BIG DATA ANALYTICS TOOL TO ASSESS THE DYNAMIC SECURITY OF INERTIAL AND FREQUENCY RESPONSE IN THE CHILEAN POWER SYSTEM - (:unkn) unknown (My University, 2026)
Given current decarbonization goals of most countries, future power system will be mainly composed by non-dispatchable, power electronics-interphased generators. Also, the smart grid modernization will allow demand response to fully integrate to power system operation. As it can be seen, future power systems operating points will be less predictable, and dynamic security assessments will no longer be adequate to prevent insecure conditions. If dynamic security is not properly maintained, the probability of widespread blackouts will increase, which represent a large cost to society. The Chilean National electric system serves the 96% of the population of Chile accounting for about 18 million people. In terms of costs, the value of lost load in Chile is about 1300 $US/MWh for blackouts between 10-20% loss. The average power demand in the Chilean Power system is about 10,000 MW, so a 10% blackout has a cost of US$1,300,000/hour. This shows the significant size of the problem in the national context. In such a scenario, software tools to forecast insecure dynamic conditions have captured particular attention. Power systems are very complex, but complexity can be addressed by data analytics intelligence to reduce the computational burden and provide solutions with simpler frameworks to facilitate industrial implementations. This suggests that data analytics applications to dynamic security assessments are a significant opportunity to address the future needs of increasing system unpredictability. Also, the availability of large amounts of data from SCADA and PMU systems is also suggesting that data analytics applications will play a central role in dynamic security assessments. Most of those proposals are based in complex dynamic systems, with a limited number of simpler approaches with the potential of actual industrial testing in power system control rooms. This project proposes the development and Implementation a big data analytics tool to assess the dynamic security of frequency stability by forecasting System Inertia, the Frequency Nadir and the Frequency ROCOF of the Chilean power system. The proposal is based in a previous result implemented in industrial hardware and software, which makes the proposal feasible to be implemented in a real control room environment. With the implementation of the project, the Chilean National Electric Coordinator will count with a software tool to forecast inertia, Nadir and ROCOF and identify short term insecure scenarios and follow the trend of other system operators facing significant integrations of solar and wind. The development of the project will not only contribute to improve the analysis capability of the Chilean National Electric Coordinator, but also will provide analytical capabilities beyond the state of the art in terms of actual implementations in power system control rooms. This will position the Chilean National Electric Coordinator as a leading entity in facing the dynamic security issues under the penetration of solar and wind power.
Keywords: BIG DATA ANALYTICS; INERTIAL RESPONSE; POWER SYSTEM DYNAMICS