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Part I of this two-part article considered the role of financial models in developing the business case for the Smart Grid. Part II continues with a discussion of regulatory requirements.

Multi-State Regulatory Requirements

While the Energy Policy Act of 2005 (EPACT) has mentioned initiatives to modernize the grid, it is important to note that much of the actual operation of the grid as well as decisions on investments to the grid, with respect to generation, transmission, and especially on the local distribution grid, are under the jurisdiction of the States. States jurisdiction is conducted through state legislatures and/or public utility commissions – and not the Federal Government. These decision-making bodies have authority over generation, transmission, distribution, and demand-side energy efficiency and demand response management. Each state has its own objectives and, often, its regulatory requirements are quite distinct from one another. For example, some states have a mandated equipment testing and certification schedule for retiring existing assets, for installing new assets, as well as criteria for claims and force majeure events.

All of these requirements will impact the costs and benefits for deploying Smart Grid technologies and need to be incorporated into the valuation exercise. In the case of utilities that have multi-state jurisdictions, the common modeling approach in one jurisdiction is not consistent with the regulatory requirements in its other areas, creating further complexity for the utility’s planners.

Utilities that pursue a Smart Grid deployment usually do so in multiple stages. Accordingly, different utilities, for that matter, different areas within a utility, will most likely be at varying stages in the overall deployment roadmap. A typical implementation may start with the automation of meter reading by installing smart meters and extends to communication and IT architecture, and finally towards a Smart Grid which consists of additional automation functionalities within the realm of the distribution network, and perhaps even the customer’s own personal network.

For instance, the distribution infrastructure includes substations and feeder circuits to carry power to neighborhoods and then distribution transformers steps down the voltage to our houses or commercial outfits. The AMI infrastructure integrates with the distribution system and provides automated meter reading and is augmented with an IT infrastructure. The most common benefits that are sought are through automated readings of kWh usage, i.e., energy consumption, and tamper detection, which are both directly used to support billing and revenue collection activities.

The Smart Grid is an extension over AMI. With sensors, instrumentation, and IT added to the substations and the lines themselves, massive amounts of data are collected and then processed so that actions can be taken in an automated manner. Using IT, it is possible to provide energy price information to customers thus providing an opportunity to optimize usage based on that data visibility, be it through manual or automated means. Subject to the prevailing interval price of power, the customer can then adjust usage. In case of power or gas outages, outage information is easily available and communicated to the user. In addition, using these sensors, utilities can automatically analyze all of that data for control purposes, for asset monitoring, for power-quality monitoring, and for increased outage intelligence. In summary, the Smart Grid allows utilities to take a proactive approach to outage detection and restoration rather than the other way around, i.e., relying on customers to alert utilities to power outages. The utility will know exactly where the outage is, what equipment is affected, and what the root cause is and automatically dispatch the repair crew. Additionally, the Smart Grid has the potential of isolating the fault with automatic switching and restoration of power service to as many customers as possible, by rerouting power flow around the problem.

Using “smart technologies,” utilities can conduct real-time analysis of distributed loads, remote control of distributed devices, and automatic management of customer demand. Finally, utilities can develop a portfolio of “demand side” tools to help bring the electric supply and demand equation back into balance. As the utility deployment progressively moves more towards a Smart Grid initiative from AMI, benefits from kW Interval Data, dispatchable rates, outage monitoring, read on-demand, selectable, billing dates, customer usage profiles, and dynamic load research are required to be included in the model to develop the complete business case.

Evidently, a utility may have multiple areas under different stages of deployment or a particular utility may choose only to implement a subset of all the components of the Smart Grid for its own strategic reasons. Therefore, there is considerable customization of the valuation model in estimating the timing and sequencing of these benefits and costs to reflect the true deployment diversity – all of which would be very hard to include in a simple generic valuation model.

In addition, key assumptions regarding improvements to utility operations will vary considerably across the range of services that be supported at various performance levels. For example, some utilities outsource all or portions of their meter reading, call center, or billing operations, thus the valuation of benefits related to these areas will require changes in formulation and timing, as well as inclusion of costs for such items as early contract termination.

