California’s Invisible Solar Problem

Susan Kraemer, Correspondent July 01, 2013

smartgrid controlcenterWhat if grid operators were unable to track the energy generation from a 2.7-GW solar project – the equivalent of several nuclear plants? Imagine the difficulties they would face.

This scenario is unfolding now in California. However this invisible power is not from one solar project, it’s from the combined generation of a rapidly growing number of rooftop arrays that now amount to 2.7 GW.

In February, one count calculated around 130,000 solar systems generating power from "behind the meter" within the California ISO. By mid-June it was over 150,000.

These systems are mostly net metered, so utilities only recieve enough data to credit the owner the sum of their production/consumption on their bill.

But as these numbers grow, utilities and grid operators are increasingly concerned about the impacts on planning and operations.

“In order for utilities to accurately plan and forecast the impact of distributed PV on their distribution systems, they need production data,” said John ‘Skip’ Dise, product manager at Clean Power Research. Dise works with utilities, ISOs and the California Solar Initiative (CSI) to find a solution to the invisible solar generation on the grid.

However, most distributed PV systems don’t have a production meter, measuring all the power generated, only a net meter. Third party solar, like programs offered by SolarCity and Sunrun, generates production numbers, but it's not sent to the grid.

“Utilities like PG&E need to see all the power generated to plan distribution, identify which transformers and substations to upgrade, and what they need to allow for back flow when there is so much solar on the system that it’s actually more than the load on a given distribution feeder,” he says. 

CAISO Sees Only Big Power Stations

Currently, only utility-scale power stations generate this data, whether it's from solar, wind, geothermal, nuclear, natural gas or coal.

“Everything on the grid has telemetry, which says ‘I’m on and I’m producing this amount, and this is where I am,’” said Steven Greenlee, spokesman for the California Independent System Operator (CAISO). “It’s data exchange.”

The job of maintaining the grid is about balancing demand and supply. System operators need to know what the load will be to match generation to load. But CAISO can’t see distributed solar generation.

“We are not getting that,” Greenlee says. “That’s all behind the meter, so we can’t see it. And that means we have a harder time producing our load forecast. That is probably one of the major things that we are talking about at this time with utilities and the resource developers and regulators.”

Historically, only utility-scale renewable generation counted towards California’s RPS, so what initially seemed like just a sprinkling of rooftop solar arrays didn’t need to be included in generation data. But now it does.

California’s Solution

SolarAnywhere Data and Forecast has long been used by the industry to generate data using satellite on a 1-km grid in California (and 10 km nationally) with unique irradiance measurement in real time. Clean Power Research analytics incorporate current local temperatures, wind speeds, and passing clouds with hourly or half-hourly irradiance measures in real time.

Wind speed and temperature both affect cell temperature, which affects efficiency. Heat reduces efficiency, and cells themselves also generate heat, but on windy days the breeze pulls heat away, increasing efficiency.

It’s all live and responds to the changing weather. “We look at where clouds are currently for real time data, and project them forward; forecasting where they’re moving,” said Dise.

smartinverter-diagram2Making the Solar Fleet Visible

By adding analytics to the data streams from both offerings, Clean Power Research, partly funded by CSI, now can supply grid operators with a comprehensive view of all generation with FleetView — including the previously invisible behind-the-meter systems.

PowerClerk includes CSI data on the performance of any given array, at any orientation, using any make of panels and inverters, at any location. It is designed to reward effective solar designs and penalize poor ones. Regulators in more and more states require it to ensure that subsidies aren’t paid for poorly performing systems. 

With this, grid operators can determine what they need to do and what they don’t need to do, for example, putting off upgrading a particular substation or transformer if local peak load is now being supplied locally. 

“As you’re getting higher and higher penetrations in neighborhoods on specific feeders,” Dise explained, “utilities must make new decisions about how they’re building out their distribution system.”

Utilities already use sophisticated planning software, but “distributed solar has thrown a monkey wrench in that because all of their tools are built around modeling load, but not net load” he said. 

smartInverter1Another Approach

But energy modeling can only go so far. San Diego Gas & Electric (SDG&E), with the most solar rooftops in the nation, created its own solar forecasting. Their tools are a work in progress, beginning with smart metering, but have limits, according to SDG&E smart grid manager Josh Gerber.

“You can fine tune them, take data sets from smart meters and run them through algorithms and come up with predictive answers about the future, take actual results, compare them to predictions, and figure out ways to tweak the model for accuracy,”  Gerber pointed out. “But until we have a way to actually monitor performance, we’re still dealing with limited validation.”

Gerber believes that the solution is better data at the source: the inverter.

Smart inverters are controllable, can change the power factor, and input or receive reactive power to manage voltage, like capacitors that drive voltage up or down. They tell the grid what they are producing “in a much more real time basis, say a minute, or even faster.”

Germany’s Solution

Germany, like California, has seen rapid residential solar growth. But Germany is already switching its solar customers to smart inverters, so its rooftop solar production remains visible as it grows.

“If all my customers had a solar inverter that we were pulling data off of,” said Gerber, “it would be much easier for us to validate what we predicted against what actually happened." The data that SDG&E gets is “too late, and too granular.”

“It’s not the way that a utility or district operator would have the visibility into the real time or near real time performance of those systems,” he explained. “It’s a very coarse-grained view.”

smartinverter3Smart Inverters Make Solar Visible — and Valuable 

Germany is spending hundreds and hundreds of millions of euros to retrofit its several hundred thousand customers’ inverters to smart inverters.

smartinverter PetraSolar32These cost a bit more than regular inverters, adding an additional cost to a system. 

