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BLUEPRINT FOR CALIFORNIA'S
CLEAN ENERGY FUTURE
The Metrics of Energy Measurement
Michael
Theroux
July 2011
Introduction
The California Energy Commission
(CEC) Integrated Energy Policy Report (IEPR) Committee organized a workshop on July 6, 2011 to present a
proposed revision to the California Clean Energy Future (CCEF) planning process, a key element
of state energy planning. Joining the CEC in the
workshop and participating in the planning process were the "Collaborating Organizations", the Governor's
Office, the California Air Resources Board, California Environmental Protection Agency (CalEPA), California
Independent System Operator Corporation, and California Public Utilities Commission.
According to the Workshop
notice, the agencies were looking for "… feedback on how to measure progress in meeting the policies identified in
the California Clean Energy Future Overview document and on how to execute the policies and track progress in a
transparent and effective way." Comments on this stage of the process were due to the CEC's Dockets Office on July
20, 2011 (Docket #11-IEP-1A). We submitted formal comments to the CEC docket, primarily to address the overall vision and
organization of interagency measurement, and questioning the precepts that lead to the chosen
metrics.
This article includes sufficient
background and document detail to provide context for our formal comments, which have been posted to Teru Talk's
"Reference" section. Our comments and article are intended to aid California in establishing a new conceptual
framework for energy assessment, to help improve over-all monitoring of all aspects of energy supply and delivery,
and hopefully to initiate a more realistic and flexible implementation of management programs to reach the State's
very aggressive Clean Energy goals.
Background
The original Overview for the
California Clean Energy Future was developed upon the foundation of California's "Loading Order" policy adopted
with the 2003 Energy Action Plan, which placed Energy Efficiency and Demand
Response as the top priority. Renewable Energy held second rank, followed by Combined Heat and Power (CHP) and
Distributed Generation (DG). Beyond these, the Loading Order specified use of the "cleanest and most efficient
conventional generation".
The CEC adopted an Integrated
Energy Policy Report (IEPR) in 2003 and fully revised the vision every two years pursuant to Public Resources Code
§ 25301[a]. On March 24, 2010, the CEC adopted an Order Instituting Informational Proceeding (IEPR Docket
#11-IEP-1A) to
develop the 2011 IEPR.
California's then Governor
Schwarzenegger established difficult "clean energy" goals as outlined in the 2010 Clean Energy Future Overview, Implementation Plan and Roadmap. With
the change in regime, our agencies now must revise these goals to reflect Governor Brown’s energy vision. Two
crucial statements of his vision have been made public.
First, California was presented
with a key campaign platform prior to Governor Brown's election. The prospective Governor's Clean Energy Jobs Plan details specific steps to dramatically improve
the state economy by implementing Clean Energy. His Jobs Plan summarizes:
"By 2020, California
should produce 20,000 new megawatts (MW) of renewable electricity, and also accelerate the development of energy
storage capacity. California can do this by aggressively developing renewables at all levels: small, onsite
residential and business systems; intermediate-sized energy systems close to existing consumer loads and
transmission lines; and large scale wind, solar and geothermal energy systems. At the same time, California should
take bold steps to increase energy efficiency."
Second and as proposed in his
Clean Energy Jobs Plan, the legislature passed and Governor Brown signed SB x1- 2, the California Renewable Energy Resources Act. The
legislation now obligates all California electricity providers (both investor and publicly owned) to obtain at
least 33% of their energy from renewable resources by the year 2020, the most aggressive renewable portfolio
standard in the country.
Revisions to the CCEF under the
current mandate of this year's Scoping Order must now incorporate original thought, quick action and
aggressive pursuit. Three major areas of change to the prior IEPR planned for 2011 have now been
ordered:
(1) Address
Governor Brown's energy policy priorities regarding the Loading Order, following the outline in his Jobs Plan and
the mandate of SB x1-2;
(2) Consider
the safety and energy reliability implications of the PG&E gas pipeline explosions on September 9, 2010,
considerations that must internalize the human and environmental costs of an aging infrastructure and of all
energy transmission, and
(3) Review and
evaluate use of public funds for energy, including renewable energy technologies and public interest energy
research, under provision of the Public Goods Charge and related program funding.
The revised 2011 IEPR will be a
set of inter-related topical documents, expected to be published from July through September 2011. Topics announced
at this time include: (a) Energy Efficiency, (b) Renewable Generation Infrastructure in California, (c) Review of
Public Goods Charge and Energy Research, Development and Demonstration Programs, (d) Bioenergy Development in
California, (e) Transportation Fuel Supply, Demand and Infrastructure, and (f) Electric and Natural Gas Supply,
Demand and Infrastructure.
