Navigant Research Blog

Where Are All the Meter Manufacturers in Transactive Energy Projects?

— December 7, 2017

That’s a question I’ve been asking myself recently. The answer seems to be “nowhere.” In the 110 or so trials of utility industry-related blockchain and transactive energy (TE) Navigant Research has identified, meter vendors are at best the silent, invisible partners of other companies. When asking leading blockchain and TE startups about the meter hardware in their trials, the stock response has been “nothing is available that supports our requirements, so we built our own.” So, why aren’t meter vendors making more noise about a potentially significant growth opportunity?

Blockchain is the hottest, most hyped technology in the energy industry, and TE is its hottest use case. If current TE trials prove successful, I expect rapid adoption, particularly in countries with high penetration of solar, supported by ratepayer-funded incentive mechanisms. TE’s market-based incentives could replace subsidies. Large-scale, fully automated TE platforms have a number of requirements, as discussed in Navigant Research’s Blockchain for Transactive Energy Platforms report:

  • TE pricing requires visibility into local network conditions, including network assets and distributed energy resources.
  • Smart contracts—which determine when transactions are opened and closed—must be hosted locally and fed with market data.
  • Meters measure and record all TE power supplied and consumed.
  • Communication networks will transport data to interested parties.
  • Transactions must be recorded to the blockchain.
  • Significant distributed compute power will support automation of the TE platform.

Meter Vendors Can Support Many TE Functional Requirements

TE markets will have to be settled in much the same way as wholesale power markets are today, in accordance with strict market regulations and technology standards. This is a complex system, where a lot of trust will be placed on the technology platform. Meter vendors have many capabilities that could put them in a commanding position to lead the TE space:

  • Smart meters already provide visibility at the point of consumption.
  • Advanced metering infrastructure communications could provide the data networks on which TE runs.
  • Smart meter data concentrators could be used as nodes for the blockchain, store smart contracts, provide compute power for localized pricing calculations, and so on.

There is another feature that meter vendors have so far overlooked: it is difficult to amend records already committed to the blockchain. Consequently, it is vital to ensure that transaction data is correct before it is recorded. This will be a difficult task in a largely automated TE platform. While smart meter accuracy is generally high—between 99.5% and 99.9%—a validation algorithm is run regularly to estimate missing or erroneous meter readings. In TE, a similar algorithm must run on transaction data. However, it is likely that validation will be distributed alongside the ledger, rather than a centralized batch process. Most meter vendors also offer a meter data management system with an associated validation algorithm.

Despite meter vendors’ requisite hardware and software, they are nowhere to be seen in the TE world. There are many reasons: ongoing major smart meter rollouts command a lot of attention, and there is little money to be made in TE right now. However, I would have expected at least one vendor to have taken the leap into the world of TE. The biggest risk is that meter vendors are trapped in the old utility world, where metering innovation was driven by utilities—with whom meter vendors have decades-old relationships—and adoption of new metering technologies was slow and incremental.

TE adoption will be different. It is driven by startups that have no previous relationship with meter vendors. These startups could develop their own validation algorithms; they could choose to use public 5G networks for data communications; or they may decide to deploy their own distributed compute. If this happens, meter vendors will miss out on potentially billions of dollars of value created by TE. Meter vendors must wake up to the reality of TE and the opportunities and threats the market presents.

 

China Cements Its Role as the Undisputed AMI Leader

— November 30, 2017

In terms of volume, China continues to preserve its status as the undisputed global leader in advanced metering infrastructure (AMI). Since 2012, State Grid Corporation of China (SGCC) has been deploying smart meters to each of its customers at a feverish clip. SGCC has installed more than 400 million smart meters across China over the past 5 years as part of this unprecedented project.

While utilities in countries like Italy and Sweden have succeeded in converting all their electromechanical meters to smart devices, the scale and execution of China’s nationwide project are truly unmatched. It is worth noting some of the unique characteristics of SGCC’s project and what’s in store for the future of the overall Chinese smart meter market.

How Is This Possible?

