Navigant Research Blog

Smart Cities: It’s All Relative

— July 29, 2015

Cities around the world are increasingly adopting technologies to improve the quality of life in the modern city, where traffic congestion, air pollution, and a lack of mobility are often the norm. Many smart city technologies are also being developed to deal with specific issues in energy distribution, energy and water management, transportation optimization, and public safety and security. Navigant Research defines a smart city as the integration of technology into a strategic approach to sustainability, citizen well-being, and economic development.

Currently, the level of smart city technology integration varies greatly by region. What is considered to be one of the leading smart cities in Brazil, for example, may be far behind some of the leading cities in Denmark. To illustrate this, let’s compare Curitiba, Brazil, with Copenhagen, Denmark.

Apples to Oranges

Curitiba has one of the most advanced recycling programs in Brazil, yet the city recycles just 20% of its waste.  In Copenhagen, 57% of total waste was recycled in 2009. Additionally, incineration centers are converting waste to energy by using steam from the water that is heated in the incinerator ovens. Roughly 80% of this steam energy is being used in the municipal heating system, and 20% is being fed back into the electricity grid. While Curitiba deserves significant praise for pioneering a very successful bus rapid transit (BRT) system, the city is still struggling with congestion and has just recently made initial plans for subway system infrastructure. Conversely, Copenhagen Metro began operation in 2002 (22 stations, nine of which are underground), and a driverless light metro supplements the larger S-train rapid transit system. Back in Brazil, Curitiba has the highest rate of public transport use in Brazil (45% of journeys), while in Copenhagen, it is estimated that 50% of all citizens commute by bicycle every day.

Beyond specific projects, broader climate action goals between these two cities are also quite different. Copenhagen aims to become the first carbon-neutral city in the world by 2025. The city has established targets in energy efficiency, renewable energy, and green building standards (all new buildings must be carbon neutral by 2020). Navigant Research has been unable to identify any city-level sustainability or climate action plans in Curitiba.

GDP Considerations

This comparative analysis by no means intends to detract from the tremendous achievements and progress in sustainability that Curitiba has attained. Instead, it seeks to illustrate the regional nature and context of what constitutes a leading smart city. With a gross domestic product (GDP) per capita of roughly $60,000 in Copenhagen, a much larger volume of resources is available for smart city development than in Curitiba, where GDP per capita is estimated to be $13,000.

The global smart city technology market is forecast to be worth more than $27.5 billion annually by 2023, according to Navigant Research’s Smart Cities report. Cumulative global investment in smart city technologies over the decade is expected to be $174.4 billion.

Annual Smart City Technology Revenue by Region, World Markets: 2014-2023

Smart Cities Revenue

(Source: Navigant Research)


Compliance Strategies for Satisfying Clean Power Plan Requirements

— July 23, 2015

Next month, the U.S. Environmental Protection Agency (EPA) is expected to release the final Clean Power Plan (CPP) rule, which regulates carbon dioxide emissions from existing power plants. While states may comply independently or work together to achieve CPP goals, Navigant Consulting has found that states can substantially reduce compliance costs by banding into trading blocs, and we have focused on regional trading in our modeling. The proposed rule is modeled in Navigant Consulting’s recent white paper,  Anticipating Compliance: Strategies and Forecasts for Satisfying Clean Power Plan Requirements, and highlights our finding that focusing on energy efficiency (EE), coal retirements, and targeted renewable expansion represents the least-cost compliance option.

Energy Efficiency

EE represents the lowest-cost compliance option in almost all areas, but it cannot single-handedly achieve compliance.  Expanding EE programs also helps ease interim compliance targets because EE can be rolled out more rapidly than new generators, reducing the near-term need to build large amounts of new low-carbon capacity. Navigant Consulting found that the expansion of EE programs in response to the CPP can save nearly $250 billion above business-as-usual EE through 2030.

Coal Retirements

The Northeastern, Southeastern, and Midwestern United States are expected to rely heavily on coal retirements for compliance. Since EE and renewables are less carbon-intensive than gas generation, higher penetration of these technologies helps keep more coal generators online.

Regional Least-Cost Compliance Options

(Source: Navigant Consulting)

Natural Gas

New gas generation plays an important role in compliance, and it is necessary to help maintain capacity and energy resource adequacy after coal retirements.  The Northeast and Southeast, in particular, will likely rely heavily on new natural gas combined-cycle plants to supplement EE in replacing retiring coal plants, and building these plants will be a large portion of their compliance costs.  The central and western United States will also rely heavily on gas to maintain capacity margins, but will likely see more simple-cycle peaking gas plants than the Northeast and Southeast due to a high rate of renewable expansion as well as EE growth.


Adding renewables is a cost-effective compliance option where renewable potential is high, especially in the central and western United States.  Navigant found wind expansion to be economic throughout the western and central United States, and it plays a particularly important role in compliance in Texas, the Southwest Power Pool (SPP), and Midcontinent Independent System Operator (MISO).  California, which has little coal left to retire, has to rely on EE and renewable resources almost exclusively for compliance. Solar and wind both play critical roles in ensuring low-emission generation in California.  Navigant Consulting found that areas that rely more heavily on renewables tend to need to spend less on replacing capacity than other areas, but also tend to see higher carbon allowance prices (which help make large-scale renewable buildout economic).

