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Efficiency & Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.

Contract No. DE-AC36-08GO28308

Approaches for Planning and 

Implementing Sustainable 

Energy Growth in a Complex 

World

Preprint

N. Snyder and A. Schwab

Presented at the 2012 World Renewable Energy Forum

Denver, Colorado

May 13-17, 2012

Conference Paper

NREL/CP-6A20-54506

June 2012
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1

APPROACHES FOR PLANNING AND IMPLEMENTING SUSTAINABLE

ENERGY GROWTH IN A COMPLEX WORLD

Neil Snyder

National Renewable Energy Laboratory

1617 Cole Blvd.

Golden, CO 80401

neil.snyder@nrel.gov

Amy Schwab

National Renewable Energy Laboratory

1617 Cole Blvd.

Golden, CO 80401

amy.schwab@nrel.gov

ABSTRACT

Efforts to promote significant market penetration of 

renewable energy have come to incorporate elements of 

complexity thinking; this includes looking at the energy 

sector as a system of systems, and including sociopolitical 

factors in these systems rather than focusing only on 

technical systems. These approaches are necessary, but not 

sufficient, and past strategies toward formulating roadmaps 

to high renewables penetration depend on unlikely 

scenarios. Fuels and electric power are commodities, and 

most people are satisfied when these commodities are 

readily available at a reasonable price. History suggests that 

this situation will likely change only in response to a major 

crisis such as a climate disaster, an energy shortage driven 

by growing demand, or a supply interruption caused by war.

Obviously there is no firm way to predict a crisis, but 

drivers can be suggested for many types of crises: global 

population growth, pollution of all types, resource 

imbalances, etc.

A new approach is needed that builds awareness of 

knowable drivers to prepare for and capitalize on knowable 

events, and to build resilience and foresight for responding 

to unknowable future crises and opportunities. This paper 

will build on current thinking related to sustainable 

development, energy forecasting, and complexity theory and 

show how past roadmapping methodologies fall short. 

While proposing ways of thinking about our responses to 

global changes, we consider how we can create and discover 

the pathways through those unpredictable changes toward 

high global renewables penetration.

1. INTRODUCTION

The subject of sustainable energy development has been 

widely discussed and debated in recent years. However, 

despite widespread interest, progress toward this goal has 

been limited. The following discussion will attempt to 

identify some of the barriers to progress, and will attempt to 

recommend improved approaches, based on current theories 

about large-scale systems.

2. THE SITUATION AS IT IS—WHAT’S BEEN TRIED 

AND WHAT DOESN’T WORK

There is a significant level of support for altering the energy 

supply and demand status quo. This support comes from a 

variety of viewpoints, including reduction of carbon 

emissions, concerns about peak oil and the growing global 

demand for oil, and addressing the national security 

concerns of nations that depend on other nations for much 

of their oil supply. Proponents of these various viewpoints 

may disagree about specific approaches, but it is still 

reasonable to project that these collective concerns will 

drive changes to the global energy economy in the coming 

decades. The challenges are to plan, estimate, and project 

the exact trajectory of these changes and the ultimate 

outcomes.

Leaders from various stakeholder organizations want to 

have some level of comfort about the expected outcomes 

from policy or investment decisions to be able to 

constructively promote change. Achieving such a comfort 
2

level will require appropriate tools and techniques, and it 

will be argued in the following sections that current tools 

and techniques do not fully meet the needs. The vision 

promoted here will be to better understand our complex 

world, and to develop new ways of thinking that can, as 

much as possible, envision and influence the future of 

global energy.

Major energy sources have evolved over the past two 

centuries, from wood to coal to oil and gas to nuclear and 

renewables. A discussion of this history is beyond the scope 

of this paper, but the drivers for this historical development 

have been a mix of resource availability, technological 

developments, investment decisions, and public policy 

decisions. The actual pathways that developed were not 

driven by overarching goals such as those described in the 

current vision. There generally was no designed approach to 

the development of the various systems, and development 

occurred at an evolutionary rather than a transformational 

rate of speed (1). The history of the U.S. energy sector is 

therefore not a good model for developing a roadmap for 

our energy future.

