Our client is currently managing over 50 solar farms and is required to submit real-time outages/derates to the ISO. Frequent wind turbine solar outages or derate events must be reported manually to the ISO system as they occur. In addition, forecasted limits must also be sent every 5 minutes.
The sheer work and volume of data review/ tickets required for the outage management process posed significant operational challenges.
- The process consumed a considerable number of resource hours every day.
- The PI/SCADA data was difficult for human consumption/decision-making. The data wasn’t easy to understand since it was at an inverter/turbine level and needed to be reviewed/processed against other data to ensure if there was an outage or derate that needed to be reported
- Due to the inability for users to manually create 100% accurate tickets, the process posed financial and operational risks because tickets were missed or incorrect.
The Solution: Automation and Machine Learning
Agile Analytics offered the perfect solution for this problem. The automation module connects to all of the underlying systems (PI/SCADA and internal systems) with a few clicks to obtain selected data. This data can then be used to automate the creation of outages as well as the creation of forecasted limits. This data is then sent to our Outage Management system, PowerManager. The automation worked as follows:
- Outage Data was sent to the ISO but users had a small time delay where they can review, update, or cancel the outage before it is sent to the ISO.
- In addition, the system also accurately forecasted limits by using current generation, current derates/outages, and forecasted weather information.
- Simplified a complex process and reduced operational and financial risk.
- Saved the users a significant amount of time daily (about 60-75%)
- Reduced existing errors by almost 99%
- Provided the client with significant financial savings.
The most important thing is that the entire solution was tested within days and implemented within WEEKS using Aigle Analytics automation and machine learning.
Steps to implementing the Solution within DAYS
You can utilize the Agile Analytics integrated PI module and multiple pipeline jobs to solve this issue, culminating in a full-fledged solution deployed in a few days. Here is a table that provides a snapshot of the steps:
|1||Identifying Required PI tags/ SCADA Point|
|2||Create an automation job and select the tags and data points|
|4||Schedule the Job (in our case, we will have it run every 5-minutes)|
|5||Automate ticket reporting, This will require writing the logic to use the data and allowing machine learning to create the tickets. The tickets are then sent to the underlying system (PowerManager) for the next steps. The limits are also sent to PowerManager, where it automatically sends them to the ISO.|
The following table gives a detailed account of the jobs executed within the pipeline:
|Params job||Runs every 5 minutes to check the breaker status|
|SQL Select Job||Pulls the appropriate PI tags for each unit from a database|
|Push to PI job||Pushes the tags and retrieves the status of each tag|
|SQL Select and Script Job||Checks if the previous value of the tag status has changed|
|Save and Push Job||Saves the tickets and pushes them to ISO|
With the increasing number of solar farms and the pressing need to report wind and solar outage/derate events promptly and accurately to ISO systems, automation becomes a necessity. Agile Analytics integrated PI/SCADA automation module provides an efficient solution, drastically reducing the amount of manual labor involved. By simply following the steps outlined above, clients can easily leverage this tool to streamline their solar, renewables, or fossil outage management process. Additionally, the entire Agile Analytics solution is a framework that can also be used to automate and solve other operational challenges.
- What is the PowerAnalytics integrated PI module?
The Agile Analytics integrated PI module is a tool that allows for seamless data management and automation of ticket reporting processes to ISO. It can connect to any PI/SCADA system.
- How does this solution reduce manual labor?
The solution reduces manual labor by automating the process of determining whether a true forced derate or outage took place and then automating the creation of the outage or derate for submission to the ISO/RTO (system utilizes specific ISO rules). The system process can be used to automate tickets for GADS (the system will utilize NERC rules). In addition, the system also automated Limits submission and automatically creates forecasted limits using current generation, forecasted weather, and machine learning.
- What is the frequency of the Params job check?
The Params job runs every minute to check the status and determine if an outage or derate has started or ended.
- How long does it take to implement this solution?
The entire solution can be built within a few days and implemented within one to two weeks, making it a rapid yet efficient solution for managing solar farms.
- How does this solution ensure the reporting of tickets is accurate?
The solution cross-checks the previous value of the tag status and determines if it has changed. If there is a state change, it either creates a new ticket or ends a previous one, ensuring accurate reporting. The system automatically starts and ends tickets. Additionally, forecasted limits also utilize current generation, weather forecasts, as well as a predictive machine learning algorithm to accurately calculate forecasted limits.