Risk-Aware Multi-Market Scheduling of Virtual Power Plants with Dynamic Network Tariffs

TL;DR

This paper introduces a comprehensive stochastic optimization model for virtual power plant scheduling that accounts for detailed device constraints, network limitations, market uncertainties, and dynamic tariffs, enhancing operational flexibility and risk management.

Contribution

It presents a novel two-stage stochastic framework integrating local flexibility procurement via dynamic tariffs with multi-market bidding, improving VPP scheduling under uncertainty.

Findings

Risk-averse strategies reduce profit volatility.

Dynamic tariffs enable demand shifting but can lower expected profits.

The model effectively exploits arbitrage opportunities in case studies.

Abstract

As the penetration of distributed energy resources (DERs) increases, harnessing their flexibility becomes critical for power system operations. Virtual power plants (VPPs) offer a promising solution. However, most existing scheduling tools rely on simplified DER or grid models and largely overlook local flexibility procurement mechanisms such as dynamic network tariffs. This paper proposes a two-stage stochastic optimization framework for VPP multi-market scheduling that integrates detailed device-level constraints, network limitations, and operational and market uncertainties. Conditional value-at-risk is incorporated to represent risk preferences, and Benders decomposition ensures tractability with extensive scenario sets. The model jointly optimizes bidding across energy and reserve markets while explicitly accounting for local flexibility procurement through dynamic network tariffs. The results from a realistic case study show that both risk-neutral and risk-averse strategies exploit arbitrage opportunities. However, risk aversion reduces profit volatility through closer alignment with physical dispatch. Dynamic tariffs unlock local flexibility by shifting demand across the day, though strong tariff signals reduce expected profitability by up to 65% with limited additional flexibility gains.