Optimal Dynamic Capacity Allocation of HVDC Interconnections for Cross-border Exchange of Balancing Services in Presence of Uncertainty - Extended Version

TL;DR

This paper proposes a stochastic market-clearing algorithm for HVDC interconnections to improve cross-border balancing services, demonstrating its advantages over deterministic approaches especially with increasing wind power integration.

Contribution

It introduces a stochastic market design for HVDC-based cross-border balancing, comparing it with deterministic methods and analyzing transmission allocation impacts.

Findings

Stochastic approach outperforms deterministic methods with high wind power.

Tighter reserve-energy coordination reduces system costs.

Explicit transmission allocation influences market efficiency.

Abstract

Considering that the existing setup of the European electricity markets promotes the spatial coordination of neighbouring power systems only on the day-ahead market stage, regional system operators have to rely mainly on their internal balancing resources in order to guarantee system security. However, as power systems are forced to operate closer to their technical limits, where flexible generation becomes scarce, the conventional market paradigm may not be able to respond effectively on the wide range of uncertainty. The operational flexibility of the power system depends both on the technical parameters of its components, i.e., generators and transmission infrastructure, as well as on the operational practices that make optimal use of the available assets. This work focuses on alternative market designs that enable sharing of cross-border balancing resources between adjacent power systems through High Voltage Direct Current (HVDC) interconnections which provide increased controllability. In this context, we formulate a stochastic market-clearing algorithm that attains full spatio-temporal integration of reserve capacity, day-ahead and balancing markets. Against this benchmark we compare two deterministic market designs with varying degrees of coordination between the reserve capacity and energy services, both followed by a real-time mechanism. Our study reveals the inefficiency of deterministic approaches as the shares of wind power increase. Nevertheless, enforcing a tighter coordination between the reserves and energy trading floors may improve considerably the expected system cost compared to a sequential market design. Aiming to provide some insights for improvement of the sequential market-clearing, we analyse the effect of explicit transmission allocation between energy and reserves for different HVDC capacities and identify the market dynamics that dictate the optimal ratio.