  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.