In recent months, many public utility commissions are requiring that utilities include system-wide benefits into their business case. This change is significant because utilities typically did not have the necessity, motivation, or incentive to evaluate and include benefits that would occur to customers and to the society at large and not directly impact the company’s balance sheet or income statement. Furthermore, the relative size of previous automated metering investments did not rely as heavily on enterprise-wide benefits, as they do today for AMI. Valuation models, therefore, often need to quantify societal benefits, such as avoided generation investment, reduction of greenhouse gases and overall carbon footprint, or intangible customer benefits such as increased satisfaction due to better service and billing, and wider service offerings and choices.

Some of these benefits, such as increased customer satisfaction, though hard to quantify, are benefits nevertheless and, depending on the regulatory environment, may need to be considered in the regulatory review process. The rationale to include these benefits is that despite the lack of realization of some of these societal or non-operational benefits, the market or society at large benefits from various aspects of implementing Smart Grid technologies and needs to be considered in these discussions.

In most practical situations, the valuation modeling for an investment of this size and importance are often conducted in conjunction with other specialized analyses within the enterprise. Many utilities will need to consider the impacts to, or from, the AMI or Smart Grid analysis and may already have incremental processes to conduct these analyses. This strong coupling may requires the Smart Grid valuation modeling to be structured in a manner that supports other internal utility analyses, particularly as it relates to relevant financial metrics and other key output variables. Some of these additional analyses could include (but not be limited to) the following:

Capital Allocation Modeling: In practice, a large utility will be evaluating multiple investment options simultaneously, some of which will be competing for a limited amount of capital. Smart grid capital projects will likely occur over multiple financial and budget cycles. As a result, utility decision makers would be faced with choosing from an array of projects that may be funded over similar or much shorter budget cycles. In almost all cases, the choice of projects is based on an optimal decision to maximize the overall benefit subject to the constraints of limited finances, particularly where working capital recovery may be limited in the regulatory process. Under such situations, it becomes necessary for utilities to more carefully analyze AMI program funding as part of an optimal portfolio of investments, to maximize overall return on investment or meet similar metrics consistent with the utilities’ strategic, financial, and risk considerations.

Risk Analysis and Strategic Decisions under Uncertainty: Smart grid deployments, like any other large scale projects (e.g., power plants), are faced with inherent uncertainties. In addition to usual project management uncertainties regarding project schedule, resource planning, and execution, uncertainties related to new product and technology performance can also have a significant impact on the business case outcome. Depending on the complexity of the deployment, conducting risk analysis and identifying sensitivities in costs and benefits to variation in key inputs may become important in the decision making. For example, energy demand elasticity usually has a variance. To meet the goal of resource adequacy if certain aspects of demand response were assumed in lieu of constructing new facilities and, in the process, some avoided capital benefits were taken, a variation of demand may occur, forcing construction of new facilities that may otherwise result in a change in the outcome of the business case.

To facilitate the risk analysis, usage of probabilistic risk assessments such as, Monte-Carlo simulation and other sophisticated valuation techniques (e.g., real-options) may need to be either incorporated into the model or performed post-modeling. While it may be argued that quantified cost-benefit analysis should not be the only consideration in deciding the merit of an investment case,, it certainly has become the principal focus for evaluating Smart Grid investments and in deciding whether the investment is in the public interest. The costs and the potential benefits of these projects are inherently uncertain, and difficult to quantify, as is the case with any new technology and uncertainty in service level and customer acceptance. A robust and exhaustive model, with sufficient scenario analyses and probabilistic risk assessment, becomes a very important part of helping decision makers to make the best choices under all these uncertain considerations.

Conclusion

Building the business case is an integral part of the AMI/Smart Grid initiative in which many utilities are seeking to embark. The business case is vital for justifying the investment - internally - for large Investor Owned Utilities to ensure that such investments have economic merit. Externally, the business case provides the principal means to justify regulatory cost-recovery where these investments are to be included in revised rate structures. To facilitate this modeling effort and establish a common baseline, there is an increased interest in seeking generic frameworks and valuation models among regulators and other stakeholders. While this “one-model-fits-all” approach is useful in providing the broad requirements of the business case, it does not provide sufficient treatment of the specific requirements of the utility’s specific situation. Utility managers, regulators, and other potential users are advised to exercise a good understanding of their issues and conditions and then determine the modeling approach for their AMI/Smart Grid deployment with company-specific modeling tools and more specific assumptions and key inputs.