Addressing the Time-Varying Dynamic Probabilistic Reserve Sizing Method on Generation and Transmission Investment Planning Decisions

TL;DR

This paper introduces a probabilistic, dynamic method for sizing reserves in long-term generation and transmission planning, accounting for high renewable energy penetration and its associated costs.

Contribution

It presents a novel approach integrating forecast error evaluation of renewable sources into expansion planning models as an endogenous reserve requirement.

Findings

The methodology effectively captures the impact of VRE forecast errors on reserve sizing.

Applying the method to the Mexican system demonstrates its practical utility.

Considering reserve requirements influences investment decisions and system costs.

Abstract

In this paper, we address the long-term system's requirement reserve sizing due to the high-level of variable renewable energy (VRE) sources penetration, inside the expansion planning model. The increase in the insertion of this kind of energy source will also bring an increase in the reserve requirements. A higher requirement will be translated into additional costs to the system since the system operator will need to allocate generators for reserve purposes. The VRE sources implicitly cause these costs, so besides the investment cost, the expansion planning models should consider those costs on the expansion decision process. The methodology proposed here aims to provide a probabilistic and dynamic evaluation of the forecast errors of VRE sources generation, translating these errors into the system's requirement reserve. This evaluation is done inside the expansion planning optimization model, treating the reserve requirement as an endogenous variable. Finally, a real case study of the Mexican system is presented, so that we can analyze the results of the methodology and the impacts of considering the reserve requirement along with the expansion planning decision.