AMI: Bridging the Gaps

Advanced Metering Infrastructure (AMI), or Smart Metering, is one of the hottest topics in utilities today, yet there are significant gaps in the technologies, the regulatory climate, and utility implementations, that could bring about a premature end to this promising trend.

The first gap is technology. We’re not talking creeping elegance here. We’re talking about “peddle to the metal.” Three years ago AMI was a term most industry insiders had trouble distinguishing from AMR (Automated Meter Reading). We dreamed to have hourly interval data. Today we have legislation that requires 15-minute interval data, and policy that contemplates 10 minute or better. In addition we have Energy Management, Demand Response, and Smart Grid applications being blended with AMI. It is easy to build requirements and specifications. It is not so easy to design, build, and operate systems that deliver these capabilities. In fact, since the term AMI has come into existence, we have yet to see implementations exceeding even half a million end-points that can deliver on the basic AMI promise.

The second gap is our regulatory environment. One of the greatest promises of AMI is Demand Response, yet effective DR could lead to reduced utility revenues. Few states have instituted the ability to enter into a dialogue with their investor-owned utilities in a fashion that recognizes and rewards the utility to reduce overall consumption.

The third gap is utility implementation. Beyond fundamental AMI technology and the regulatory issues lies potentially the largest gap. This is the implementation gap the ability for utilities to architect and implement enterprise-wide programs, which leverage AMI technologies and existing business processes to deliver true business efficiencies and optimizations.

The Technology Gap

We live in unprecedented times when it comes to communications and information technology. The ever-expanding worldwide market for voice and data communications, and unabated progress of Moore’s Law, has brought about dramatic improvements in communications capabilities, information capacities, and digital signal processing, and while these technologies are making their way into utility AMI, increasing capabilities at decreasing costs, issues still exist.

The technology gap is really an expectation gap. Utilities want reliable, cost effective, interoperable and interchangeable AMI technology that meets or exceeds the latest AMI requirements. Despite the technology progress we have seen, the evolution of utility requirements outstrips the commercial community’s ability to develop and validate technology owing to the size and complexity of the problem at hand. It’s easy to envision requiring 15-minute interval data instead of hourly, but it’s harder to appreciate that this equates to: 4 times the data retention in each meter; 4 times the communications capacity to transport this data on a daily (or more frequent basis) from the meters to the utility; and 4 times the storage and processing capacity at the utility to collect and make use of this data. By analogy imagine a cellular system, where each and every subscriber changed their daily usage of voice, text, and data by a factor of 4. Could an existing system handle such an increase in usage without performance degradation or infrastructure enhancements? The same dilemma is facing the AMI providers. As systems are being designed and validated to meet one set of requirements, new requirements continue to push the functionality and performance envelop, broadening the expectation gap between what exists today, and what is desired tomorrow.

Utilities could specify the capacity of their desired AMI systems such that they could support increased future requirements, but at what cost? A system with 4 times the capacity for the future may not be justifiable within today’s AMI business case. AMI is a long-term investment, and it is imperative that investment considerations carefully and thoughtfully weight all present and future options. Vendors can help address this dilemma by developing capabilities to incrementally increase system functionality and performance. For example, remote software upgrade for all system elements (meters, network equipment, etc.) limits the risk of future functionality; and network infrastructure that enables communications bandwidth to be increased incrementally (versus replacement) limits the risk of future performance. Providing the potential for future functionality and performance improvements at an incremental cost today, and additional incremental cost tomorrow would mitigate a good deal of the expectation gap risk.

Other evolving AMI technology requirements include home area networking and smart grid. Home area, or in-premise, networking is evolving as the means to integrate the energy consumer into the utility supply and demand equation. Numerous pilots have shown that demand response works, and that the elasticity of consumer response increases with access to consumption and rate information, and a means to utilize this information. Home area networking requirements contemplate an additional communications “channel” into the home or premise. This would allow the utility to publish information that devices in the home could subscribe to. Published information could be as simple as present consumption (as registered by the meter), and current rate information, but could include utility-generated commands to dispatch or control loads within the home as well. A variation of load control is whole house remote disconnect/reconnect for use in revenue management, and even more importantly in system reliability in extreme situations, avoiding less controllable rotating black or brown outs. Load limiting via such devices can enable the use of emergency systems (such as lifesaving equipment, communications, and general lighting) while mitigating the largest, less critical loads.

These evolving requirements possess both technology and standards challenges. Home area network technologies such as ZigBee, Home Plug, CEBus, and a multitude of others are in various stages of development; provide little to no interoperability; and have so little adoption that there is even no de facto standard. In the U.S., ZigBee has garnered a lot of interest from the AMI and load control communities, however, the ZigBee standard is still in a state of ratification, especially in terms of the application level protocols (called public profiles) required to provide the interoperability of energy management devices. Today there exist standalone operational load control and demand response systems, but no integrated AMI and load control and demand response systems, although several are planned.

Smart Grid applications look to leverage a common communications infrastructure along with AMI for applications such as Volt/VAR management via capacitor controllers, voltage regulation, remote switching and recloser operations, transformer monitoring, and fault indication. Today we only have the capabilities to utilize such an infrastructure in a command and control fashion. Tomorrow, we have the promise of: advanced, distributed grid control applications; peer-to-peer communications; and in-situ decision-making.