According to the 2011 Integrated
Energy Policy Report web page and accompanying schedule, a Summary of major findings and
policy recommendations from the subsidiary volumes will be presented by staff and proposed for adoption by the
Energy Commission during the last two months of 2011.
2011 Revision of the CCEF – Metrics of
Measurement
The July 6th workshop
concentrated on the changes proposed to the CCEF as part of the broader 2011 IEPR process. As outlined in the
Overview, the CCEF Implementation Plan and Inter-Agency Roadmap both rely on metrics of measurement by which the
agencies of purview over state energy planning might properly judge relative progress toward the mandated 33%
goal.
Eleven specific energy
measurement metrics that had been previously posted to the IEPR web page were
described and considered for their overall thoroughness, organization, efficacy in tracking, and as needed to
adjust the course of implementation:
(1) Demand Response refers to a reduction in customers’ electricity
consumption over a given time.
(2) The Zero Emissions Vehicle program will play a critical role in
meeting California’s air quality and greenhouse gas reduction goals for 2020 and beyond.
(3) The 2020 forecast of greenhouse gas (GHG) emissions is important for
tracking California’s progress towards the goal of reducing statewide emissions to 1990 levels by
2020.
(4) The current energy efficiency goals are based on historical savings
assumptions and state policies for achieving greenhouse reductions.
(5) On-line capacity metrics track available energy by technology and by
year from 2001 to 2010.
(6)
Phasing out once-through cooling (OTC) directs improvement in nuclear plant
efficiency.
(7) Renewable Energy generation data measure progress toward statewide RPS
targets.
(8)
Reserve Margins evaluate short-term market developments and a range of
potential system variations to determine if there are any significant risks of potential electricity supply
shortfalls during the upcoming peak demand season.
(9)
The system average rate is calculated by dividing the annual revenue
requirement of the IOUs by their annual retail sales.
(10) Statewide Energy Demand represents historical statewide annual
electricity consumption and end-use natural gas consumption data.
(11) Transmission expansion plays a vital role in enabling the
interconnection and operation of renewable energy to meet Renewables Portfolio Standards.
Agencies measure data associated
with actions that they have purview over and can in some way hope to manage. The presented Metrics are a result of
selecting key data sets and measurement programs associated with each of the Collaborating Organizations noted in
the Introduction to this article, the agencies and institutions most directly responsive to
and responsible for "energy" that have been and continue to be taking direct roles in the CCEF
revision.
Holistic Energy Management
Kicking off the July 6th
workshop, CalEPA Deputy Secretary Anthony Eggert offered the well-worn quote that "what you can't measure, you
can't manage", as an introduction to the overview of the California Clean Energy Future, and to the topic of
metrics assessment. Mr. Eggert asked that those attending consider if indeed the agencies were using the right
metrics of energy supply and demand measurement.
The corollary is also just as
true; the above conundrum can be restated: what you don't manage, you don't measure. To a large degree, what
is not counted does not count in the tally.
Prior to asking agency staff to
present on each of the proposed Metrics, workshop participants were also asked to consider if there might be
another way to organize the process that accounts for progress toward stated energy goals in
California.
We would offer that "Energy
Supply and Demand" must be viewed in its entirety, that the on-going revision of the CCEF is hampered by a very
non-holistic perspective. Clean Energy planning must include all controlling interests and if the State
is to so dramatically increase Renewable Energy, it stands to reason that the agencies with purview over all
aspects of renewable energy sources must be fully engaged. Not in evidence during the workshop were
representatives from agencies with purview over Agriculture, Forestry, Water and Waste. Renewable energy is only
one part, and the minor component, of California's energy past, present and desired future.
Realistically, measurement and
management of "clean energy" requires that they be done in context of all energy, clean and "dirty". As
one example, Chair Weisenmiller observed during the workshop that understanding and measuring California's use of
coal for power is necessary if we wish to observe and encourage the decline of that usage. Measurement
of each energy pathway from source to end-user is similarly important.
The Value Chain Approach
Agency staff provided the
workshop with the process of metrics selection and organization. Ms. Heather Raitt, Assistant Executive Director on
Climate Change, presented four key organizational categories: (a) Demand, (b) Supply, (c) Transmission, and (d) a
catch-all component, "additional supporting processes".
