Locational Marginal Burden

Energy burden—the fraction of income spent on electricity—varies across communities due to how power systems are operated. This visualization demonstrates the Locational Marginal Burden (LMB) framework, which reveals how transmission congestion can create price disparities that disproportionately affect low-income communities.

Key Insight

When transmission lines become congested, some communities lose access to cheap power and must buy from expensive local generators. Low-income areas can end up paying a higher percentage of their income for electricity than wealthy neighbors—even though both receive the same kilowatt-hours.

The Three Communities

Consider a simple power network with three communities:

CommunityDescriptionIncomeGenerator
RiversideWealthy suburb$125,000Expensive backup generator
EastsideLow-income neighborhood$20,000None
Industrial ParkPower plantN/ACheap main generator

When the transmission line between Riverside and Eastside becomes congested, Eastside is cut off from the cheap Industrial Park power. They must buy electricity from Riverside's expensive generator—causing their electricity prices to spike.


Interactive Visualization

Adjust the sliders below to explore how transmission capacity and demand affect electricity prices and energy burden.


The Mathematics

Energy Burden

Energy burden at location ii is defined as:

bi=πidisib_i = \frac{\pi_i \cdot d_i}{s_i}

where:

Locational Marginal Burden (LMB)

The LMB matrix captures how changes in demand at one location affect energy burden everywhere:

Kij=bidj=change in burden at nodeichange in demand at nodejK_{ij} = \frac{\partial b_i}{\partial d_j} = \frac{\text{change in burden at node} i}{\text{change in demand at node} j}

The off-diagonal terms are what make LMB different from simply looking at prices. They capture the network effects that propagate through congestion constraints.


What the Visualization Shows

ComponentDescription
Network DiagramThe three-bus triangle with power flows. Red pulsing indicates congestion.
ControlsAdjust line capacity and demand at each community.
MetricsLMP ($/MWh), energy burden (%), and system cost.
LMP ChartHow prices vary as transmission capacity changes.
Burden ChartHow energy burden varies with capacity. Notice the disparity under congestion!
LMB MatrixThe 2×2 sensitivity matrix (for the two communities with income). Off-diagonal entries show spillover effects.

Citation

If you use this visualization or the LMB framework, please cite:

@inproceedings{talkington_west_haider_2024,
    author = {Talkington, Samuel and West, Amanda and Haider, Rabab},
    title = {Locational marginal burden: Quantifying the equity of optimal power flow solutions},
    year = {2024},
    isbn = {9798400704802},
    publisher = {Association for Computing Machinery},
    doi = {10.1145/3632775.3661947},
    booktitle = {Proceedings of the 15th ACM International Conference on Future and Sustainable Energy Systems},
    pages = {97–107},
    numpages = {11},
    location = {Singapore, Singapore},
    series = {e-Energy '24}
}

Paper (ACM DL) | arXiv


Acknowledgments

This research was supported by the NSF Graduate Research Fellowship, NSF AI Institute for Advances in Optimization (AI4OPT), and the Georgia Tech Strategic Energy Institute.

Technical Note: This visualization runs entirely in your browser. The DC optimal power flow is solved using a QP algorithm in JavaScript. LMB is computed via closed-form implicit differentiation of the KKT conditions.