The Value of Interval Meter Data in Solar Project Analysis
by Adam Gerza on Aug 01, 2015
Table of Contents
2. Who makes it available
3. Why is it better for analyzing solar PV projects
4. How to use and interpret raw data
5. About Energy Toolbase
Click to download PDF version
What is interval meter data?
“Interval data” or “meter data” is a series of measurements of energy consumption, taken at predefined intervals throughout the day. Typically interval meter data comes in increments of 60-minute, 30-minute or 15-minute granularity. The term “Interval data” is used interchangeably with “meter data”, “raw data”, “demand interval data” and also “Green Button Data”. They basically all mean the same thing, and are all captured by a digital or smart meter.
Units of measurement:
The main units of measurement of interval meter data are: kilowatt hours (kWh) or kilowatts (kW). kWh measures energy or consumption over a period of time. kW measures power or the amount of energy used at a given moment, which is commonly referred to as demand. You can derive one based on the other using the formula:
energy (kWh) = power (kW) x time (hr)
Example: if the time interval is 15 minutes, the unit of measurement is kW, the value is 20, then:
kWh = 20 x 0.25 or kWh = 5
Granularity of intervals:
Shorter intervals means more data points, and higher resolution data. Here’s the number of data points captured over 1-year, depending on the interval.
Green Button data (GBD) is basically interval meter data outputted into a standardized data format that can be easily accessed via the click of a “green button”. The Green Button standard was created with the support of the White House, the US Department of Energy (DOE), and the National Institute of Standards & Technology (NIST) to provide electricity customers with easy access to their energy usage data in a consumer-friendly format. When electric utilities use an interoperable data standard it eliminates the need for software applications to support a bunch of different data formats.
The two primary file types that Green Button data is downloaded into are: CSV (comma-separated value) and XML (extensible markup language). CSV formatted data is generally read in Excel. XML is a machine readable format, generally imported directly into a software application.
Who makes interval data available?
With the rapid growth of: smart meters, advanced metering infrastructure (AMI) and real-time communication networks, the number of electric utility customers who have access to interval meter data has grown dramatically. According to the Green Button Data website “more than 60 million households and businesses can use Green Button to access their energy usage data from their electric utility.”
For many large C&I (commercial & industrial) customers, this data has been captured and logged for decades. But now this data is becoming more accessible and ubiquitous, with the adoption of open data standards like Green Button.
3 ways to get interval data from the utility:
- Download via utility website
- Get written authorization from customer, then request it from a utility service rep
- Via a third party service like UtilityAPI
Download via utility website
Some utilities make raw interval data available for download directly through their customer web portal, which is effectively the Green Button option.
For instance, in California all three investor owned utilities: Pacific Gas & Electric, Southern California Edison and San Diego Gas & Electric – allow for direct download of Green Button data through their websites. The logos below are URL hyperlinks to step-by-step instructions for downloading GBD data:
Get authorization from customer
When the utility does not make GBD available for download via their website, it often times can be retrieved from a utility representative. This route does require the host customers’ consent. A number of utilities have template authorization forms to request billing and interval data file on behalf of a customer. Here’s a URL hyperlink to a generic ‘Authorization to Receive Customer Information’ form.
Utilities have different internal systems in place for processing these requests. In some cases they have the data AND make it available, in other cases they may have the data BUT choose not to make it available, while some utilities may not have access to the raw data themselves. For utilities that do not yet make Green Button data available for download via their website, it certainly can’t hurt trying this route.
Via a third party service
Different types of third party services exist to access and retrieve interval data. They can be classified into two general categories: services that get or fetch the data from the utility, or services that independently meter and log the interval data, independent of the utility.
UtilityAPI is a popular software service that facilities easy retrieval of interval data and utility billing data from utility websites. Using the service, a solar developer can send a link to the customer whose data they want to access. The customer would securely enter their utility login credentials and authorize that the data be sent directly to the requesting party. This streamlines the data fetch and retrieval process for both parties.