We submit these concepts are
inherent characteristics of the value chain of energy supply rather than a primary organizational
structure. It is useful to revisit each of these concepts:
Demand is draw upon the end of a supply chain. Much
of our governance over energy has been focused on modifying demand, through imposed restrictions and quotas to
offering temporary incentives and policy preferences. Yet "demand" becomes less manageable for example, when we
consider on-site generation and distributed combined heat and power. Who will measure and manage this
element, using what combination of the metrics chosen? Demand is best understood as the result of all factors
acting upon an Output. Without clearly accounting for the pathway leading to that output, it is probably
unrealistic to expect effective management of Demand, as the controls occur all along that pathway, not simply at
the end.
Supply as described in the IEPR program documents
has been too narrowly defined. In context of an end-to-end value proposition, supply must encompass
everything from the origination of resources which eventually are converted to energy, and not simply the last step
of provision to the end-user. Here, we find total lack of representation of purview over those sources that
contribute to so many "pathways". One obvious example would be the long-standing assessment of biomass as a
renewable feedstock. Where is this accounting and management represented in the current Metrics
consideration?
Transmission most aptly describes the paths of the
products of the value chain from generation to end-user. Controls over transmission are naturally of high priority
for agencies with specific purview over only the final pipe and wire infrastructure required for delivery of energy
products. While there is obviously a need to insure that transmission has sufficient capacity for present and
future conveyance needs, there is a hazard inherent in assigning too much weight to end-point controls. There is
also a need to consider how implementation of "smart grids" and on-site generation will complicate understanding of
transmission.
Additional Supporting
Processes as outlined in the Overview constitute a mixed accumulation
of physical systems and managerial methods. Rather, we might define a Process category as that combination
of systems and methods present at any point along the value chain that effect conversion from one raw form of a
resource into another more accessible and beneficial form. It appears that all other components currently assigned
to this catch-all category might then be more appropriately considered as "modifiers" along the value
chain.
Any commodity assessment must
take into account the source, the process, and the output. Each step along a pathway from raw source to end-user
inherently must accrue value (if no more than access) at each step. Step-wise value-added processing turns a
resource into a commodity, and this perspective is certainly appropriate for all provision and use of Energy. A
value-chain approach to energy monitoring and management logically takes into account the local, state and federal
policy-driven regulatory framework that impacts this value-added process. Public or private, market or policy
driven, each value-chain exhibits certain characteristics and is subject to certain controls.
Establishing metrics of
measurement logically should extend to the existing and needed mechanisms necessary to identify the broadest
cross-section of energy generation. The data necessary for tracking the flux of coal, natural gas, crude petroleum,
biomass, water, geothermal resources, solar irradiation, microbial, and radioactive feedstock and any other
potential resource from which energy might be generated for an end-user thus falls within scope of the
metrics of energy measurement. Energy-provision benefits, barriers, challenges and inequities become apparent once
in context; monitoring impact / response of policy and regulation upon this flux must be
considered.
Plotting out the vision,
implementation schedule, and "roadmap" of California's energy future assumes that management can be effectively
informed by proper and thorough monitoring and that research, development, commercialization, and governance may be
positively used to direct growth toward the desired outcome. That quantifiable outcome, whatever it might be, must
be viewed as the result of the processes that add (or subtract) value along the path from resource to commodity,
impacts upon value that signal to the market desired direction and rate of growth.
Modeling the Energy Value Chain
A simple Input/Output (I/O)
organizational model may best provide a foundation for truly identifying, monitoring and understanding the flux of
California's overall energy value chain. I/O modeling organizes all components of and controls upon the progress
from source to end-user. For energy, the CCEF I/O model starts with an agreed upon suite of mutually beneficial
socio-economic outcomes, one goal of which is to adjust the energy generation and provision balance to attain a
portfolio of 33% renewable energy by 2020.
An inclusive and responsive I/O
model construction for Energy must pay close attention to the process by which the myriad resource
Inputs become commodity Output. It is with the step-wise identification, characterization and management of
process that the I/O model most provides access to critical "inflection points", places where the least
management can result in the most optimal result. We can think of our model as an Input-Process-Output (IPO model)
framework.
Accounting for all elements of
an energy value chain must be a "live" program, always open to additions, deletions, revisions, and refinements as
conditions change. Input, Processes and Outputs need attributes, the characteristics that differentiate it from
other similar elements.
Modeling also requires an
approach that consistently excludes any judgment of worth of the element added until the element may be adequately
viewed in context of the whole. Any a priori value attributed to individual elements tends to defeat the goal of
creating a model representative of the energy system's inherent diversity, resilience and rate of change.