The current global energy supply is dominated by fossil 

fuels. Their major sources are not uniformly distributed, but 

rather are concentrated in a few countries; see Figure 1. This 

uneven distribution has significant geopolitical impacts, 

affecting commerce, international relations, and even armed 

conflicts.

Fig. 1: Major Oil-Producing Countries (2)

The sheer size and dominance of the fossil fuel industry 

constitute a major impediment to a large-scale shift to more 

sustainable energy sources. A discussion of industry details 

would need to be extensive, but for the purposes of this 

paper one way to highlight its magnitude is to consider its 

impact on U.S. foreign and military policy. After the fall of 

the Soviet Union, the United States had no reason, from a 

global perspective, to continue its military focus on the 

Persian Gulf. However, this region remained critical 

because of its significant oil production, and U.S. policy 

remained focused on protecting oil supplies as a critical 

principle (3). Another way to highlight the influence of the 

fossil fuel industry is to look at U.S. government subsidies; 

a 2009 study estimated that over a recent seven-year period 

the fossil subsidies totaled $72 billion; the renewable 

subsidies totaled $29 billion. In addition, nearly $17 billion 

of the renewables total went to corn ethanol, which is a 

renewable source but one that does not contribute to an 

infrastructure change toward more sustainable electric 

vehicles (4).

The bottom line on the current energy system structure is 

that the system is enormous, and thus hard to change, and it 

has evolved to its present configuration in an uncontrolled 

manner. This reality suggests that traditional methodologies 

for planning and promoting change are unlikely to be 

successful; new ideas are required.

3. THE IMPOSSIBILITY OF PREDICTING HOW IT 

WILL OCCUR

There are well-established methods for predicting the future 

of energy supply and demand. Typical methodologies are 

based on trend analysis and assumptions that are based on 

historical patterns. In the United States, the key organization 

for energy data collection and forecasting is the Energy 

Information Administration (EIA). The current EIA 

projection for electricity generation through 2035 provides a 

good example of an energy forecast; see Figure 2. Note that 

in this forecast the mix of energy sources for electricity is 

not significantly different from the mix today.

Fig.2. EIA Electricity Generation Forecast (5)

Canada

5%

Mexico

4%

United 

States

14%

Brazil

4%

Venezuela

3%

Europe

7%

Norway

3%

Russia

15%

Iran

Iraq 6%

3%

Kuwait

4%

Saudi 

Arabia

15%

United 

Arab 

Emirates

4%

Algeria

3%

Nigeria

4%

China

6%

Percentage of World Supply
3

Several issues influence the advancement of sustainable 

energy growth, which in turn severely limit the ability to 

plan for this growth. The first and foremost issue is the 

notion of planning for anything on a global scale; this has 

not been done before, and the feasibility of actually doing it 

is highly questionable. The second issue is the lessons from 

energy development history, as described above; multiple, 

sometimes disconnected drivers will dictate the 

developmental pathways and ultimate outcomes. Finally, 

there is the issue of the complexity of the global energy 

system; this issue requires further discussion.

The science of complex systems is relatively new, having 

developed over the past few decades. This body of 

knowledge is multifaceted, and not all aspects are applicable

here, but fairly recent developments provide useful 

information about understanding the nature of the global 

energy mega-system. Complex systems are defined as 

containing all of the following: diversity, connection, 

interdependence, and adaptation (6). There are many 

properties of complex systems, but perhaps the most 

interesting is that they have emergent properties. In the 

energy mega-system, which meets all the requirements for a 

complex system, properties emerge that cannot necessarily 

be predicted by studying the underlying components. A 

positive result of this phenomenon is that the system 

becomes very robust, which means that consumers will 

largely continue to have reliable energy supplies in spite of 

unpredictable negative events. However, when attempting to 

fundamentally change the system, as is the case when 

driving a change from fossil to renewable energy, the 

robustness of the current system will tend to reinforce the 

status quo, so any changes will be resisted.