To offset this cost, Gerber suggests that California solar customers with smart inverters could receive a payment, like the German feed-in tariff, for their grid balancing service.

Currently, California solar customers are paid only for their kilowatt-hours of power. But with smart inverters providing a valuable voltage smoothing service, they could also be paid by the kilovar.

“In a future with services unbundled, they could get paid for services they provide to the grid: reactive power and voltage support,” suggested Gerber. “They would have a way to earn more than just the raw energy credit on their net metering bill.”

For a more comprehensive article on smart inverters click here.



Robert Grothe's Sidebar: A suggestion about smart inverters vs home/community energy storage devices. What if the utilities themselves offered a standardized smart programmable inverter as part of your solar grid tie-in to the netmeter. That way the utilities could be assured they would be getting consistant quality programmable data (like the Mar's rovers do from their engineers) from which to monitor the electrical generation of the solar array.  AND using the satellite weather feeds to do predictive analysis of energy flow. Of course a good energy storage device in every home would be a better more moderated approach with better results. The kind that can take the surplus solar energy generated during the day and feed it back into grid. (i.e. smart EV's come to mind. But then you have the problem of keeping the EV fully charged for the early morning commute.)

So a stand alone energy storage device in the home or located locally in community serving hundreds of households is still needed. (i.e. Grothe Power Towers' come to mind here.) Or move some or all of this somehow to the netmeter and let the customer decide which inverter to use. The netmeter would provide the voltage regulation and live smart data feeds and manage the energy storage needed. It's a complex issue that needs a good test bed of all these ideas to find the perfect balance.
Anyone got several million dollars in R&D lying around they want to use for testing these ideas let me know. I'm ready when you are? Contact me from the Power Tower website. Universities and research labs are welcome.



Wind and Solar Power Paired With Storage Could Power Grid 99.9 Percent of the Time

by University of Delaware Energy Research Team

Dec. 10, 2012
— Renewable energy could fully power a large electric grid 99.9 percent of the time by 2030 at costs comparable to today's electricity expenses, according to new research by the University of Delaware and Delaware Technical Community College.

A well-designed combination of wind power, solar power and storage in batteries and fuel cells would nearly always exceed electricity demands while keeping costs low, the scientists found.

"These results break the conventional wisdom that renewable energy is too unreliable and expensive," said co-author Willett Kempton, professor in the School of Marine Science and Policy in UD's College of Earth, Ocean, and Environment. "The key is to get the right combination of electricity sources and storage -- which we did by an exhaustive search -- and to calculate costs correctly."

The authors developed a computer model to consider 28 billion combinations of renewable energy sources and storage mechanisms, each tested over four years of historical hourly weather data and electricity demands. The model incorporated data from within a large regional grid called PJM Interconnection, which includes 13 states from New Jersey to Illinois and represents one-fifth of the United States' total electric grid.

Unlike other studies, the model focused on minimizing costs instead of the traditional approach of matching generation to electricity use. The researchers found that generating more electricity than needed during average hours -- in order to meet needs on high-demand but low-wind power hours -- would be cheaper than storing excess power for later high demand.

Storage is relatively costly because the storage medium, batteries or hydrogen tanks, must be larger for each additional hour stored.

One of several new findings is that a very large electric system can be run almost entirely on renewable energy.

"For example, using hydrogen for storage, we can run an electric system that today would meeting a need of 72 GW, 99.9 percent of the time, using 17 GW of solar, 68 GW of offshore wind, and 115 GW of inland wind," said co-author Cory Budischak, instructor in the Energy Management Department at Delaware Technical Community College and former UD student.

A GW ("gigawatt") is a measure of electricity generation capability. One GW is the capacity of 200 large wind turbines or of 250,000 rooftop solar systems. Renewable electricity generators must have higher GW capacity than traditional generators, since wind and solar do not generate at maximum all the time.

The study sheds light on what an electric system might look like with heavy reliance on renewable energy sources. Wind speeds and sun exposure vary with weather and seasons, requiring ways to improve reliability. In this study, reliability was achieved by: expanding the geographic area of renewable generation, using diverse sources, employing storage systems, and for the last few percent of the time, burning fossil fuels as a backup.

During the hours when there was not enough renewable electricity to meet power needs, the model drew from storage and, on the rare hours with neither renewable electricity or stored power, then fossil fuel. When there was more renewable energy generated than needed, the model would first fill storage, use the remaining to replace natural gas for heating homes and businesses and only after those, let the excess go to waste.

The study used estimates of technology costs in 2030 without government subsidies, comparing them to costs of fossil fuel generation in wide use today. The cost of fossil fuels includes both the fuel cost itself and the documented external costs such as human health effects caused by power plant air pollution. The projected capital costs for wind and solar in 2030 are about half of today's wind and solar costs, whereas maintenance costs are projected to be approximately the same.

"Aiming for 90 percent or more renewable energy in 2030, in order to achieve climate change targets of 80 to 90 percent reduction of the greenhouse gas carbon dioxide from the power sector, leads to economic savings," the authors observe.


Tasmanian Testbed for Large Integrated
   Renewable Energy Projects Ramps Up

By Oliver Wagg, Contributor November 9, 2012 
SYDNEY -- A small island lying in the Bass Strait between Australia's states of Victoria and Tasmania is set to become the testbed for one of the most sophisticated integrated renewable energy technologies in the world.