There are an increasing number of products and service providers capable of capturing interval consumption data, independent of the utility. While this route does require the installation of hardware, like data loggers and communication gateways, it offers advantages over utility interval data capture. One key advantage is the ability to capture the highest resolution data possible by determining the interval period. For example, the eGauge Systems device allows for one second data capture, which is 900 times higher resolution than 15-minute interval data. Another advantage is the ability to measure circuit level loads, or the consumption from a specific appliance like an HVAC unit.
Why is interval data better for analyzing solar projects?
Interval meter data is better because it’s higher resolution. It contains significantly more data points than the alternative, which is monthly summary data taken from utility bills. Having higher data fidelity allows for a more detailed level of analysis.
Advantages of working with interval data vs. monthly summary data when analyzing and proposing solar PV projects:
Find the best utility rate option: utilities are increasingly offering multiple rate schedule options to customers, many of which are time-of-use (TOU) based. Interval data makes it possible to precisely quantify the dollar savings of the proposed project on each available option.
Practical use case: we pulled interval data on a random sample of 30 existing residential solar system owners in California. We analyzed if these homeowners would save more money staying on the (default) tiered rate, or opting onto the (voluntary) time-of-use based rate.
- 70% were better off on the TOU rate schedule
- 5% were better off on the tiered/block rate schedule
- 25% no net dollar difference, because the homeowner had a ‘full-offset’ system
- on average, the TOU rate saved the customer an additional 36% annually
Simulate kW demand reductions from PV: interval data depicts the load profile of a customer, which illustrates when demand charges occur. Having the raw data file allows a developer to ethically estimate the reduction of demand charges in both kilowatts and dollars.
Practical use case: demand charges make up 45% of the utility bill for a manufacturing facility. The owner solicits two solar proposals. Using only monthly summary data, one proposal makes arbitrary assumptions for the reduction of demand charges, which the customer feels is naïve at best, and deceitful at worst. The winning developer requested the interval data file, and simulated the reduction of demand charges in a transparent fashion.
System Optimization: on time-of-use based rate schedules, interval data is a prerequisite to determine the optimal system size for dollar savings. The required inputs into the model are: interval meter data, the solar system design specifications, and any utility rate switching options.
Practical use case: a sophisticated solar developer knows that time-of-use energy credits cannot be carried forward at the end of a 12-month net metering cycle. Referencing their customers’ interval data file, the developer uses software to simulate different system sizes, ensuring they don’t leave money on the table by sizing a system that’s too big.
Future net metering frameworks: in a traditional net metering framework where kWh exports to the grid are compensated at the full retail rate, calculating the dollar savings of a solar project is easy. But in any framework (i.e. value of solar tariff) where exports are compensated at a value less than the fullretail rate, interval data is required to precisely determine the dollar savings of the project.
Practical use case: a homeowner in Hawaii is considering going solar. The project developer needs to design and optimize a solar system that minimizes exports to the grid, which are compensated at a wholesale rate. Interval meter data is necessary to evaluate the dollar savings and project economics.
Combining energy storage with solar PV: two of the most common value streams of customer-side-ofthe- meter energy storage projects are: peak demand shaving and time-of-use arbitrage. It’s impossible to model either of these scenarios and determine to what extent energy storage makes sense for a specific customer without raw meter data.
Practical use case: a commercial customer who already has solar wants to evaluate the payback economics of adding an energy storage system, and eliminating the peak demand charges that their solar system is not reducing.
Calculate realized dollar savings: to accurately quantify energy savings in dollars (i.e. the value of solar) for an operational solar system, interval data is required in tandem with solar production data.
Practical use case: a commercial customer entered into a PPA agreement four years ago. The customer definitively knows how much their system has been producing, and how much they are paying their PPA provider. But they have no clear idea of their actual realized dollar savings, because their rates have changed and their consumption patterns have changed.
How to use & interpret interval data?
The previous sections of this guide demonstrate that: (1) interval data is more ubiquitous and easy to access than ever, and (2) having the data provides a number of valuable benefits. The question then becomes,
Q: How do you use & interpret raw data to unlock the benefits?