Another macro-level feature of the present global 

environment is that, according to some authors, we are at a 

point of significant change at the global level. One argument

is that we are entering yet another “age,” chronologically 

following the agricultural, industrial, and information ages.

The three overarching characteristics of this age are 

accelerating electronic connectedness, global economics 

leading to global culture and politics, and increasing 

individual choices and control that will decrease the power 

of institutions and organizations (7). Another argument is 

that we are entering a revolutionary age unlike anything that 

has been seen in the past few hundred years. The driver for 

this revolution is an increasing number of players, 

interconnectedness, and the speed of information

transmission. The result of this new reality is the 

development of nonlinear systems (sandpiles) that represent 

energy that is ready to avalanche, which in turn can produce 

great change that is unpredictable because it is organic 

rather than mechanistic (8). The characteristics noted here, 

based on analysis of current global realities, match up well 

with those of complex systems.

The key point of visualizing the global energy mega-system 

in complex systems terms is to frame any discussion of 

changing this system within the associated realities. A new 

framework for change is needed—one that is based on 

working with uncertainty rather than relying on traditional 

reductionist thinking.

4. AN APPROACH TO GUIDE OUR PATH—IN LIEU 

OF A ROADMAP

Sustainable energy growth can be justified on the basis of 

various drivers; three that are commonly cited in support of 

renewable energy are the environment (carbon concerns 

and/or pollutants), national security, and energy security.

However, energy is a commodity, and as such changes to 

how energy is produced are not necessarily important to the 

typical consumer. To raise the level of importance in the 

public’s perception, it is necessary to frame sustainability as 

a value proposition.

Actually creating a sustainable environment is more of a 

sociopolitical activity than a technical one, and the technical 

community has responded to this reality by creating many 

“scenario analyses” that are intended for consumption by 

policymakers. The shortcoming of these analyses is that 

they attempt to visualize one or more possible future states, 

but they sometimes gloss over the many difficult steps 

needed to get to the end state. Detailing those steps is a

function of traditional roadmapping.

4.1 Roadmapping

Roadmapping is a method for strategically charting 

technological development toward a desired end state. There 

are various references for this process, but for sustainable 

energy development, which will be largely a commercial 

activity, a reasonable reference is the International 

Technology Roadmap for Semiconductors; this activity is 

managed by an international consortium of chip 

manufacturers. The process develops improvement targets 

for parameters such as cost, throughput, power 

consumption, and physical size. Targets are developed 

under the assumption of continued scaling of electronics; 

underlying this is the assumed validity of Moore’s Law, 

which predicts that the number of components per chip 

doubles roughly every 24 months (9). Referring back to the 

definition of complex systems, the semiconductor industry 

does not seem to meet all the requirements, and an 

examination of the roadmapping methodology reveals 

traditional reduction of technical elements into building 

blocks that can be individually improved.
4

4.2 Decision-Making

Closely related to roadmapping is decision-making.

Traditional decision-making does not take into account the 

behavior of other interested actors, and it focuses on a single 

outcome rather than on system properties. This process 

focuses on command and control optimization, rather than 

on understanding the systems within which one must work 

(6).

Alternatives must be proposed to replace traditional 

processes and to establish the value proposition for 

sustainable energy. As a first step, a general concept is that a 

way to drive change in a system is to expose it to an 

environment in such a way that interactions with the 

environment drive the system in the desired direction (10).

With regard to energy system changes at a smaller scale, 

there are well-established public policy mechanisms that can 

be used to create an environment that promotes movement 

toward a desired end state. However, these smaller scale 

changes deal with linear, noncomplex systems, and are not 

likely to be effective with larger issues; thus, a new 

approach for changing the environment is needed.

