Pricing Real-time Stochastic Storage Operations

TL;DR

This paper develops a novel pricing mechanism for real-time stochastic storage operations that eliminates the need for out-of-market uplifts by introducing temporal locational marginal pricing, ensuring fair and truthful market settlements.

Contribution

It proposes a new TLMP pricing scheme that incorporates ramping and state-of-charge shadow prices, improving upon traditional uniform pricing methods in stochastic storage markets.

Findings

TLMP removes the need for out-of-market uplifts.

TLMP ensures truthful bidding incentives.

Numerical simulations confirm revenue adequacy and reduced uplifts.

Abstract

Pricing storage operation in the real-time market under demand and generation stochasticities is considered. A scenario-based stochastic rolling-window dispatch model is formulated for the real-time market, consisting of conventional generators, utility-scale storage, and distributed energy resource aggregators. We show that uniform pricing mechanisms require discriminative out-of-the-market uplifts, making settlements under locational marginal pricing (LMP) discriminative. It is shown that the temporal locational marginal pricing (TLMP) that adds nonuniform shadow prices of ramping and state-of-charge to LMP removes the need for out-of-the-market uplifts. Truthful bidding incentives are also established for price-taking participants under TLMP. Revenue adequacy and uplifts are evaluated in numerical simulations.