The Rise of Distributed Energy Resources
Electric power systems (EDS) are changing rapidly. The growth of distributed energy resources (DERs), such as rooftop solar panels, battery storage, and small-scale generators, is transforming the traditional EDS. Consumers are no longer passive users but are becoming prosumers who both consume and produce energy. While this shift introduces new flexibility and innovation to the grid, it also raises an important question: how should electricity markets evolve to coordinate these DERs efficiently?
Traditional electricity markets were designed around centralized generation and one-way power flows. Today, however, integrating DERs requires new coordination mechanisms that allow many small participants to interact dynamically while respecting grid constraints [1], [2]. Among the emerging solutions, transactive energy markets (TEM) have gained increasing attention.
Transactive energy markets
A TEM enables distributed coordination between electricity producers and consumers through price-based interactions rather than centralized control. Participants negotiate energy exchanges directly while responding to market signals and operational constraints. This approach improves scalability, preserves participant privacy, and facilitates the integration of DERs in the EDS [3], [4].
However, most existing TEM designs focus primarily on economic efficiency and system operation. Environmental impacts, particularly carbon emissions, are typically addressed through external policy mechanisms such as carbon pricing or emission regulations. While these policies are important, they often fail to provide clear operational signals to individual market participants.
As a result, participants may make economically rational decisions that unintentionally increase system-wide emissions. For example, a prosumer purchasing electricity from the grid may observe only the market price, without knowing whether the electricity comes from a renewable resource or from a carbon-intensive generator.
Why Carbon Signals Matter
Electricity generation technologies differ significantly in their carbon intensity. Renewable resources such as solar and wind produce little to no direct emissions, while conventional thermal generators can emit substantial amounts of carbon dioxide. Yet these differences are rarely visible to individual market participants.
Providing information about the carbon impact of electricity consumption can help address this issue. In traditional electricity markets, location-specific prices known as locational marginal prices reflect the cost of delivering electricity to different parts of the network. Inspired by this idea, researchers have begun exploring locational emission signals.
These signals estimate how a small change in electricity demand at a specific location affects total system emissions. Making this information available to market participants allows environmental considerations to be incorporated directly into energy trading decisions.
From Price Signals to Emission Signals
One approach to implementing emission signals is through distribution locational marginal emissions (DLME). DLME represents the marginal emission impact associated with electricity consumption at different locations in the EDS. Just as prices guide economic decisions, DLME can guide environmentally responsible choices.
For example, when two potential trading partners offer electricity at similar prices, the emission signal may reveal that one supplier has a significantly lower carbon footprint. A carbon-aware market participant may therefore prefer a cleaner source of electricity.
A key challenge is how to efficiently compute emission signals. EDS are complex networks in which generation, dispatch, and power flows change continuously. Calculating emission impacts using detailed optimization models would require repeatedly solving large system problems, which is impractical for real-time applications.
To address this challenge, we propose data-driven methods that estimate emission sensitivities using historical operational data. By analyzing how emissions respond to changes in system and local demand under different operating conditions, these models can quickly estimate marginal emission signals without repeatedly solving large optimization problems.
Toward Carbon-Aware Electricity Markets
Integrating emission signals into TEM offers several important benefits. First, it helps align economic incentives with environmental objectives. When carbon impacts are reflected in trading decisions, market participants naturally shift toward cleaner electricity sources.
Second, emission signals improve transparency and accountability. Participants gain visibility into the environmental consequences of their actions, enabling more informed trading decisions.
Third, data-driven emission estimation enables scalable implementation. By avoiding repeated system-wide optimization, emission signals can be generated efficiently even in systems with large numbers of distributed participants.
As DERs continue to expand, electricity markets will need mechanisms that coordinate not only economic value but also environmental impact. Embedding carbon signals directly into TEM represents an important step toward an efficient and flexible EDS that supports a low-carbon future.
References
[1] D. K. Molzahn et al., “A survey of distributed optimization and control algorithms for electric power systems,” IEEE Transactions on Smart Grid, 2017.
[2] J. P. Lopes et al., “Integrating distributed generation into electric power systems: A review of drivers, challenges and opportunities,” Electric Power Systems Research, 2007.
[3] GridWise Architecture Council, GridWise Transactive Energy Framework, Pacific Northwest National Laboratory, 2019.
[4] T. Morstyn, A. Teytelboym, and M. D. McCulloch, “Designing decentralized markets for distribution system flexibility,” IEEE Transactions on Power Systems, 2019.