When looking at the Chinese market for smart meters, it becomes clear that all meters are not created equal. More often than not, smart meters deployed across China lack the full capabilities of a basic smart meter common in Europe or North America, such as hourly interval measurements or reasonably symmetric two-way communications. Yet, the Chinese meters still provide significant capabilities beyond traditional automated meter reading systems, including very low speed or potential short-range communications.

These limited capabilities are one of the primary drivers behind the radically different price points of Chinese smart meters, which are typically around 50% less than typical US or European prices. In addition, the monopolistic nature of Chinese utilities leads to high volume purchase orders from domestic suppliers, further reducing average meter costs.

What Is Happening on the Ground?

Over the course of 2016, SGCC deployed 70 million new smart meters, with the installed base reaching approximately 400 million devices. SGCC expects full deployment by the end of 2017.

China Southern Power Grid, the country’s other state-owned electric utility, was primarily involved in pilot-scale projects prior to March 2016, at which point the utility began its large-scale commercial deployment. China Southern expects full deployment by 2020, which should account for more than 80 million meters.

Improving Technology Shows Promise for the Market

While initial indications would suggest a significant market downturn in 2017 and 2020 given the rollout conclusions, the emerging second-generation smart meter market should help placate any potential concerns. According to China’s national regulations, meters must be replaced every 5 to 8 years. With the lifespan of SGCC’s deployed meters running between 1 and 5 years, the mega-utility will now begin looking into second-generation upgrade meters, which often carry a higher cost along with increased capabilities.

This emerging second-generation market is expected to help sustain the strong revenue and growth profiles that have characterized the Chinese market for years. As other major markets like Brazil, Egypt, India, and Turkey begin their forays into large-scale smart meter projects, lessons can be learned from the impressive scale and execution of China’s rollouts.

 

AMI Data Brings New Possibilities for Energy Efficiency Measurement and Verification: Part 2

— August 4, 2017

Coauthored by Emily Cross and Peter Steele-Mosey

Part 1 of this blog series covered operational improvements and provided background on the role of advanced metering infrastructure (AMI) data in energy efficiency program evaluation, measurement, and verification (EM&V). This blog continues the discussion with a focus on program impact evaluation. Navigant Research examines these topics in detail in its report, Utility Strategies for Smart Meter Innovation: Energy Efficiency Measurement and Verification.

Program Impact Evaluation

The use of AMI data for program evaluation has the potential to substantially reduce evaluation costs. A major cost associated with the evaluation of large customer (commercial and industrial) energy efficiency program evaluation is onsite verification and metering. For some programs, it is possible to reduce the number of site visits required or reduce the frequency of site visits. Another opportunity for faster program evaluation using AMI data is large-scale validation of coincident demand savings for energy efficiency programs. With AMI data, it is a straightforward matter to isolate demand impacts occurring during utility system peak performance hours.

Programs operating in utility services areas with full penetration of smart meters, deploying energy efficiency measures with consistent load reduction patterns, are excellent candidates for evaluation using hourly or subhourly AMI data. Energy efficiency impact analysis using utility data assumes enough of the program participant savings are above a minimum measurable threshold. That is, the signal-to-noise, savings-to-baseline ratio must be high enough to see the savings in the meter data for a substantial number of participants in the program. Otherwise, program savings estimates may be statistically non‑significant even if savings are being achieved.

A hybrid EM&V approach, using a combination of advanced, automated AMI data analytics and targeted in‑depth evaluation, provides the most value to utility clients and regulators. Automated impact analysis using AMI data (M&V 2.0) can serve as an initial screening of participants. It can quantify realized savings measured at each participant meter using high accuracy pre-post time-of-week/time-of-year and temperature normalized savings models. Participant projects screened out of the automated analysis can be identified and sampled for deeper analysis, providing targeted insights to utility clients and regulators for more complex projects.

Where automated screening methods provide sufficient program feedback without further investigation into the reasons for measured savings, evaluation costs could be reduced relative to traditional methods. Automated M&V2.0 screening provides a high level, statistically significant measure of program performance without the need for follow-up evaluation for programs with established performance. The evaluator using such methods must demonstrate there is no bias introduced by using only projects with measurable savings to characterize program performance.