4.3 Innovation

Innovation has the potential to change the environment, 

which in turn can push desired change. In a consumer 

product setting where innovation provides new capabilities, 

the changes can be transformative; the obvious example in 

recent decades is with personal computers and other 

consumer electronics, which have literally changed the 

world in countless ways. The question now becomes how to

address the needed steps in a nonlinear, complex

environment. As a starting point, examining the 

relationships between sustainability, the energy system (at 

various levels), and innovation is helpful. Figure 3

illustrates these relationships.

Sustainability constrains innovation because it limits what is 

acceptable; for example, burning certain hazardous wastes 

might be the most efficient method for destroying them, but 

the release of byproducts to the environment could be 

unacceptable. Innovation enables change by providing new 

technologies and methods for generating energy or reducing 

energy waste. The energy system impacts sustainability 

because utility-scale energy production is a large industrial 

process (even renewable energy production), and such large 

processes inevitably have some environmental impacts. All 

of these elements operate within an overarching framework 

of societal maturity. Of the three connecting linkages, only 

innovation drives improvement; the others constrain or 

impact. Thus, it is worthwhile to explore how to leverage 

innovation.

Fig. 3. The Environment of Complex Change

Innovation is typically associated with technological 

advancement, but in this instance it is appropriate to define 

innovation more broadly. Referring again to the concepts of 

an energy mega-system and the environment that surrounds 

it, there is a need for extensive innovation in the 

nontechnical elements if there is to be any hope of seriously 

changing the status quo. The scenario analyses referenced 

above typically contain many caveats about these 

nontechnical factors, and because the nontechnical factors 

often cannot be reduced into easily addressed elements, the 

focus on innovative solutions often stays on the technical 

elements that can be defined and addressed.

An example of a proposed nontechnical innovation is the 

concept of regional innovation investment boards that would 

support demonstration projects and early adoption programs 

for alternative energy. These boards would be chartered by a 

federal agency, funded through electricity surcharges, and 

be structured to deal with the unique issues of each region 

rather than taking a uniform national approach. The goal of 

setting up such boards would be to deal with the middle 

activities between initial technology development and largescale deployment; this middle area is often referred to as the 

“valley of death” (11).

The analyses show that many such innovative ideas will 

need to be proposed and implemented to change the status 

quo. However, each action will be resisted, for the reasons 

noted above. History suggests that, at the macro scale, this 

situation will likely change only in response to a major 

crisis such as a climate disaster, an energy shortage driven 
5

by growing demand, or a supply interruption caused by war.

However, this is certainly not a preferable way to move 

forward, so a mechanism is needed to enable major changes 

without a driving crisis.

4.4 Knowable Drivers

A new approach is needed that builds awareness of 

knowable drivers to prepare for and capitalize on knowable 

events, and that builds resilience and foresight for 

responding to unknowable future crises and opportunities.

These knowable drivers include global population growth, 

pollution of all types, and resource imbalances. These must 

operate within an environment of growing societal maturity.

It can be argued that as a global society has developed in 

areas such as commerce and academics, the structures of 

governments and the viewpoints held by other key decisionmakers and the constituents they represent remain in the 

narrow and myopic realms that developed in an earlier and 

far different time. Only by developing viewpoints that are

inclusive of societal goals at some level—even if they are 

not initially global—can awareness of drivers be leveraged 

into actions that shape the future.

Unfortunately, there are no instant solutions to the 

challenges posed by societal maturity. Change will likely be 

a slow process, perhaps accelerated only by some crisis.

However, the development of tools designed to deal with 

change in the new, complex global environment may help 

spur the emergence of resourceful viewpoints and societal 

structures.

5. EXPLORING OUR ANALYTICAL TOOL KIT

Understanding the approaches used in the past to analyze 

these issues—and their strengths and limitations—may help 

us identify useful tools for responding to the emerging 

needs of the energy system. We group these approaches into 

four broad categories: linear causality, circular causality, 

complexity, and reflexivity (10).

