Price Tracing: Linking Nodal Prices in Optimized Power Systems

TL;DR

This paper introduces Price Tracing, a method that links nodal prices in power systems to system flows, enabling transparent cost allocation and insights into price structures, especially useful for renewable energy integration.

Contribution

It presents a novel mathematical approach called Price Tracing that coherently links locational marginal prices with system flows, improving cost transparency and allocation in power system optimization.

Findings

Price Tracing provides transparent cost allocation.

The method outperforms existing approaches in plausibility and consistency.

Application to Germany's renewable-rich system demonstrates practical benefits.

Abstract

Optimizing the total cost of power systems is a common tool for network operation and planning. Besides valuable information about how to run and possibly expand a power system, the optimization provides an optimal Locational Marginal Price per node and time step. This price can be seen as the price of electricity paid by consumers and purchased by suppliers, while maximizing social welfare. Naturally, it is a direct result of the optimization problem, and therefore does not give any information about its internal composition. This paper shows that by applying Flow Tracing, an algorithm for tracking flows in complex networks, it is possible to interlink Locational Marginal Prices in a coherent mathematical way. This does not only lead to important insights into the price structure, but also provides an intuitive decomposition and allocation of all system costs. Then individual consumers see how much they have to pay to individual generators and transmission lines in the power system. This method, introduced as Price Tracing, outperforms similar approaches provided by the literature, since the resulting cost allocations are transparent, plausible, and consistent with the Locational Marginal Prices from the optimization. The Price Tracing method is applied and discussed on behalf of a power system model of Germany with a high share of renewable power. The presented analysis and its implications can help in finding a more efficient market design to promote renewable power supply.