What’s the best way to avoid performance issues – and associated expenses – during a microgrid system installation? Uncover and correct them ahead of time. A North American oil refinery microgrid did just that by investing in thorough Real Time Digital Simulator (RTDS) testing of its power management system.
The oil refinery had installed new substations and upgraded equipment to improve its on-site power system reliability; however, new load added to the system caused a generation deficit when in island mode from the local utility. To preserve critical loads (and shed non-critical ones), the project team implemented a power management system.
Hundreds of tests were performed to validate system operation for designed transitions and anticipated failure modes, uncovering potential issues that were corrected before installation.
Vendor support, peer reviews, and additional regression testing all become more feasible and effective, giving the engineer and the plant owners and operators greater confidence in the installed system
This white paper details six lessons learned from these tests.
Lesson 1: Accurately characterize the system. To prove that a power management system could detect contingencies and shed load quickly enough to preserve stable operation, we first developed a software electrical model of the system in a popular phasor-domain power system modeling package. It identified that the refinery generators would become unstable, or trip offline for self-preservation, after as little as 30 cycles from certain initiating events. Without these dynamic model validation tests at the beginning of the project, system definition would have needed to depend on typical values for similarly sized machines, reducing confidence in both the performance definition and RTDS testing results. Read more.
- Lesson 2: Thoroughly test system operating modes. Considering the high number of combinations for possible operating scenarios – simple loss of grid connection; single-breaker failures; near-remote utility loads briefly served by plant generation; single-unit outages, etc. – detailed models and analyses help to identify worst-case contingencies and performance requirements. Read more.
- Lesson 3: Include at least one of each device type in the test. Through our testing, we learned that the vendor had implemented different update rates in IEC 61850 GOOSE-message look-up tables in different device types. This undocumented artifact produced unnecessary tripping operations in some instances, as well as significantly delayed tripping action in others. We were able to design a work-around, perform our usual quality assurance review of the design, and functionally test the correction in the RTDS lab. It is possible that this problem might not have been discovered due to limitations of tests performed only in the field if RTDS-based FAT was not performed. Read more.
- Lesson 4: Test system failure modes. Verify secure operation under a wide variety of failure and equipment-outage scenarios. A few simple design changes can prevent misoperation.
- Lesson 5: Identify FAT and commissioning test boundaries. Limited overlap of testing is preferred over leaving areas untested. Keeping commissioning tests succinct limited expensive field time by our testing team and reduced the impact the commissioning could have on the length of the scheduled plant outage. These save costs all-around while still delivering a thoroughly tested system. Read more.
- Lesson 6: Carefully preserve system test details. Although there may be gigabytes of data, preserving system test details allows the test environment to be re-created for a small fraction of the original investment if a system revision or plant addition is necessary. Read more.
The value of the refinery process made it worthwhile to invest in RTDS testing and to confirm that this oil refinery microgrid could continue stable operation when an islanding contingency occurs.
Download the whitepaper to read more on discovered issues, solutions and lessons learned.