For mass-market (residential and small commercial) programs, traditional evaluation often involves the application of survey findings to validate and update deemed savings values. In many cases, an empirical econometric approach can deliver an answer with just customer AMI data and program tracking data if the key question to be answered is simply: how many kilowatt-hours (kWh) and kilowatts (kW) is this program giving me? Such empirically-based savings could reduce program implementation and evaluation costs by streamlining or eliminating the ex ante customer application process, provided savings are measurable at the meter.

 

AMI Data Brings New Possibilities for Energy Efficiency Measurement and Verification: Part 1

— June 29, 2017

Coauthored by Emily Cross and Peter Steele-Mosey

Utility industry stakeholders have been debating whether the proliferation of advanced metering infrastructure (AMI), also known as smart meters, will change the way energy efficiency program evaluation, measurement, and verification (EM&V) are conducted. Many utilities remain unsure about what is realistically possible. This uncertainty is compounded by the fact that new firms seem to emerge each year, claiming to provide increasingly deep insights into customers’ energy reduction potential (such as appliance-level load disaggregation and building-specific identification and targeting) using little more than consumption data from the utility.

How Can AMI Data Be Used?

In the field of EM&V, what is AMI data good for? How can it be used by utilities, regulators, and stakeholders to reduce evaluation costs, deliver more accurate and precise estimated program results, and improve the effectiveness of program delivery?

To answer these questions, it is helpful to define the two key evaluation-driven use cases for AMI data:

  1. Operational improvements: Early indications of program achievement provide the opportunity for course correction. Due to the continual collection of AMI data, it should be possible to quantify the impacts of changes in marketing approach and customer targeting on energy efficiency achievement more quickly than is traditionally required for program evaluation.
  2. Program impact evaluation: What is the best estimate of the energy and demand savings that a program delivered? This type of information is required to track utilities’ progress against mandated energy efficiency targets, to enable energy efficiency programs to be bid into energy and capacity markets as resources, and to quantify overall program cost-effectiveness.

Part 1 of this blog covers operational improvements, while part 2 will cover program impact evaluation. This topic is covered in detail in Navigant Research’s new report, Utility Strategies for Smart Meter Innovation: Energy Efficiency Measurement and Verification.

Operational Improvements

Utilities are all too familiar with the frustration of waiting for results from evaluators. Typically, a full year of data is required and the evaluation itself may take several months. This lag between implementation and assessment limits the ability of program administrators to course correct underperforming programs or understand how to tailor messaging to maximize the recruitment of high potential customers.

AMI data is collected continually, and several firms have recently come to market with prebuilt software solutions designed to quickly plug and play with this data. In theory and depending on the type of program, it should be possible to obtain ongoing updates of program performance long before the actual evaluation even begins.

These software packages have their limitations and are no substitute for a custom econometric evaluation, as they tend to be one size fits most. Additionally, the innovative approaches they employ sometimes lack the support of academic and professional literature from which econometric approaches benefit.

There is no denying, however, that these prebuilt software solutions can deliver results much more quickly than the traditional approaches. The results may not be sufficiently robust for a regulatory environment, but they may (depending on the program and the vendor) be sufficient to allow program administrators to take greater control of their programs and monitor their progress in near real-time. Program administrators would have the opportunity to make more effective use of program budgets and increase the value of their programs for their shareholders and ratepayers. They could use these software solutions for programs where simply multiplying the implementer‑reported savings by the prior year’s realization rates is not expected to be accurate.

 

Blog Articles

Most Recent

By Date

Tags

Clean Transportation, Digital Utility Strategies, Electric Vehicles, Energy Technologies, Policy & Regulation, Renewable Energy, Smart Energy Practice, Smart Energy Program, Transportation Efficiencies, Utility Transformations

By Author


{"userID":"","pageName":"Advanced Metering Infrastructure","path":"\/tag\/advanced-metering-infrastructure","date":"12\/18\/2017"}