A: (good) software
Whether it’s a homemade Excel spreadsheet or the most sophisticated software platform on the market, here’s the basic set of functions the software must perform:
The first step is importing the raw data into the software application and then normalizing that data into a standard format. Interval data comes in different file types, like CSV, XML or PDF. Within each type there are numerous ways the data can be structured. For example, in Excel the data could be arranged in a single-column or multi-column format. The software tool must be able to import different file types, and different file formats, as well as standardize different units of measurements and granularity of intervals.
Utility rate analysis:
The next step is to translate the raw meter reads into dollar values. Interval data files do not contain billing information and do not specify which utility rate schedule a particular meter is on. Therefore once the data has been imported the user must define the utility rate schedule, in order for the software to reconstruct the bill.
For straightforward utility rate schedules like a “flat rate” recreating the utility bill is easy. For more complicated schedules, like a “critical peak pricing rate, with time-of-use & demand charges” the bill reconciliation process becomes considerably more complex. Adding to the complexity is the fact that many rate schedules have sub-attributes, like the ‘baseline territory’ or ‘service voltage type’, which determine how the bill is calculated. To properly account for all the various rate schedules and subattributes, the software application will likely reference a utility rates database.
Model & Optimize:
It’s best to think about this step in terms of the inputs (going in) and outputs (coming out) of the software or model.
- Interval meter data: granularity of intervals, units of measurement
- General customer info: tax status, tax rates, utility escalation rate assumption, etc.
- Utility rates: sub-attributes, rate tariff effective date, eligible rate switch options
- Incentives: rebates, tax credits, depreciation, REC’s
- Solar system specs: costing, equipment (panels/inverters/racking), design specs (tilt angle, azimuth, shade), solar production calculator (PVsyst, PVSim, HelioScope, PV Watts, etc.)
- Financing: transaction type (cash purchase, loan, lease, PPA, etc.), terms of the transaction (interest rate, escalation rates, term, fees, etc.)
- Avoided cost: dollar savings from solar on eligible utility rate options
- Project economic metrics: pay-back period, return on investment (ROI), internal rate of return (IRR), net present value (NPV), lifetime cost of energy (LCOE)
Given that all of the inputs and assumptions going into the model will dictate the outputs coming out, it’s important for the software to be transparent. The less the software functions like a black box the better. In terms of optimization, capable software should be able to optimize for any output, based on the defined project inputs. For example, based on a customers’ unique usage profile, what solar system size and design specifications will result in the optimal 20-year internal rate of return.
To realize the full value of interval data, the analysis must be presented clearly to the customer. Fancy modeling and optimization are only worthwhile if the results can be effectively communicated. Often times the key takeaways that interval data illuminates will be abstract. For example, quantifying that it makes sense for a customer to opt onto a voluntary TOU rate schedule, or determining the maximum solar system size for a specific customer to ensure they don’t lose annual time-of-use energy credits. Great proposals will communicate complex items like these clearly to the customer.
About Energy Toolbase
Energy Toolbase is an industry-leading software platform for analyzing and proposing the economics of solar and energy storage projects. Our SaaS product is used by hundreds of the leading developers nationwide to accurately, objectively and transparently perform their utility rate analysis.
We think the future of solar project development will be all about interval data and combined technology systems. We designed and built the Energy Toolbase platform for that future, which in many ways is already here.
~john Gurski, Founder & CEO
Product features: working with interval data
- Data import – best-in-class importation of interval data from any file format.
- Utility rates engine – precise energy savings calculations in dollars. Our in-house utility rate database spans over 30 states and 130 utility territories.
- System optimization – determine the optimal sized system for dollar savings. Our simulation engine references: interval data, solar design specs, and utility rate switch options.
- Simulate demand reductions from PV – transparently quantify the reduction of demand charges in kilowatts and dollars.
- Energy Storage – objectively analyze the economics of energy storage projects with or without PV.
Professional proposals – present analysis in a clear and logical fashion that speaks directly to your customer. Customizable, interactive and visually stunning.
Sign up for a free trial at www.energytoolbase.com