Glide Path

Many commenters to the EPA focused on the difficulty of meeting near-term interim targets.  Navigant Consulting’s analysis has shown that the implementation of a glide path with less stringent initial targets results in savings of over $200 billion when compared to a non-glide path scenario.


Do Energy Efficiency Investments Deliver? Yes!

— July 13, 2015

A new paper from the University of California, Berkeley and the University of Chicago garnered a little press this week and deserves a deeper dive. The paper makes a broad claim about demand-side management (DSM) program impacts based on a comprehensive study of program performance, with one hitch—the focus is exclusively low-income weatherization. One Forbes perspective came to the conclusion that “the study shatters a central orthodoxy in the rarified realm of energy and environmental policy. It suggests that energy efficiency is not necessarily a win-win solution for the environment and the economy. That suggestion is likely to influence future political debates over federal subsidies for energy efficiency.”

The authors have made a dramatic claim that falls short of the bigger picture on DSM program impacts. The paper states that “even when accounting for the broader societal benefits of energy efficiency investments, the costs still substantially outweigh the benefits; the average rate of return is approximately -9.5% annually.” Low-income programs have long had a special place in utility DSM projects as a public benefit and have been accepted as a part of the broader portfolio approach to energy efficiency by passing less stringent cost-effectiveness tests than other program types.

In fact, in an American Council for an Energy-Efficiency Economy (ACEEE) paper from 2014, this very issue was fleshed out. Low-income programs have faced distinct challenges from other energy efficiency programs but do not represent the overall cost and benefits of DSM as a whole. Let’s take a deeper look at recent utility program performance. 

Here are the results from the most recent Energy Efficiency Evaluation Report for the state of California:

California Energy Savings for Statewide 2010-2012 Portfolio

Casey Chart

 (Source: California Public Utility Commission)

The report also states that the portfolio of energy efficiency activities for 2010-2012 was cost-effective, with every dollar invested in non-codes and standards energy efficiency returning $1.04.

Extrapolating the performance of one category of a utility energy efficiency program, in one state, from one study can mislead the public in understanding the macro-level impacts of energy efficiency as a whole. Maybe even more problematic is the threat of using this kind of academic assessment as fodder for the heating politics of energy policy in the United States. Let’s keep an honest focus on the big picture.


States’ Roles in the Clean Power Plan

— June 25, 2015

Cross_Gatel_webThe U.S. Environmental Protection Agency (EPA) plans to finalize the Clean Power Plan (CPP) this summer. As part of the plan, states will have 1 to 3 years to submit State Implementation Plans (SIPs) to the EPA for review. Some states are already starting the planning process to develop an SIP, and most are beginning with stakeholder meetings that include utilities and other major players in their state. Other states are waiting to see the final regulation before they begin.

States face a complicated web of decisions when crafting SIPs. The figure below shows a simplified hierarchy of the paths that they may take. States are unlikely to go through the decision process in a linear fashion; instead, they will need to consider all options and narrow them down based on their existing policies, resources, and stakeholder goals, among other factors.

SIP Example Decision Process


CPP Decision Tree - Recreated

(Source: Navigant Consulting)


The first decision a state needs to make is whether to submit an SIP. If a state does not submit an SIP, the EPA will impose a Federal Implementation Plan (FIP). The EPA has indicated that it may include insights on what an FIP will look like when it releases the final rule this summer. Some states have passed legislation limiting their state agencies from submitting an SIP without legislative approval, which could impede those states from submitting an SIP at all.

A decision that will need to be made early in the process is whether or not a state wants to work with other states to submit a regional plan. There have been proposals, for instance, from Duke Nicholas Institute, that individual plans could be crafted to be standalone and still allow trading of credits with other states, similar to the way that renewable energy credits (RECs) can be traded among states even though Renewable Portfolio Standard (RPS) policies were not coordinated prior to implementation. However, many states are already in discussions about coordination efforts—for example, 14 Midcontinent states submitted comments to the EPA on its proposal and held a stakeholder event on June 5.

If states do work together on regional implementation plans, under the proposed rule they would have an additional year before their plan is due to the EPA. This allows additional time to coordinate among the many players involved across all coordinating states, but narrows the amount of time between when the implementation plan is approved by the EPA and compliance begins—potentially as little as 1 year.

Targets and Policies

Another decision that states must weigh in on is whether or not to use the rate-based target laid out by the EPA or to convert it to a mass-based target. This decision is interrelated with the kind of policy regime a state chooses to include in its SIP. A rate-based target may be more appealing to states that impose individual unit obligations on fossil units in their state, as it eliminates the uncertainty surrounding future load growth. Conversely, a mass-based target may be easier to implement in the northeast, where a mass-based cap-and-trade system already exists.

States will also need to determine how to integrate existing renewable and energy efficiency policies into their SIPs and decide if new policies are needed. These include RPSs, energy efficiency standards, and updates to building codes and can be combined with cap-and-trade, as in California, or standalone.

There are many additional considerations for states to take into account as they craft implementation plans. For the best overall outcome, it is recommended that states start early, have meaningful stakeholder involvement throughout the process, and leverage modeling and analytical tools where possible.


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