Managing Complexity: 5 benefits of high-frequency data for solar + storage projects

North America is swiftly becoming the global hotspot for hybrid solar + storage systems. Nowadays it is rare to see a new solar PV design proposal in the United States that does not incorporate a co-located storage system.

The practical and financial benefits of these systems are increasingly well understood. Integrating battery storage helps PV operators to smooth plant output and support grid stability. It also opens an array of potential new revenue streams from emerging flexibility and grid balancing services.

But managing solar + storage systems is highly complex. Storing and dispatching power at the optimal time requires an extremely granular understanding of how much power a project is generating both now and in the immediate future.

Developers, operators, and owners increasingly require high-frequency (1-minute) weather and solar irradiance data that enables them to make quick, accurate and financially effective decisions. In this blog, we outline the 5 benefits of high-frequency data for the budding solar + storage market in the US. 

AES Lawai Solar Project. Photo by Dennis Schroeder / NREL 58009 

Why is high-frequency (1-minute) irradiance data so important?

In the solar sector, the frequency in which irradiance data is collected and observed can range between 60-minute intervals, all the way down to 1-minute intervals. If data is collected at 1-minute intervals, it’s being collected at an extremely granular scale, or higher-frequency. Infrequent observations, or low-frequency data, can lead to an imperfect understanding of solar irradiance behaviour.

Today, the industry continues to rely on low-frequency (60-minute) time series data during the pre-planning stage of projects, all the way through to the operational phase. As new solar + storage projects are trending towards a two-to-four-hour window, in which power is generated, stored, and dispatched, relying on 60-minute time series data causes blind spots that limit the operator’s ability to maximise revenue streams and support the grid.

More granular, high-frequency data is needed to fill these blind spots, mitigate technical and financial risks, and support the day-to-day operation of hybrid projects.

Solargis’ approach to 1-minute data

Solargis has developed a new approach to 1-minute data in collaboration with the University of Malaga. Solargis uses an extensive, multiyear worldwide database of 1-minute observations, from which the five most similar sites are used to represent the radiative conditions of a particular project site.

Additionally, Transition Probability Matrices are generated for the location of interest for four different sky classes, and several thousands of iterations are done for each cloud index value. The 1-minute times series data is generated in line with the company’s satellite-based model.

When Solargis’ 1-minute data is used with the company’s historical forecasting data, it unlocks significant financial benefits for project developers, owners and operators, enables them to make better design and dispatch decisions and more safely operate the Battery Energy Storage System (BESS). Below we outline the 5 key benefits of using Solargis’ 1-minute data and forecasting products.

5 benefits of using 1-minute data

Understanding variabilities of regional PV assets

Historical 1-minute data enables operators and utilities to understand solar resource variability in a much more granular way. In particular, 1-minute data allows operators to better understand cloud edge effects, which are a common phenomenon in PV power generation caused by the sudden increase in irradiance due to the reflections of passing clouds. This helps with the identification of nodal/sub-station level variabilities for different seasons and preparing for variable conditions.

Also, accurate or realistic sub-hourly level PV energy production forecast values are essential for grid stability and operations. With Solargis’ forecast data, project operators can make better dispatch decisions and therefore support utilities in balancing supply with demand.

Accurate clipped energy estimation

Access to high frequency data also helps developers estimate “clipping losses” more accurately, which is the lost energy caused in a solar system due to the inverter derating its output to meet either its maximum power rating, or the maximum allowable power for the grid connection.

In most cases, and depending on the region, PV plants typically underestimate clipped losses when using hourly data, which is becoming more common with larger DC to AC ratios.

Optimising battery size

Many projects are trending towards two-to-four-hour battery systems in which power is stored and dispatched. Most of the projects either engage in peak shaving, energy arbitrage or ramp support and/or other grid support services. Therefore, accurate battery design (MWh) is essential to minimize the energy yield variability of a project, as well as to optimise the type of solar + storage application.

With Solargis’ 1-minute historical data and historical forecast data, developers can design optimum-sized batteries and enhance other supplementary power electronic equipment. Therefore, 1-minute data is essential to informing the size of a battery chosen for a particular application during the project design phase, and accurately budgeting for the upfront costs of a project.

Reduction in penalties and maximising revenues

If a solar asset produces more energy than the forecasted values (day ahead and intraday), it must be curtailed to ensure grid stability. This means controlling the inverters to reduce the maximum power output, which could lead to technical strains on the system and lost energy. Contrasting this, if an asset under-delivers, the grid operator may fine the asset operator for not fulfilling their contracted production.

Solargis’ forecasting service unlocks a much more granular view of when to store and dispatch power, giving operators an enhanced ability to control the variability of power generation.

Likewise, for ramp control application, it is very important to study and model battery operations. 1-minute historical data and historical forecast data ensures that research and modelling is done in the most accurate way. Through greater control, 1-minute data reduces the number of penalties that an operator receives for not properly servicing the grid within the required ramp limitations.

Effective wholesale energy trading

For operators participating in the wholesale energy trading market, accurate forecasting, along with the market price signal data, unlocks the ability to pinpoint the most financially efficient period to charge and dispatch power from a solar + storage system. These financial studies can be modelled even before the construction of a solar + storage plant. Using historical satellite actual productions and historical market price data, battery dispatch models can be run with several contingency combinations.

With this knowledge, operators can make accurate dispatch and charging decisions that maximise their revenues when selling power to the wholesale electricity market.

To find out how Solargis can help with 1-minute data, attend our upcoming webinar on December 7th 2022. Register here to attend.

To find out more about Solargis’ 1-minute data methodology, click here.