⚡ Inertia-Aware Operation in a Decarbonizing Power System

Why future power grids must plan for inertia—and pay for it properly.

As renewable energy grows, the grid changes in a fundamental way:

✔ Conventional generators (coal, gas, nuclear) → going offline

✔ Inverter-based renewables (PV, wind) → rapid increase

But there’s a hidden side effect:

We are losing the system inertia that keeps the grid stable.

When inertia is low:

Frequency drops faster after a disturbance
RoCoF (rate-of-change-of-frequency) becomes dangerously high
Load-shedding and protection systems may fail
The grid becomes more fragile

This study develops a framework that helps operators secure enough inertia and
design fair market payments for resources that provide it. :contentReference[oaicite:0]{index="0"}

🧠 What Is Inertia, and Why Does It Matter?

Synchronous generators naturally resist sudden frequency changes because they have spinning mass.

Inverter-based generators (PV/wind) do not spin, so they provide little or no inertia unless specifically controlled.

If inertia is too low:

Frequency drops deeper (worse frequency nadir)
It drops faster (higher RoCoF)
Recovery becomes harder

A stable grid requires minimum inertia levels at all times.

🔍 Why Unit Commitment Must Include Inertia

Figure 1. The representation of an electric power system showing tight coupling of synchronous generators and smart variation renewable energy systems.(Image source: NREL)

Traditionally, Unit Commitment (UC) decides:

which generators should run
how much they should generate
how reserves are scheduled

But UC did not consider inertia.

So as renewables increase:

cheaper generators turn off
but turning them off also removes inertia
risk of frequency collapse increases

This paper proposes:

Inertia-aware UC (IA-UC): Co-optimize energy, reserves, and inertia together.

Meaning:

Keep enough synchronous machines online
Use storage & renewable deloading to provide virtual inertia
Respect uncertainty in PV & wind

This allows operators to meet inertia requirements with fewer generators and lower cost.

🧩 Market Challenge: How Should We Pay for Inertia?

In energy markets today:

Energy is paid through LMP
Reserves are paid through reserve prices
But inertia has no standardized price

Different system operators use:

Region	How They Secure Inertia
ERCOT	Reliability-Must-Run (contracts)
CAISO	Minimum-online-commitment + uplift
NESO	Stability market
EirGrid	Long-term inertia contracts

But these methods:

distort energy markets
require large uplift payments
give unclear investment signals

This paper compares 4 remuneration methods for inertia:

Marginal Pricing (MP)
Uplift
Approximate Convex Hull Pricing (aCHP)
Average Incremental Pricing (AIP)

🔧 How the Proposed Framework Works (Simple Explanation)

The model extends chance-constrained UC to:

handle uncertainty in PV/wind generation
handle uncertainty in renewable-provided inertia
enforce system-wide minimum inertia in every hour
allow ESS to provide inertia
determine costs & payments for inertia provision

The framework evaluates both operations and economics, not just physics.

🧮 Expert Snapshot: Representative IA-UC Optimization Formulation

Below is a compact optimization model capturing the core structure of the paper’s inertia-aware chance-constrained UC (IA-CCUC).

Objective

Minimize expected cost under renewable uncertainty:

Constraints

1) Unit commitment logic

Up/down-time constraints apply to (u_{i,t}).

2) Ramping limits

3) Generator capacity with chance constraint

4) ESS power & energy limits (chance-constrained)

5) DC power flow constraints

7) System inertia adequacy (chance-constrained)

📈 Results: IEEE 118-Bus System

✔ Inertia-aware UC dramatically improves stability

Figure 2. System inertia levels with and without inertia-aware scheduling.

Without inertia constraints:

Off-peak hours fall below the requirement
System becomes vulnerable to disturbances

With IA-UC:

All hours satisfy inertia limits
And fewer generators are needed than in “RMR-style” operation

✔ Frequency response improves significantly

A generator outage causes frequency to dip.
With IA-UC:

Frequency nadir improves by 0.13%
RoCoF improves by ~50%

Meaning the grid becomes much safer.

Figure 3. Faster and safer frequency response with inertia-aware UC.

✔ Commitment decisions become more efficient

Instead of forcing many expensive units online (as RMR does),
IA-UC selectively chooses just enough generators to meet inertia needs.

This reduces cost while maintaining stability.

💰 Which Remuneration Method Works Best?

The model compares MP, aCHP, AIP, and uplift.

✔ Marginal Pricing (MP)

Inertia price is often zero
Provides no investment signal
Requires large uplift payments

✔ Uplift

Ensures cost recovery
But offers no meaningful price signal for planning

✔ Average Incremental Pricing (AIP)

Embeds fixed/start-up costs into prices
Provides better compensation than MP
But inertia price still too weak

⭐ Approximate Convex Hull Pricing (aCHP) — Best Performer

Produces strong, transparent inertia prices
Minimizes uplift
Ensures revenue adequacy
Encourages investment in inertia-capable units

aCHP consistently outperforms the others.

📘 Reference

Kim, HyunJoong, and Jip Kim. “Inertia-aware Unit Commitment and Remuneration Methods for Decarbonized Power System.” arXiv preprint arXiv:2412.10820 (2024). [link]

Inertia-Aware Unit Commitment and Remuneration in Decarbonized Power Systems