Shat Pratoomratana, Pacific Northwest National Laboratory: Hello! My name is Shat Pratoomratana. I’m a researcher at Pacific Northwest National Laboratory and today I’m going to be talking about some of the work we’ve been doing looking at the reaction of connected lighting systems to OpenADR signals.
In recent years, the growth in the penetration of renewable energy and distributed energy resources has caused the power grid to shift from a centralized system to a more distributed and “smart” system. This has the potential to and has been shown to cause operational, reliability, and resiliency issues on the power grid. One approach that has been used to mitigate these issues is by utilizing the available load flexibility in demand side resources to provide grid services.
Generally, the load flexibility available in lighting systems hasn’t been used for this purpose, even though lighting makes up a sizeable portion of the load in both residential and commercial buildings. With the recent advent of lighting systems that contain intelligence, sensors and the ability to exchange data over modern network interfaces to make them so-called connected lighting systems, lighting now has the ability to communicate with and respond to the power grid and its needs.
In this work an analysis of signals available in a grid communication protocol known as OpenADR is done in order to determine which signals are suitable for use by the connected lighting system, and which configuration parameters are necessary in order to allow the connected lighting system to appropriately respond to each of these signals. In order to facilitate the analysis a load profile for a lighting system needs to be created. And fortunately for us, the Department of Energy keeps a library of prototype buildings with nominal lighting load profiles already defined.
The nominal load profile that was used from this library was an average weekday lighting load profile for a medium office building. The minimum and maximum load profiles were determined by us by considering daylight availability and recommended lighting practices and codes. Using these minimum, nominal, and maximum lighting load profiles helps to define the available flexibility at any given point in the day as well as allowing for observations of how an incoming signal can cause the lighting load to deviate from nominal. If you’d like to know more about the DOE prototype buildings a link is provided at the bottom of the screen.
OpenADR contains ten signals that can generally be grouped as level signals, price signals, energy storage signals, and setpoint signals. Using commercial software certified by the OpenADR Alliance, we can create and send OpenADR signals. Once sent, the signals are received by the OpenADR endpoint and processed using custom developed Python code. The code extracts information from the OpenADR signal such as signal name, payload, duration, etc., and uses that information to create a simulated response based on lighting configuration parameters and the lighting load profiles.
To visualize the lighting system response, figures like the one shown here were created. The top subplot shows the lighting load profiles seen previously with the addition of the purple line and purple area to show the incoming OpenADR signal payload and duration respectively. The dashed yellow line shows the simulated system response. The bottom subplot shows what we are calling a “demand curve,” which is the relationship between an input signal and the lighting output. The figure currently being shown is the response to a simple level signal. The simple signal is a level signal and discrete values of 0, 1, 2, and 3, can be sent using this signal, where each level represents a particular amount of load shed. A percent reduction in load was mapped to each simple level, and given that reduction amount, a curve can be determined that predicts the reaction of the system to any simple level at any point in the day.
Price signals they are used to expose flexible loads to the wholesale price of electricity and other electricity pricing factors. Like with any commodity, the price of electricity can be the limiting factor in deciding how much to purchase and use. This idea encourages the use of electricity when it is cheap and can cause the consumers of electricity to shift their energy usage. Since pricing is a more suggestive signal the system operator or facility manager need to decide what the system output should be given a certain price, and this can be achieved by constructing a custom price vs. power demand curve. And like the simple signal, price signals need to be mapped to lighting load values, except in this case pricing signals must be mapped to a continuous space rather than discrete levels.
Demand curves can take many different shapes which can achieve different objectives such as keeping cost constant or limiting lighting load increases. The full study explores multiple demand curve shapes and their impact on system response.
Finally, setpoint signals are used to directly set the absolute or relative power output of the system. In practice setpoint signals are simple to react to: the signal explicitly tells the system what the load should be, and the system changes its load to that value. But given that the lighting system has limits on its flexibility it is entirely possible that a setpoint value could potentially put the system outside of its flexibility range. To prevent this, the system would opt-in and change the load to the requested setpoint value only if the request was within the flexibility range, otherwise, the system would opt-out and continue normal operation. In doing this analysis, configuration parameters that were deemed necessary to allow the connected lighting system to respond to each signal type, was determined as such: For the simple signal, the connected lighting system should include a configuration parameter that allows for the mapping of each level to a particular amount of load shed. For price signals the connected lighting system should include a configuration parameter that allows for the ability to define or upload a price vs. power demand curve that specifies the lighting load given a certain price.
For setpoint signals the connected lighting system should include the ability to configure the logic that determines if it is appropriate to participate in the event and react to the signal. Using these results there is ongoing work to develop a test method for use in a laboratory environment, that will characterize the ability of connected lighting systems to utilize their flexibility by responding to grid signals. It is the hope that this work will encourage more consideration for the use of connected lighting systems as flexible resources by providing general education of these concepts and by also providing examples of possible reactions by a connected lighting system to several different types of grid communication signals available today.
If you have any questions, and I hope you do, please don’t hesitate to contact either me or my colleague Michael Poplawski directly via email. Thanks so much for listening and have a great rest of your day!