HP March 2022 eBook—Energy Transition - 64

Refining Technology
Additionally, since an entire fleet can be on one platform, individual
fleet performance can be easily rolled to corporate level
key performance indicators (KPIs) that can be tracked over the
period. Having such KPIs helps the corporation to develop a
strategy around its energy performance.
Fleet performance presented on one visualization platform
also acts as a " social proof " and psychologically motivates people
to match the best demonstrated behavior. The concept of
social proof is widely discussed in psychology. Cialdini5
coined
the term to represent a phenomenon wherein people copy the
actions of others to undertake behavior in a given situation. A
classic example of decreasing household energy use would be to
not only provide the individual's electric consumption but also
the electricity consumed by the neighbors.
Providing a common platform for sharing data will promote
a healthy competitive environment and motivate all to make energy
efficiency improvements.
TOOL DEVELOPMENT
The entire fleet development work process can be broken
down into eight major steps, as shown in FIG. 1. The entire work
process begins with the identification of the critical energy fleet
population, followed by the development of a technical functional
specification that acts as a backbone for the entire tool
development process. This considers defining key energy performance
indicators, establishing calculation methodologies,
target setting and energy gap calculations.
Once tool mechanics are developed, it is important to arrange
the millions of data points generated by the tool into visuFiring
duty
als for easier interpretation. The last and most critical step in
achieving success is to gain the trust of business partners and
embed the tool into normal work processes. This sets up the
tool for long-term success.
Identification. Configuring thousands of pieces of equipment
into the fleet tool is resource intensive. So, for every fleet family,
it is important to identify the critical fleet population based on
the Pareto Principal.6
It is often a good idea to assign a priority
for every piece of equipment to maintain a right balance between
the upfront resource required and the benefits obtained
by monitoring. This approach (FIG. 2) enables an organization
to focus on the critical equipment first, followed by low-priority
equipment when more resources are available.
One simplified approach to define priority is to sort the fleet
in the descending order of energy consumption. A threshold
energy consumption allows the identification of high-priority
items that must be configured during an initial rollout. Minor
modifications to the list are often needed depending upon
equipment criticality from the process unit perspective. For example,
smaller furnaces like the naphtha hydrotreater feed furnace
may not be qualified based on the threshold value; however,
depending on its criticality in a process unit or a site, an
owner-operator may want to include it in the initial rollout.
Define KPI. This step includes the development of the technical
approach defining KPIs, universally consistent estimation
methodologies and target setting.
KPIs can vary depending on the family of fleet. For example,
energy efficiency can serve as a KPI for equipment like furnaces,
boilers and gas turbines. Different KPIs, such as thermodynamic
efficiency for compressors or potential power that can be
generated through steam letdown, etc., can be developed.
Once KPIs are determined, it is important to establish globHigh
priority
Low priority
Number of furnaces
FIG. 2. Determining initial fleet population.
ally consistent methodologies to estimate the same, and to find
a balance between accuracy vs. complexity of the techniques to
quantify the KPI. Methods that are too complex and more accurate
are usually resource intensive, as they require numerous
process inputs and make the tool more complicated. Often, a
literature survey or in-house research can provide such consistent
techniques. For example, furnace efficiency for gas-fired
furnaces can be estimated based on stack conditions, such as
oxygen concentration and temperature7
η = 99 - (0.001123 + 0.0216 EA) / (Tstack
)
and Ta
ambient temperature in °F
O2stack = Excess oxygen measured at stack in dry mol%
FIG. 3. Typical variability of performance parameters and how
improvement is made.
Target setting. The historical performance of the fleet in
terms of KPI is valuable information in defining targets. Normally,
KPI variability follows the normal variation with the
fleet being operated at its best performance at least 10% of the
time. A typical variability is shown on the upper left hand of
FIG. 3. Minimizing the variation is the first step in improving
performance, followed by pushing the mean value closer to a
Hydrocarbon Processing | SEPTEMBER 2021 | HydrocarbonProcessing.com
(Eqs. 1 and 2):
)
- Ta
EA = (0.98 × 21) / (21- O2stack
where
Tstack
(1)
(2)
= Flue gas temperature measured at stack and
Firing duty
Cumultative
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HP March 2022 eBook—Energy Transition

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