department of Electronics and Telecommunications.
Data from Bhutan
Kulia is currently writing his master’s thesis, supervised by Lars Lundheim and Marta Molinas from the Department of Engineering Cybernetics. His thesis is part of an MSc programme called Knowledge for Humanitarian Purposes that is offered by NTNU.
Kulia adopted the HHT method to analyse data from a microgrid in Bhutan.
To do this, Kulia developed an algorithm based on Huang’s HHT method. He decided to do this because he hadn’t been able to identify the frequency-related variations in his voltage measurements when he used traditional approaches. His analysis made no sense.
“At least they made no sense to me,” Kulia said, an observation confirmed by Molinas.
But the Hilbert-Huang Transform provided a completely different picture.
Identifying errors rather than masking them
The method proved far more suited for identifying possible problems than existing approaches. Suddenly Kulia had some clues to go on.
“In this case, we suspect that the problem lies in the control unit itself,” says
The controller is the part of the generation system that coordinates the rest of the power system based on measurement data.
If the controller design does not respond properly to the measurements, it may try to compensate for frequency components that do not really exist, but that are a result of how the algorithm analyses the data.
Then the part of the network that is supposed to regulate variations actually introduces new oscillations or fluctuations in voltage and frequency. This is not something you want happening in your electrical system.
It can also have serious consequences for the industry. Manufacturers of control systems don’t want to hear that a control unit is creating additional problems.
Method is drawing attention
The new method is also able to detect other phenomena. The new HHT method appears to be far better suited for analysing phenomena related to frequency variations than many traditional methods. It effectively detects the frequency components of the measurement data, which is essential in designing control systems.
One article about the findings, with Kulia as first author, has already been published and another has been accepted for publication. One of the reviewers of the soon-to-be published paper noted that “as solid state control equipment continues to expand, traditional ‘fundamental frequency’ analysis is no longer sufficient, especially in microgrids.”
MORE NORWEGIAN SCITECH NEWS
Privacy Policy
The Privacy Statement is about how this website collects and uses visitor information. The statement contains information that you are entitled to when collecting information from our website, and general information about how we treat personal data.The legal owner of the website is the processing officer for the processing of personal data. It is voluntary for those who visit the web sites to provide personal information regarding services such as receiving newsletters and using the sharing and tip services. The treatment basis is the consent of the individual, unless otherwise specified.
1. Web analytics and cookies (cookies)
As an important part of the effort to create a user-friendly website, we look at the user pattern of those who visit the site. To analyze the information, we use the Google Analytics analysis tool.Google Analytics uses cookies (small text files that the site stores on the user's computer), which registers the users' IP address and provides information about the individual user's online movements. Examples of what the statistics give us answers to are; how many people visit different pages, how long the visit lasts, what websites users come from and what browsers are used. None of the cookies allow us to link information about your use of the site to you as an individual.The information collected by Google Analytics is stored on Google servers in the U.S.. The information received is subject to the Google Privacy Policy.An IP address is defined as a personal information because it can be traced back to a particular hardware and thus to an individual. We use Google Analytics's tracking code to anonymize the IP address before the information is stored and processed by Google. Thus, the stored IP address can not be used to identify the individual user.
2. Search
If the webpage has search function, it stores information about what keywords users use in Google Analytics. The purpose of the storage is to improve our information service. The search usage pattern is stored in aggregate form. Only the keyword is saved and they can not be linked to other information about the users, such as the IP addresses.
3. Share / Tips service
The "Share with others" feature can be used to forward links to the site by email, or to share the content of social networking. Tips for tips are not logged with us, but only used to add the tips to the community. However, we can not guarantee that the online community does not log this information. All such services should therefore be used wisely. If you use the email feature, we only use the provided email addresses to resend the message without any form of storage.
4. Newsletter
The website can send out newsletters by email if you have registered to receive this. In order for us to be able to send e-mail, you must register an e-mail address. Mailchimp is the data processor for the newsletter. The e-mail address is stored in a separate database, not shared with others and deleted when you unsubscribe. The e-mail address will also be deleted if we receive feedback that it is not active.
5. Registration, form
The website may have a form for registration, contact form or other form. These forms are available to the public to perform the tasks they are supposed to do.Registration form is for visitors to sign up or register.Contact form is for visitors to easily send a message to the website's contact person.We ask for the name of the sender and contact information for this. Personal information we receive is not used for purposes other than responding to the inquiry.The form is sent as email via Mailgun as a third party solution. The entire submission will be stored at Mailgun for 24 hours. Between 24 hours and 30 days, only mailheader is stored before the submission is deleted after 30 days. The reason for this storage is to confirm whether emails are sent from the website and forwarded to the correct recipient.Once the email is received by the recipient, it is up to the recipient to determine the data processing needs of the email.
6. Page and service functionality
Cookies are used in the operation and presentation of data from websites. Such cookies may contain language code information for languages ​​selected by the user. There may be cookies with information supporting the load balancing of the system, ensuring all users the best possible experience. For services that require login or search, cookies can be used to ensure that the service presents data to the right recipient.