Module 10 — A New Approach to Market Design
Lesson 4 of 10
Network-Feasible Allocation
Learning objectives
By the end of this lesson you should be able to:
- Understand what is meant by a network-feasible allocation.
- Explain why electricity market outcomes must satisfy physical network constraints.
- Recognise the importance of considering network feasibility during allocation rather than afterwards.
- Appreciate the role of power system models in supporting physically feasible decisions.
- Understand why network-feasible allocation is an important component of integrated market design.
Introduction
Electricity markets determine who generates electricity, who consumes it and when energy is exchanged.
However, every market outcome must ultimately be delivered through a physical electricity network.
Transmission lines have thermal limits.
Distribution networks have voltage limits.
Transformers have capacity limits.
Generators and consumers have operating constraints.
Regardless of how attractive a market outcome may appear economically, it can only be implemented if it remains physically feasible.
This observation motivates the idea of network-feasible allocation.
Economic decisions and physical reality
Electricity markets operate in the economic domain.
Power systems operate in the physical domain.
These two domains are closely connected.
Every economic allocation corresponds to a physical pattern of power flows throughout the network.
If those flows exceed the capabilities of the network, the allocation cannot be implemented safely.
Market design must therefore respect both economic objectives and engineering constraints.
What is a network-feasible allocation?
A network-feasible allocation is an allocation that satisfies both:
- the market objectives, and
- the physical operating limits of the electricity system.
Rather than considering only supply and demand, allocation decisions also recognise constraints such as:
- line capacities,
- transformer ratings,
- voltage limits,
- generation limits,
- storage constraints,
- operational reserve requirements.
Only allocations that satisfy these constraints are accepted.
Feasibility as part of the allocation
One approach to market design is to determine an economic allocation and then adjust it if network problems arise.
An alternative approach is to consider network feasibility during the allocation itself.
In this case, every accepted request is evaluated against the current state of the network before it becomes part of the evolving market.
The allocation therefore remains physically feasible throughout the clearing process.
A simple example
Imagine two neighbouring communities connected by a transmission line.
One community has abundant renewable generation.
The other has high electricity demand.
Economically, transferring additional electricity may appear desirable.
However, if the transmission line has reached its operating limit, no further power can be transferred safely.
A network-feasible allocation recognises this limitation and only accepts additional requests that remain within the capability of the network.
The role of network models
Determining whether an allocation is feasible requires information about the electricity network.
Engineers use mathematical network models to estimate how power flows through the system.
Depending on the application, these models may consider:
- power flows,
- voltage levels,
- thermal loading,
- network topology,
- equipment operating limits.
These models provide the information needed to determine whether proposed allocations remain physically achievable.
Coordinating multiple constraints
Modern electricity systems contain many interacting constraints.
For example:
A battery may have available energy but insufficient network capacity to export it.
A generator may be capable of increasing production while a nearby transformer is fully loaded.
A flexible consumer may be willing to shift demand but only within certain operating limits.
Network-feasible allocation considers these interactions together when evaluating requests.
Integrating economics and engineering
Electricity markets are often described using economic concepts such as prices, incentives and competition.
Power systems are described using engineering concepts such as voltages, currents and power flows.
Network-feasible allocation brings these two perspectives together.
Economic decisions are evaluated within the physical capabilities of the network.
This helps ensure that market outcomes remain implementable without compromising system security.
Building on previous lessons
The previous lessons introduced two important ideas:
- maintaining a continuously updated system state, and
- evaluating requests whenever they arrive.
Network-feasible allocation adds a third component.
Every new request is assessed not only against the current market state, but also against the physical capabilities of the electricity network.
In this way, economic coordination and physical operation evolve together.
A key insight
A successful electricity market must produce outcomes that are both economically desirable and physically deliverable.
Network-feasible allocation incorporates engineering constraints directly into the allocation process, ensuring that accepted requests remain compatible with the capabilities of the electricity system.
Key takeaways
- Every electricity market outcome must ultimately be delivered through a physical network.
- Network-feasible allocation considers engineering constraints during the allocation process.
- Physical limits include transmission capacity, voltage limits, equipment ratings and operational constraints.
- Mathematical network models help determine whether proposed allocations remain feasible.
- Integrating engineering and economics helps ensure that market outcomes are physically deliverable.
- Network-feasible allocation builds upon the stateful and continuously clearing architecture introduced in the previous lessons.
Looking ahead
So far, we have explored what information the market remembers, when allocation decisions are made and how they remain physically feasible.
The next lesson examines how prices can emerge throughout the network, introducing the concept of distributed and hierarchical pricing.