Greening the Grid: Electricity Market Clearing with Consumer-Based Carbon Cost

TL;DR

This work addresses decarbonization by embedding consumer-driven carbon costs into electricity market clearing, enabling direct allocation of generation emissions to loads via a generation–load allocation matrix and total load emissions. The proposed linear, convex market-clearing model optimizes over generation, demand, and emission allocations while incorporating consumer bids for carbon costs $c_{co_2}$, and is benchmarked against carbon-flow and carbon-agnostic formulations. Numerical studies on a 3-bus system and the IEEE RTS-GMLC network show that moderate carbon costs can shift dispatch toward cleaner generation with limited impact on consumption, while higher costs prompt load reductions and substantial emission cuts; the degree of impact depends on the share and placement of carbon-sensitive loads. Compared with the carbon-flow model, the carbon-cost approach offers greater allocation flexibility and potentially serves more load, at the expense of higher generation costs and emissions in some scenarios, with the flow model delivering larger emission reductions under stricter tracing. These findings suggest that integrating consumer carbon preferences into market clearing can be a valuable tool for achieving carbon reductions in power systems, subject to sufficient uptake of carbon-sensitive loads and careful design of allocation rules.

Abstract

To enhance decarbonization efforts in electric power systems, we propose a novel electricity market clearing model that internalizes the allocation of emissions from generations to loads and allows for consideration of consumer-side carbon costs. Specifically, consumers can not only bid for power but also assign a cost to the carbon emissions incurred by their electricity use. These carbon costs provide consumers, ranging from carbon-agnostic to carbon-sensitive, with a tool to actively manage their roles in carbon emission mitigation. By incorporating carbon allocation and consumer-side carbon costs, the market clearing is influenced not solely by production and demand dynamics but also by the allocation of carbon emission responsibilities. To demonstrate the effect of our proposed model, we conduct a case study comparing market clearing outcomes across various percentages of carbon-sensitive consumers with differing carbon costs.

Figures (8)

• Figure 1: Comparison between carbon flow model and carbon cost model.
• Figure 2: Illustration of the three-bus system.
• Figure 3: Results for different carbon costs in the three-bus system.
• Figure 4: Carbon prices in several emission trading markets from 2018 to 2023 carbonp.
• Figure 5: Histrogram showing the utility values $u_d$ of all the consumers in the RTS-GMLC system.