About This Series

This blog is part of a series that explores how engineering approximations and simplified reasoning, while essential in daily practice, can slowly evolve into misleading engineering myths when their original assumptions are forgotten or ignored.

The series focuses primarily on solar PV systems and battery energy storage systems (BESS), where estimation methods are frequently reused beyond their intended scope. Over time, these shortcuts can influence expectations, proposals, and even system designs in ways that no longer reflect real-world behavior.

The goal is not to discourage approximation, but to clarify where it works, where it fails, and why context matters when reasoning about complex energy systems.

 

Disclaimer & Scope

This content is intended for educational and professional discussion purposes only.

To improve clarity, the explanations use simplified examples and conceptual reasoning. These are not a substitute for:

• Detailed system design
• Advanced modeling
• Manufacturer documentation
• Project-specific engineering analysis

Actual system performance depends on multiple factors, including environmental conditions, load behavior, equipment specifications, operational constraints, and design assumptions. Nothing in this article should be interpreted as a performance guarantee or a replacement for formal engineering processes.

 

Engineering Is Built on Approximation — and That’s Not a Flaw

Engineering is not the pursuit of perfect calculation.
It is the discipline of making reliable decisions under uncertainty.

To achieve this, engineers routinely rely on:

• Estimation
• Approximation
• Rules of thumb
• Simplified models
• Experience-based judgment

These tools are not weaknesses—they are necessities. Without them, no project would ever move beyond the drawing board.

However, approximation only works when it is:

• Based on valid physical principles
• Applied within known boundaries
• Treated as guidance, not certainty

When these conditions are respected, approximation is powerful.
When they are ignored, problems begin quietly.

 

The Proper Role of Estimation in Engineering Practice

In sound engineering workflows, estimation is used to:

• Narrow down design options
• Test feasibility
• Identify obvious mismatches
• Decide where deeper analysis is required

Estimation is a filter, not a final answer.

Even the simplest calculation carries assumptions—about time, behavior, conditions, and constraints. Professional judgment lies in knowing which assumptions are acceptable and which are not.

A fast calculation does not become correct simply because it is convenient or widely repeated.

 

When Approximation Turns Into Myth

The line is crossed when simplified logic escapes its original context.

In recent years—particularly in solar PV and battery storage—approximations originally meant for internal estimation have increasingly been used:

• In sales discussions
• In proposal justifications
• As implied performance guarantees

The math may look clean.
The explanation may sound intuitive.
The numbers may appear reasonable.

Yet the underlying reasoning is often:

• Incomplete
• Overgeneralized
• Detached from real operating conditions

At this point, approximation stops being a tool and starts becoming a myth.

 

Why Energy Systems Are Especially Vulnerable

Solar and battery systems are not static. They are:

• Time-dependent
• Weather-dependent
• Load-dependent
• Probabilistic in behavior

Small conceptual errors—especially around averages, timing, and recovery—do not fail immediately. Instead, systems may:

• Perform well under typical conditions
• Appear successful for most of the year
• Fail under stress, seasonal extremes, or prolonged demand

This delayed feedback makes flawed reasoning difficult to detect, allowing myths to persist unchecked.

 

The Compounding Effect in Developing Markets

In markets such as Pakistan, these issues are amplified by:

• Aggressive sales environments
• Limited client-side technical literacy
• Heavy reliance on verbal explanations
• Reuse of informal “design logic”

When simplified explanations are repeated often enough, they begin to:

• Replace proper understanding
• Influence younger engineers
• Normalize poor design reasoning

Over time, myths stop being questioned and start being taught.

 

What This Series Is — and Is Not

This series is not:

• A rejection of estimation methods
• A criticism of experience-based judgment
• An attack on practical engineering shortcuts

It is:

• A framework to separate valid approximation from harmful oversimplification
• An effort to reintroduce time, recovery, and worst-case thinking
• A call for clearer reasoning in how energy systems are discussed and designed

The goal is not to eliminate shortcuts—but to keep them anchored to reality.

 

How to Read the Articles That Follow

Each article in this series will:

• Examine a commonly repeated belief
• Explain why it sounds reasonable
• Show where it breaks down
• Offer a more robust way of thinking

The intent is understanding, not blame.

 

Closing Thought

Engineering shortcuts are powerful tools.
Engineering myths are liabilities.

The difference lies not in the math,
but in the assumptions we accept without questioning.

 

Frequently Asked Questions (FAQs)

 

What is an engineering approximation?

An engineering approximation is a simplified calculation or assumption used to make quick, practical decisions when exact data or models are unavailable. It helps engineers assess feasibility and direction, but it is not meant to replace detailed analysis.

 

Why are approximations commonly used in solar and battery systems?

Solar PV and battery energy storage systems involve many variables such as weather, load behavior, and time-based performance. Approximations help engineers estimate system size, costs, and feasibility during early planning stages.

 

When does an approximation become an engineering myth?

An approximation turns into a myth when it is reused outside its original context, treated as a guaranteed outcome, or repeated without revisiting its assumptions—especially in sales discussions or simplified proposals.

 

Why are energy systems more sensitive to incorrect assumptions?

Energy systems are dynamic and probabilistic. Small errors in assumptions about averages, timing, or recovery may not show immediate failure but can cause significant performance issues during peak demand or extreme conditions.

 

How do engineering myths affect system performance?

Engineering myths can lead to undersized systems, unrealistic expectations, poor reliability, and failures under stress conditions. They often surface only after long-term operation, making them costly to correct.

 

Why are these issues more common in developing markets?

Developing markets often face aggressive sales environments, limited technical literacy among clients, and reliance on verbal explanations. Over time, simplified logic becomes accepted practice instead of being questioned.

 

Does this series discourage estimation or rules of thumb?

No. The series supports estimation and practical shortcuts—but emphasizes that they must remain grounded in physical reality, clear assumptions, and proper engineering judgment.

 

How should engineers use approximations responsibly?

Approximations should be used as guidance tools to narrow options, test feasibility, and identify risks—while knowing when deeper analysis and system modeling are required.

 

Who should read this series?

This series is valuable for:

 

• Practicing engineers
• System designers
• Energy consultants
• Technical sales teams
• Engineering students and junior professionals

Anyone involved in energy system design or decision-making can benefit from understanding where simplifications help—and where they mislead.

 

What is the main takeaway from this series?

Engineering shortcuts are powerful when used correctly. The real risk lies not in simplification itself, but in accepting assumptions without questioning their limits.