Control Co-Design Under Uncertainty for Offshore Wind Farms: Optimizing Grid Integration, Energy Storage, and Market Participation

TL;DR

The paper tackles optimizing offshore wind farm integration under wind and price uncertainty by introducing a control co-design (CCD) framework that jointly optimizes onshore energy storage sizing, HVDC cable capacity, and droop-based control for market participation and frequency support. It employs a multi-time, multi-stage stochastic formulation with scenario trees to couple design decisions with day-ahead and real-time market participation, accounting for ancillary services. Key contributions include integrating design sizing with control tuning, detailing a scenario-generation and multi-scale optimization approach, and validating the framework with PSCADE EMT simulations, which show improved revenue and robust grid support. Practically, the CCD approach enables more economical and reliable OWF deployments by aligning capital investments with evolving energy markets and grid requirements.

Abstract

Offshore wind farms (OWFs) are set to significantly contribute to global decarbonization efforts. Developers often use a sequential approach to optimize design variables and market participation for grid-integrated offshore wind farms. However, this method can lead to sub-optimal system performance, and uncertainties associated with renewable resources are often overlooked in decision-making. This paper proposes a control co-design approach, optimizing design and control decisions for integrating OWFs into the power grid while considering energy market and primary frequency market participation. Additionally, we introduce optimal sizing solutions for energy storage systems deployed onshore to enhance revenue for OWF developers over time. This framework addresses uncertainties related to wind resources and energy prices. We analyze five U.S. west-coast offshore wind farm locations and potential interconnection points, as identified by the Bureau of Ocean Energy Management (BOEM). Results show that optimized control co-design solutions can increase market revenue by 3.2\% and provide flexibility in managing wind resource uncertainties.

Figures (14)

• Figure 1: The structure of the system considered in this paper. Offshore wind farms are connected to onshore points through HVDC separately.
• Figure 2: Schematic of the workflow for the proposed multi-time multi-stage stochastic control co-design methodology
• Figure 3: The control diagram of offshore wind turbine is shown highlighting the rotor stator control (RSC). The droop gain ($k$) associate the RSC controller is optimized to provide the required reserve for primary frequency market participation.
• Figure 4: Probability density functions of CAISO NP15 region DA and RT market prices for 2018 and 2022.
• Figure 5: (a) Scenario generation scheme for offshore Wind Farm Optimization. (b) Schematic scenario tree with defining the multi-stage decision variables.