A Causation-Based Framework for Pricing and Cost Allocation of Energy, Reserves, and Transmission in Modern Power Systems

TL;DR

This paper introduces a causation-based pricing framework for power systems that allocates costs for energy, reserves, and transmission based on contingency analysis, improving efficiency and reliability in electricity markets.

Contribution

It proposes a novel causation-based pricing scheme with security charges and explicit reserve prices, enhancing cost-reflectiveness and reliability incentives in power system operations.

Findings

Ensures revenue adequacy and neutrality in pricing.

Promotes reliability incentives for generators.

Demonstrates effectiveness through case studies.

Abstract

The increasing vulnerability of power systems has heightened the need for operating reserves to manage contingencies such as generator outages, line failures, and sudden load variations. Unlike energy costs, driven by consumer demand, operating reserve costs arise from addressing the most critical credible contingencies - prompting the question: how should these costs be allocated through efficient pricing mechanisms? As an alternative to previously reported schemes, this paper presents a new causation-based pricing framework for electricity markets based on contingency-constrained energy and reserve scheduling models. Major salient features include a novel security charge mechanism along with the explicit definition of prices for up-spinning reserves, down-spinning reserves, and transmission services. These features ensure more comprehensive and efficient cost-reflective market operations. Moreover, the proposed nodal pricing scheme yields revenue adequacy and neutrality while promoting reliability incentives for generators based on the cost-causation principle. An additional salient aspect of the proposed framework is the economic incentive for transmission assets, which are remunerated based on their use to deliver energy and reserves across all contingency states. Numerical results from two case studies illustrate the performance of the proposed pricing scheme.