High-Fidelity Solar Power Forecasting Systems for the 392 MW Ivanpah Solar Plant (CSP) and the 250 MW California Valley Solar Ranch (PV)

Ivanpah Solar Electric Generating System

Improving forecasting methods at the Ivanpah Solar Thermal plant

Project Overview

Recipient: The Regents of the University of California, San Diego

Program: EPIC

Award Amount: $999,898

Co-funded Amount: $764,019

Agreement Number: EPC-14-008

Project Term: 1/15/2015 - 3/15/2018

Project Status: Active

Recipient Location:  La Jolla, CA

Site Location(s):  Nipton, CA; Santa Margarita, CA

The Issue

Accurate forecasting tools for solar irradiance and solar power output have the potential to increase the reliability of California's energy supply, and the ability to optimize the dispatch of energy sources by reducing the uncertainty created by fast-changing weather conditions. High fidelity solar forecasting is an enabling technology for increasing solar penetration into the grid. However, there is a lack of well-developed forecasting models for components of solar irradiance that are critical to concentrating solar technologies, especially Direct Normal Irradiance (DNI) and Plane of Array (POA).

Project Innovation

This project will focus on the development and validation of tools capable of monitoring and forecasting DNI and POA irradiance and the power generation accurately, from 5 minutes out to 72 hours in the future, mainly at the Ivanpah Solar Thermal plant, but also at the California Valley Solar Ranch (CVSR) plant. The project will also include the development of tools for predicting wind speed, which affects the heliostats' deployment, and improve the power generation forecast via Resource-to-Power Model (RTP) for Ivanpah CSP and CVSR (Tracking PV) plants. The goal of this system is aimed at reducing uncertainties associated with operation, regulation and scheduling of Ivanpah. The new forecast models will be used as a feed forward input to the RTP model in the solar field controls system that will enable the solar field to preemptively position itself for weather transients.

Project Benefits

The project will develop and validate forecast models optimized for direct normal irradiance (DNI), plane of array (POA) irradiance for large-scale concentrating solar power (CSP), concentrating photovoltaics (PV), and tracking PV power plants. The application of big data and behavioral analysis will help optimize power plant operations.

Lower Costs: The project will deliver models that will help utility scale costs associated with day-ahead scheduling, reduce plant operation costs associated with intra-day variability, and reduce ancillary service purchases needed to avoid forced outages.

Greater Reliability: The project will result in greater reliability by developing high-fidelity models that increase the accuracy of solar energy forecasting to decrease the number of forced outages associated ancillary reserves.

Economic Development: The project will help economic development by reducing solar power plant operating cost by more than 10% and having the ability to substantially affect the effective solar capacity in California.

Environmental Benefits: The project will result in GHG emission reductions by decreasing the uncertainty associated with solar power generation to diminish the need of fossil fuel generation.

Public Health: The project will improve public health by increasing level of renewable energy utilization which results in reduction of air emission pollutants generated from fossil fuel generation.




Project Overview

Recipient: The Regents of the University of California, San Diego

Program: EPIC

Award Amount: $999,898

Co-funded Amount: $764,019

Agreement Number: EPC-14-008

Project Term: 1/15/2015 - 3/15/2018

Project Status: Active

Recipient Location:  La Jolla, CA

Site Location(s):  Nipton, CA; Santa Margarita, CA

Project Team

CEC Project Manager: Silvia Palma–Rojas

Recipient Contact: Carlos Coimbra

Match Partner(s): Itron, Inc. dba IBS; NRG Energy, Inc.


 

 

For questions or additional information, please email RandDProjectinfo@energy.ca.gov

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