5.1 Linear Causality

As noted earlier, linear roadmapping, forecasting, and many 

decision-making approaches fall short in analyzing the 

complex global energy system. Linear analytical tools 

identify short-term implications of policy or investment 

decisions. In stable situations, relatively bounded in space or 

time, they can also be useful for extrapolating longer term 

forecasts from past trends. When the territory stays the 

same, roadmaps based on prior experience can be useful

predictive tools.

Linear analyses of energy systems provide straightforward 

explanations that are easily quantified, explained, and 

grasped. However, the clarity of explanations can blind 

decision-makers to other equally defensible descriptions of 

system effects. Simple analyses disregard the effects of 

other key drivers, longer term system feedback loops, and

interactions with other systems. Outside the implicit 

boundaries of a linear model, for example, could be an

analysis of the economic benefits of a coal power generation 

plan—its effects could be equally provable as a driver of 

ecological degradation or of cultural disruption.

5.2 Circular Causality

Although linear models effectively predict short-term 

effects, in the real world, there is always a long term. More 

sophisticated models, including circular causality, add in 

feedback loops and self-reinforcing cycles to account for

longer term interactions. Tools such as system dynamics 

modeling provide insight into longer term, more widely 

distributed impacts of policy or investment decisions. These

help decision-makers understand linkages between remotely 

related system elements. Circular models can, for example,

consider a power plant’s further influence on economic 

development, population growth, and increased power 

demand.

As circular models expand, their discrete predictive 

capability declines, frustrating decision-makers who seek 

definitive answers. These models are most useful for 

understanding essentially closed systems with limited 

numbers of known players, systems where major system 

drivers are controllable from within the system, and systems 

whose dynamics are not impacted from outside their

boundaries. Even when analyzing more open, less 

predictable systems, decision-makers gain some level of 

comfort and guidance from the insights provided by these 

tools.

When adding in the complications of circular causality and 

feedback loops, the increasingly complex interactions 

between multiple system elements can render analysis of 

key drivers, at best, situationally dependent and, at worst, 

misleading. Trying to predict the effect of a particular action 

using circular analysis delivers first hopefulness, as the 

more sophisticated analysis yields new insights and a sense

that a decision’s effects can be predicted. Ultimately, 

however, that hopefulness turns to frustration as 

unanticipated longer term implications and the model’s 

shortcomings become apparent.
6

5.3 Complexity

The relatively new area of complex systems theory holds 

promise for helping decision-makers develop new 

viewpoints. It enables simulation of interacting systems and

provides useful descriptions of emergent system properties,

competition between systems, and characteristics of highly 

interrelated systems. These models provide insight into selforganization, the emergence of new variety, and natural 

selection within a system.

Complexity shifts the focus from transactions to 

relationships and shows how relationships between agents 

and with system structure influence system outcomes.

Understanding the effect of system structure on system

behavior provides important insights into the effects of 

policy or regulation.

Complexity theory provides insights into globally 

interconnected energy systems and highlights the limitations

of models to discretely predict impacts. This essential 

uncertainty is counterbalanced by the richness of insight 

into the dynamics of changes and the impacts of policy, 

regulation, and sustainability constraints. This assures

decision-makers that the most foreseeable impacts have 

been considered, even if their exact effects cannot be 

predicted.

5.4 Reflexivity

The newest tools come from the field of reflexivity theory,

which considers the unique characteristics of systems with 

thinking participants. Reflexivity draws distinctions 

between human systems and natural systems. Two key 

elements of human systems are fallibility and reflexivity.

Fallibility describes the partial or distorted world views of 

any participants in a system. Reflexivity describes how 

these distorted views can influence the situation to which 

they relate, as distorted views lead to inappropriate actions.