The Regulatory Gap

Many utilities are considering the adoption of AMI. Primary drivers include the reduction of operational costs, enhanced customer service, and improved outage response. While these savings cover much of the cost of AMI implementation, they do not typically cover the full cost, especially when advanced technologies such as home area networking are considered. Demand response and time-based rates provide additional benefits that can make AMI cost-effective to consumers provided there exists a regulatory environment that is open to cost recovery of such an investment.

Numerous regulatory jurisdictions have adopted policies favoring the deployment of AMI systems. California has led the U.S. with regulatory policy for demand response valuation, and the approval of PG&E’s and SDG&E’s AMI filings representing in excess of 11 million electric and gas meters. Texas recently established legislation backing up original policy enabling recovery of AMI investments meeting established functionality and performance specifications. Ontario, Canada has called for 800 thousand AMI meters to be deployed by the end of this year (2007), with all 4.5 million electric customers to receive smart meters by the end of 2010.

At a national level FERC has assessed the need to deploy AMI in support of demand response; however, adoption of favorable policy on a state by state basis has been slower than that contemplated by the Energy and Policy Act (EPAct) of 2005. Multiple reasons for this exist. As already discussed AMI technology is new and rapidly evolving, and there is a general lack of knowledge by regulators and policy makers regarding the capabilities and cost of these systems.

Time-based rates have been around for decades, but rates contemplated for demand response such as a variety of time-of-use and critical peak pricing rates as well as incentive variations such as peak-time rebate, are equally poorly understood. Further difficulty to adoption is the debate regarding the adoption of such rates, and whether they should be based on opt-in or opt-out policies. An additional problem is that time-based rates are not typically amendable to all consumers across all demographic and socioeconomic groups, and regulatory interveners get caught up in defending their constituents to the potential detriment of the society as whole.

Finally, there is insufficient policy regarding the treatment of utility (shareholder), consumer (rate payer), and societal benefits stemming from AMI. Demand response capabilities can be considered a preventative investment that will only provide a probability of return based on the frequency of use. The risk-reward equation between ratepayers/society and utility shareholders needs to allow utilities to recover such investments, and then share the benefits to consumers and society in the eventual use of such systems.

The Implementation Gap

An AMI system is much more than replacing meter readers and getting reads more frequently and accurately. AMI is a pivotal information source and control infrastructure that, used effectively, can drive enterprise-wide efficiencies and benefits. Benefits often include:

• Reduced system capacity requirements
• Improved outage detection and restoration
• Reduced distribution system losses
• Improved power quality
• Increased system reliability
• Reduced and improved field maintenance
• Improved distribution automation and an enabler for Smart Grid
• Better distribution asset monitoring
• Better system planning
• Better transformer load management
• Improved load forecasting, rate design and rate validation
• Dampening of price volatility impacts
  
• Enhanced revenue protection through remote disconnect options and the detection of energy diversion
  
• Gateway to load control and in-premise energy management applications

Beyond business case development, technology selection, and regulatory approval comes AMI system implementation. To achieve the benefits and promises of AMI, utilities must design, build, and operate and maintain complex systems that touch almost every operational system and business process. This is the implementation gap.

First and foremost a solid and robust AMI design is required to bridge the implementation gap. A design starts with traceability from AMI benefits, to AMI functional and performance requirements and process and infrastructure changes. A design further decomposes the AMI solution into discrete elements that can be sourced as necessary. Common elements include: AMI meters; load control and/or demand response devices; distribution automation and smart grid devices; communications networks; AMI, load control/demand response, and smart grid application, control, and data collection head-ends; end-point installation; communications network installation; meter data management system (MDMS) license, installation, and configuration; systems integration (head end to MDMS, and MDMS to existing utility applications); program support services including program management services, deployment and/or operations services, and rate design and/or marketing services; and operations and maintenance services for any of the aforementioned elements but most commonly end-points, communications network, and MDMS. Finally the design of an AMI system requires a solution implementation plan or roadmap that provides discrete project steps typically in the form of business releases, and the means to validate these releases as well as the final solution with respect to the formal specification and AMI benefits. Typically utilities seek external expertise from consultants and systems integrators for the design of an AMI solution.

Next step in bridging the implementation gap is building the AMI solution. This begins by establishing program management and coordination over all the discrete elements of the AMI solution and the commercial entities that provide them. One of the greatest gaps in the build phase is the lack of skilled and experienced solution providers. Utilities today are forced to engage the services of multiple product and service providers to build an AMI solution, often including expertise to support the program management efforts as well. The sourcing and coordination of multiple resources increases the complexity and potential risk of an AMI program. One way to alleviate such problems is for the industry to develop the capability to source solutions across the myriad elements required.

Finally, operations and maintenance of the AMI solution throughout its intended operating life and vigilance over benefits realization is the last step to bridging the implementation gap.

Conclusion

AMI is one of the most promising means by which utilities can radically impact society, consumers, shareholders, and employees. To prevent a premature end, we must work to bridge these gaps by recognizing their existence and proactively seeking ways to avoid them or mitigate the impact of the risks they represent. To do so requires the willingness to understand, educate, and seek collaborative solutions with domain experts, technology and providers, and regulators.

Podcast

Advanced Metering System Implementation at Alliant Energy
Speaker: Rick Potter
Date: 25/07/2007
Duration: 25min

Summary: This podcast discusses the AMI implementation project underway at Alliant Energy. Rick Potter of Alliant Energy and Jeff Evans of Enspiria Solutions discuss the current status of the project, technology benefits and lessons learned.

Listen now