Determination of value is a product of the model, not an element-selection criterion.
Input-Process-Output Model
Input to the energy value chain includes a broad
range of feedstock types, some inherently containing more contaminants or environmental toxins than others. Yet it
is not the feedstock that solely determines whether energy generated will be clean or dirty, it is the entire chain
of acquisition, transport, processing, delivery and even specific pattern of usage that determines socio-economic
and environmental "friendliness".
A quick list of "energy inputs"
might include but certainly would not be restricted to solar, water (hydropower), geothermal, biomass, waste
(including waste heat recovery), fossil-based sources and nuclear reactivity. The category list must be left open;
already, new science has been indicating that energy may be scavenged simply from the motion always present in our
environment.
Input attributes would describe
agencies of purview and the policies, rules, regulations and laws pertinent to a particular energy feedstock
component. As an example, there are many different local, state and federal agencies that impact "biomass"; some
impacts are feedstock type and source specific, others are more generic. Having diverse types of biomass slotted as
Input provides a way to sort out the controls over each type, group of types, and category of groups. For biomass
in particular, we needn't "start from scratch"; the meticulous work of the California Biomass Collaborative under
direction of the "re-invigorated" Interagency Bioenergy Working Group has certainly provided an accounting of
types, sources and quantities. The management of this data has not represented in the current Metrics under
consideration.
Similar data sets define, with
widely varying levels of accuracy and thoroughness, a broad array of Input types to the California Energy value
chain. The task of placement within a matrix becomes one of linkages to existing data sources and purviews, and
identification where such sources and purviews are absent or unsatisfactory for an identified
type.
In one difficult example,
California has recently had the misfortune to see that a system input of "clean" natural gas still can constitute a
disastrous public hazard in a poorly maintained infrastructure. "Coal" as an input feedstock type may be clean or
dirty depending not so much on the chemical characteristics of the feedstock, as on the characteristics of
conversion Process; old coal-fired energy generation is far dirtier than our newest "clean coal" technologies. The
feedstock type should be represented in the model whether one is pre-disposed to shun or support the inclusion of
coal.
Process describes the stepwise progression from the
raw Input to creation of the final commodity as an Output. Accounting for Process in the IPO model starts with
acquisition and aggregation, proceeds through transport and certainly includes all forms of refining and reforming,
whatever the feedstock. Barriers and controls that rely on methodical data collection mechanisms have been
institutionalized upon Process along this entire pathway; each factor impinging for good or bad upon the Process
exists as a "adjustable" variable that may be increased or decreased to effect a shift toward overall goals. To do
so, however, these attributed must be identified and associated with the specific steps of value chains that they
impact.
As an example, the prescriptive
controls over percentages of "renewable" versus "fossil" input to a Process might be better observed and
potentially modified in context of the inclusive IPO model. Transport, fuel refining, and chemical production are
globally trending toward use of less fossil and more bio-sourced feedstock, yet this has less to do with any policy
or regulatory dictum than the economics of availability. To paraphrase a colleague in the oil and gas industry:
'Hydrocarbons is where you find 'em'. The recent and on-going Definition of Solid Waste rulemakings, for example, take this into
account.
Presumptions of the degrees of
"cleanliness" based on Input can only confuse an understanding of processing types. Using a matrix approach
encourages assigning value after inclusion, rather than assuming attributes and therefore precluding the proper
placement within the whole. There may well be processes that simply should not be allowed to be part of
California's energy future, yet that determination should depend upon the context of "clean, compared to
what?"
To monitor and manage a change
in Process that can decrease or increase the effective value to be accrued along the value chain from an input to
the output, we must account for and measure the types of Processes, and objectively assign attributes of operations
maintenance, constraints, and limitations. Identification of Best Management Practices (BMPs) can be one result of
such an incremental assessment. In truth, any system may be operated well, or operated poorly; an
emphasis on Best Management Practices regardless of the type of conversion mechanism used for processing is
probably more likely to provide the desired "clean energy" result.
Output elements of the energy model include all
products of energy as a commodity, whether kinetic such as drive shaft power, thermal in terms of heating and
cooling, electrical as direct and indirect current, or chemical as where that commodity is used for fuel. At
present, most of the CCEF-listed Metrics involve measurement of attributes of commodities in this Output category,
such as usage data and resulting controls over Demand Response constructs. Without question, the growth of
zero-emissions vehicles (ZEVs) in the transport sector is important. Perhaps of more value however would be a
better understanding of and accounting for each step in the value chain that results in user-access to Output
energy commodities critical for those ZEVs to more rapidly penetrate the marketplace. Assessing ZEV numbers without
reliable access to the rest of the associated value chain's data certainly must result in skewed analyses of the
"manageable" characteristics of that value chain, with minimal utility for effecting the desired
change.
