The Power Sector's Transition to the Smart Grid
The power industry has developed a vision of the ultimate “plug-and-play” smart grid (SG). Many detailed and thoughtful architectures for this ultimate fully automated and optimized SG have been proposed.
There is a wide variety of opinions as to how we’ll get there from here, but there is consensus that it will take decades for a robustly implemented SG to come to fruition. There is also consensus that the total investment requirements will be enormous. Lastly, it is understood the journey will not be without obstacles because field implementation is always full of surprises.
A credible implementation scenario will not be just about technology; it will consist of business cases that take strategic drivers of the power sector into account. To implement the SG, we need a thorough understanding of the strategic drivers of its evolution – as a basis for planning, evaluating, and investing risk capital in R&D&D, new products and the infrastructure of this future grid.
Various players in the industry have developed a profusion of listings of the strategic drivers of the evolving power sector in the past few years. We have consensus, more or less, on the common elements of a “master list”, but not necessarily on their relative importance, given the differing agendas of impacted industry stakeholders.
This brief paper summarizes and clarifies the strategic drivers of the SG evolution, using a unique new and simplified categorization. The paper then presents the potential impacts of these drivers on service reliability and the cost of service, impacts that logically lead to the need for embedded intelligence in the power grid, i.e., the ultimate SG.
Strategic Drivers of the Power Sector
1. Structural Changes
The power industry is responding to the very real structural changes occurring in the electric sector, changes occurring in both its (1) physical and (2) market configurations.
Physical structural changes are occurring as a result of a broad set of energy policy mandates promoting:
- Renewable energy production, distributed energy generation and storage, micro-grids, electric vehicles, energy efficiency, increased end-use customer choices
Market structural changes are occurring as a result of efforts to increase the efficiency of electricity markets:
- New products such as demand response, frequency regulation
- Promotion of peak-shifting wholesale generation and transmission rates and dynamic pricing for end-use customers
- Competition from non-utility providers and end-use customers
- Broader participation in, and pending integration of, wholesale and retail markets
- Expansion of “incentive regulation” program
2. Aging Infrastructure
The infrastructure of the power sector is not just aging – it is aged, with much of it now well past its original design life. Legacy control systems are the norm, providing far less functionality than that available from automated intelligent digital devices available based on today’s technology. There is a strong concern within the power sector that this aging infrastructure, unmitigated, will inevitably lead to lower levels of service reliability.
Lastly, there is continuing verification of increased levels of cyber-based intrusions within the power sector. This has raised concerns in particular about the vulnerability of unprotected legacy operations technology (OT) -- the devices and software that control the grid. Legacy monitoring and control systems are widespread in our aging power system, designed and installed in an era when cybersecurity was not an issue.
So that’s it – our definitive list of strategic drivers of the SG – condensed into three categories.
How Do These Strategic Drivers Affect the Power Sector’s Performance?
The power sector’s performance is measured primarily by service reliability and the cost of service.
The physical structural drivers listed above, if unmitigated, will:
- Decrease service reliability due to the intermittency of renewable power production, the increased uncertainty of “net” load (demand) resulting from unpredictable end-use customer use of on-premises energy production and management equipment, and the operation the distribution system in ways for which it was not designed, i.e., two-way power flows
- Increase the cost of service because:
- The capital costs of renewable energy, energy storage, and some customer-owned production and energy management devices are currently much higher than traditional grid technologies (1, 2)
- Increased spinning and regulation reserves are needed to maintain existing levels of reliability as the proportion of renewable energy increases in the production mix (3, 4)
- The load duration curve’s shape is shifting unfavorably towards a lower asset utilization rate across the grid as the ratio of peak load to average load increases (5)
Fortunately, we have shown elsewhere that SG applications can fully mitigate the above negative outcomes. (6, 7)
In contrast, the market structural changes, when implemented, will increase service reliability and decrease the cost of service. However, this implementation is subject to a lengthy political and analytical process involving regulators, various stakeholders, and likely the legal system as well.
Most of the structural market changes presented here have been under discussion for decades with very little progress being made in terms of implementation. Structural market changes represent a major opportunity to lower the deployment cost of the smart grid, while maintaining acceptable reliability levels.
We Are Driving Embedded Intelligence into the Power Grid
To mitigate the negative and support the positive impacts of the above strategic drivers, we will be embedding intelligence across the power grid. This intelligence will be supported by today’s and tomorrow’s advanced information, operational, and communications technology.
The ultimate SG will be an optimized, automated system meeting a prescribed level of service reliability and security, delivering commodity-priced electricity. To achieve this, SG applications will introduce, on a project by project basis, automated intelligent digital devices distributed across the grid. The transition will take multiple decades.
Initially, the SG will deliver sensing, monitoring, diagnosis, and control functionality. As we progress in our understanding of the grid and develop more sophisticated algorithms, we will progress to automation, and ultimately to optimized operations.
The SG applications will have shorter working lives than the long-lived assets of today’s grid, but they will be substitutable, because interoperability will be the norm for all produced SG devices and applications (8).
The good news: planned properly, the net cost of the transition over its multi-decade duration should be zero, relative to continuing on a business-as-usual basis (5).
As always, comments are welcome and appreciated.
- Chris, Namovicz, “Assessing the Economic Value of New Utility-Scale Renewable Generation Projects”, US-EOIA, EIA Energy Conference, June 17, 2013
- “Distributed Generation Renewable Energy Estimate of Costs”, NREL, August 2013
- CPUC, “33% Renewable Portfolio Standard: Implementation Analysis – Preliminary Results”, June 2009
- Robert Gross, et al., “The Costs and Impacts of Intermittency“, U.K. Energy Research Centre, Imperial College, London, March 2006
- Geraghty, Dominic, “Shape-Shifting Load Curves”, smartgridix.com, January 25, 2014
- Geraghty, Dominic, “The Elephant in the Room: Addressing the Affordability of a Rejuvenated, Smarter Grid”, smartgridix.com, November 21, 2013
- “Estimating the Costs and Benefits of the Smart Grid”, EPRI Technical Report 1022519, March 2011
- Geraghty, Dominic, “ Implementation of the Interoperability in the Real Smart Grid”, October 2014, smartgridix.com (to be published, draft under review, available from the author)