Title: Long-term planning of high-renewable power systems
Abstract: Integrating renewable energy resources into power systems poses significant challenges for traditional long-term planning procedures. The intermittent nature of wind and solar power outputs requires the procurement of sufficient reserve to compensate for the system’s deficit or excess of power and ensure secure operation in different periods. This challenge is further compounded as the share of intermittent renewables increases, and fewer gas generators are built due to more stringent greenhouse gas emissions constraints, leading to increased reserve prices and reduced energy prices.
New technologies, such as demand response and small modular reactor units, and new procedures, such as using wind and solar in providing reserves, are being explored as potential reserve resources to address this challenge. Moreover, the required reserve is a function of invested intermittent resources. The output of wind, solar, and system load are the key factors in determining the necessary reserve in each period. The NOAA HRRR dataset provides weather data with a 15-minute resolution and is used to calculate the output of wind and solar generators.
These operational and planning decisions come together in capacity expansion planning (CEP) as an LP. However, operational constraints are not modeled with high fidelity within CEP due to computational restrictions. To improve the fidelity of CEP, a more detailed check on the operational constraints is performed externally, and the results are fed back into CEP. Using the results of the CEP, the corresponding reserve for wind and solar investments is calculated. If the required reserve differs from the CEP reserve requirement, the CEP is re-run. This iterative process is part of a high-fidelity planning platform under development at Iowa State University. The results of CEP determine the timing and technology of generation and transmission investments, and the platform aims to provide more accurate and efficient planning for renewable energy integration into power systems.
Bio: Ali Jahanbani Ardakani completed his Ph.D. in power systems at McGill University in 2015 and subsequently joined Iowa State University as a postdoctoral research assistant. He has consulted on offshore wind projects and is now a research assistant professor at Iowa State, where his work focuses on the long-term planning of power systems and the integration of offshore wind.
Join from a PC, Mac, iPad, iPhone or Android device:
Please click this URL to start or join. https://iastate.zoom.us/j/94087524568?pwd=WXc4eWtLaWJJKzNpcHZydlptOUZIZz09
Or, go to https://iastate.zoom.us/join and enter meeting ID: 940 8752 4568 and password: 324328
Join from dial-in phone line:
Dial: +1 312 626 6799 or +1 646 876 9923
Meeting ID: 940 8752 4568