Creating a "level playing field"
among controls over energy Outputs is envisioned as a desired result of the CCEF revision. In absence of a matrix
describing the life-cycle assessment characteristics of energy in context, it is difficult if not impossible to
compare well-to-pump impacts of petroleum Inputs with other pathways. California's development of a Low Carbon Fuel
Standard is attempting to construct just such a comparative matrix; extension of this model beyond transport fuels
to include all energy would be worth serious consideration.
Output attributes are typically
considered when selecting mechanisms to encourage or discourage specific patterns of energy usage. Energy agencies
contributing their methods of monitoring clean energy governance efficacy will naturally feel more comfortable if
not tasked with monitoring what they do not have the purview to manage. In such instances, the expertise of other
governing and oversight parties not so directly charged with the end-user supply and demand flux must be engaged to
fully grasp the controlling attributes of each energy output.
A matrix approach that reserves
judgment and simply accounts for all outputs appears warranted. One need not initially know the
activities, impacts, controls and benefits along a particular Process, to recognize an identified Output. The
Output of all energy commodities should be identified and methodically assigned pertinent characteristics that in
their turn can be measured and compared to the CCEF goals according to consistent and comparable
criteria.
Energy output delivery is no
different than any other commodity; the ability to safely and cost-effectively reach the Market determines and is
determined by the entire value chain.
Conclusion and Recommendations
As presented in our formal comments to
Docket
Two closely related
organizational concepts are offered to improve understanding of energy generation and delivery in California.
First, we suggest that provision of energy constitutes an inter-related complex of value chains, of
identifiable pathways from source to end-user. Second, we offer an Input-Process-Output model by which all forms of
energy value chains may be identified, measured, and compared.
Agencies measure what they
manage or intend to manage. For example, access to feedstock is critical to the energy value chain for nearly all
sectors, but impacts to feedstock availability, whether positive or negative, tend not be considered because they
are not strictly within the purview of "energy management." A cohesive state-wide energy policy must take into
account access and availability from source to end-user.
Rather than consider efficacy
against a set of performance standards of what constitutes "clean" versus "dirty," judgments are made in advance,
and entire sectors of potential energy provision are disparaged. Coal is not inherently dirty; it is the
industry-standard Process that converts coal to energy that has been the problem. Waste pollutes less when
carefully controlled through an advanced conversion Process than when left to common management ending in landfill
disposal. Any processing system can be run well or poorly, and it is the Process performance and
specific use of Output rather than the Input feedstock source that should dictate considerations of environmental
cleanliness.
We are recommending an inclusive
method facilitating direct comparison of the energy value chain of the status quo vs. that of the proposed
Process. The question, "Clean, compared to what?" needs to be answered. Using
existing Process as the baseline for comparison establishes the basis for informed management leading to
identification of Clean Energy.
We are
not recommending that agency governance incorporate every aspect of each energy value chain. Indeed, in
most cases, less governance would be preferred. We feel that more good will be accomplished by
identifying and eliminating regulatory inequities than could be accomplished by more regulations, grants, loans or
incentives.
We appreciate and do not
underestimate the enormity of the task at hand to order all forms of energy provision to our state. Yet we also see
that much of the data are already being managed, that the task is more about inclusion of these
disparate management regimes than of wholly new constructs.
Data management for extremely
complex and constantly changing conditions must be based on a holistic and inclusive initial identification of
elements, followed by a rational placement of each in context of the other elements. This "database" approach is
already a well-developed field of inquiry; its application to policy-laden purview decision-making may only
recently have become possible. Society is no longer constrained by the sheer scale of the requisite data storage,
organization, extraction, analysis and constant maintenance. The data can be gathered, but there are often far more
subtle reasons for not doing so than simply data storage capacity.
If California is to implement
the rapid increase in development of renewable energy as mandated, we must at a minimum identify every
possible pathway. Once positioned in context of other pathways in the overall energy value chain, we can
methodically enumerate attributes, among which will be that part of the spectrum of social, environmental and
economic appropriateness we tend to collectively call "Clean Energy".
© Teru Talk by JDMT, Inc 2011. All rights
reserved.
You are free to reprint and use this article as long as no
changes are made to its content or references and credit is given to the author, Michael Theroux.
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