Reflexivity describes the feedback loops in which 

participants’ views influence the course of events, and the 

course of events influences the participants’ views as a 

continuous and circular feedback loop. (12)

Reflexivity offers a vantage point for rethinking and 

developing new viewpoints that are more in sync with 

changing global energy systems. As it seeks to include

decision-makers within the system model, it integrates the 

roles of decision-makers as model constructors and system 

participants, as well as observers. It acknowledges that each 

model is a reflection of the modelers’ thinking or the 

decision-makers’ viewpoints and reflexive of their positions

within the modeled system. Reflexivity extends the full 

circular effects of other models by considering how the 

perspectives, beliefs, assumptions, and actions of decisionmakers are affected by system constraints and how they, in 

turn, affect system outcomes.

Reflexivity describes the emergence of innovation as pivot 

points for nonlinear system shifts. Innovation in energy 

systems emerges in response to—and is limited by—

constraints. Reflexive, resilient entities in the system

innovate and adapt to protect self-interests and to exploit

emergent opportunities in the system. As entities innovate, 

they shift the dynamics of the embedded subsystems,

resulting in ripple or cascading nonlinear system changes—

those unpredictable sandpile avalanches.

Although not yet fully explored, reflexivity provides tools 

for describing the effects of entrenched system agents 

employing defensive strategies to protect market positions, 

building alliances to erect barriers to entry, or attack or 

swallow more resilient, adaptive, and innovative entities. 

Reflexivity enables not just the understanding of how 

systems adapt and change, but also how decision-makers, 

working within the system with real-time feedback, might 

adapt to influence the system toward desired ends.

The reflexive perspective may enable decision-makers to 

see how the assumptions behind their models may limit

their resilience. It can help them rethink their models to 

integrate emerging patterns and more agilely adapt to 

changes. Applied reflexively, tools such as iterated scenario 

planning use the construction of planning scenarios to 

explore potential new drivers of change and to develop

portraits of decision-makers’ thinking. Iterated scenario 

planning integrates real-time experience with the changing 

environment to developing more agile responsiveness and

resilience.

Other reflexive tools that extend perspectives and develop 

adaptive capabilities include open system and dialogic

methods such as appreciative inquiry. They enable entities 

and decision-makers from across systems to exchange key 

information about the nature of the system, facilitate selforganization of innovation networks and encourage 

development of higher order system goals of sustainability 

and energy security.

Reflexivity acknowledges that, in systems such as the global 

energy system, decision-makers are never disinterested 

observers and their learning always changes the system and 

its outcomes. It accepts the inability to discretely predict but 

builds on the human ability to grow, adapt, and innovate 

toward a new future.

CONCLUSION

Building on the broad agreement of the need to move 

toward more sustainable energy systems, leaders and 
7

decision-makers will continue to request more sophisticated 

theories, models, and tools to guide their plans. Although 

decision-makers want comfort and predictability, in a 

changing world, they most need the perspectives, skills, and 

tools for gaining insight into the dynamics of shifting 

systems. New tools enable them to explore complex

interactions of possible scenarios and to acknowledge that 

risk is a feature of the world. This cultivates rapid awareness 

and quick reaction time to unpredictable events.

In the complex and shifting world of global energy systems, 

modelers’ and planners’ roles must shift from attempting to

predict the unpredictable to helping decision-makers cope 

successfully with the uncertainties of a globally 

interconnected world. Planning and modeling become even 

more important tools for building resilience and agility to 

adapt to emerging challenges and seize opportunities within

emerging global energy systems.

ACKNOWLEDGMENT

This work was supported by the U.S. Department of Energy 

under Contract No. DE-AC36-08-G028308 with the 

National Renewable Energy Laboratory.

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Challenge for Systems Engineers: International Council of 

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Energy Statistics: downloaded and adapted 16 February 

2012

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vehicles: Energy Policy 36, Elsevier, 2008

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(5) Annual Energy Outlook 2012: Energy Information 

Administration, 2012

(6) Page, Scott, Understanding Complexity: The Teaching 

Company, 2009

(7) Houle, David, The Shift Age, Booksurge, 2007

(8) Ramo, Joshua Cooper, The Age of the Unthinkable:

Back Bay Books, 2009

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