• Energy Research

The increased penetration of renewable energy sources in the electrical grid raises the need for more power system flexibility. One of the high potential groups to provide such flexibility is the industry. Incentives to do so are provided by variable pricing and remuneration of supplied ancillary services. The operational flexibility of a chlor-alkali electrolysis process shows opportunities in the current energy and ancillary services markets. A co-optimisation of operating the chlor-alkali process under an hourly variable priced electricity sourcing strategy and the delivery of Frequency Containment Reserve (FCR) is the core of this work. A short term price prediction for the Day-Ahead Market (DAM) and FCR market as input for a deterministic optimisation shows good results under standard DAM price patterns, but leaves room for improvement in case of price fluctuations, e.g., as caused by Renewable Energy Sources (RES). A two-stage stochastic optimisation is considered to cope with the uncertainties introduced by the exogenous parameters. An improvement of the stochastic solution over the deterministic Expected Value (EV) solution is shown.

With the increasing shares of intermittent renewable sources in the grid, it becomes increasingly essential to quantify the requirements of the power systems flexibility. In this article, an adjusted weight flexibility metric (AWFM) is developed to quantify the available flexibility within individual generators as well as within the overall system. The developed metric is useful for power system operators who require a fast, simple, and offline metric. This provides a more realistic and accurate quantification of the available technical flexibility without performing time-consuming multi-temporal simulations. Another interesting feature is that it can be used to facilitate scenario comparisons. This is achieved by developing a new framework to assure the consistency of the metric and by proposing a new adjusted weighting mechanism based on correlation analysis and analytic hierarchy process (AHP). A new ranking approach based on flexibility was also proposed to increase the share of the renewable energy sources (RESs). The proposed framework was tested on the IEEE RTS-96 test-system. The results demonstrate the consistency of the AWFM. Moreover, the results show that the proposed metric is adaptive as it automatically adjusts the flexibility index with the addition or removal of generators. The new ranking approach proved its ability to increase the wind share from 28% to 37.2% within the test system. The AWFM can be a valuable contribution to the field of flexibility for its ability to provide systematic formulation for the precise analysis and accurate assessment of inherent technical flexibility for a low carbon power system.

AbstractThe participation of wind farms in providing ancillary services is an asset for the power system and one way to maintain a strong grid with the increasing penetration of renewable energy sources. Research has shown this to be feasible for wind farms by using efficient prediction and sophisticated control systems. In some parts of the world, strict grid codes are already being implemented that require wind farms to provide ancillary services. Moreover, the primary reserve market in Europe is moving towards shorter procurement periods, providing wind farms an opportunity to more efficiently optimise their resources based on short term forecasts. It can however be challenging for the wind farms to efficiently participate in grid frequency support services, especially for primary reserve services. The reason behind this is the requirement of quick activation and deactivation of power reserve margin for services such as Frequency Containment Reserve (FCR) and Fast Frequency Response (FFR). A full activation of the contracted reserve is required within seconds of a grid frequency dip. A sudden change in wind turbine dynamics is expected to have an impact on the wake behind the wind turbine. The wake effect within a wind farm is taken into thorough consideration in its design process. The effect on the wake due to the wind turbines participating in fast response ancillary services however, remains unexplored. This is a matter of greater concern for wind farms with a high capacity density. To this end, the main contribution of this article is to observe the effect of ancillary service based control system on the wake effect of a wind turbine. Additionally, the capability of developed wind turbines controllers to follow primary reserve services are also tested. FFR and FCR services are tested for a range of frequency designs, these include both synthetic and actual grid frequencies. The synthetic frequency profiles are designed to replicate both fast and slow frequency variations in order to analyse the impact on wake behaviour. The simulations are performed for low and high wind speed including constant as well as turbulent winds.

The components of an operational wind turbine are continuously impacted by both static and dynamic loads. Regular inspections and maintenance are required to keep these components healthy. The main bearing of a wind turbine is one such component that experiences heavy loading forces during operation. These forces depend on various parameters such as wind speed, operating regime and control actions. When a wind turbine provides frequency containment reserve (FCR) to support the grid frequency, the forces acting upon the main bearing are also expected to exhibit more dynamic variations. These forces have a direct impact on the lifetime of the main bearing. With an increasing trend of wind turbines participating in the frequency ancillary services market, an analysis of these dynamic forces becomes necessary. To this end, this paper assesses the effect of FCR-based control on the main bearing lifetime of the wind turbine. Firstly, a control algorithm is implemented such that the output power of the wind turbine is regulated as a function of grid frequency and the amount of FCR. Simulations are performed for a range of FCR to study the changing behaviour of dynamical forces acting on the main bearing with respect to the amount of FCR provided. Then, based on the outputs from these simulations and using 2 years of LiDAR wind data, the lifetime of the main bearing of the wind turbine is calculated and compared for each of the cases. Finally, based on the results obtained from this study, the impact of FCR provision on the main bearing lifetime is quantified and recommendations are made, that could be taken into account in the operation strategy of a wind farm.

Assessing the overall condition of wind turbines (WTs) in operation is challenging due to their intricate nature. This becomes even more complicated when WTs provide ancillary services and respond to grid requirements under curtailment modes. Multiple models are required to effectively evaluate the WTs' healthy condition, which can be unmanageable and impractical, particularly for large-scale wind farms. This article proposes a novel hybrid physics-based deep learning framework to accurately approximate the time-varying correlation between control sequences and system response, reflecting the aerodynamic nonlinearity of the 5-MW offshore WT model, designed and tested by the National Renewable Energy Laboratory (NREL). Another layer of this study's novelty relies on proposing a computationally efficient weakly supervised method that uses the hybrid structure to detect degradations and anomalies considering curtailment operation. Then, a self-learning classification approach is employed to iteratively update the best-tuned classifier, dynamically learning unforeseen abnormalities from brand-new anomalies during active operations. The proposed anomaly detection strategy deals with system uncertainties, such as wind stochasticity, power curve variations, and different sparsity levels in the datasets. The results of the proposed approach show promise in improving health monitoring performance, leading to a more efficient and accurate assessment of the overall condition of WTs.

AbstractThe pan‐European power grid is experiencing an increasing penetration of Variable Renewable Energy (VRE). The fluctuating and non‐dispatchable nature of VRE hinders them in providing the Ancillary Service (AS) needed for the reliability and stability of the grid. Therefore, Energy Storage Systems (ESS) are needed along the VRE. Among the different ESS, a particularly viable and reliable option is Pumped Hydro Storage (PHS), given its cost‐effective implementation and considerable lifespan, in comparison to other technologies. Traditional PHS plants with Francis turbines operate at a high head difference. However, not all regions have the necessary topology to make these plants cost‐effective and efficient. Therefore, the ALPHEUS project will introduce low‐head PHS for regions with a relatively flat topography. In this paper, a grid‐forming controlled converter coupled with low‐head PHS that can contribute to the grid stability is introduced, emphasising its ability to provide different AS, especially frequency control, through the provision of fast Frequency Containment Reserve (fFCR) as well as synthetic system inertia. This paper is an extended version of the paper “The Contribution of Low‐head Pumped Hydro Storage to a successful Energy Transition”, which was presented at the 19th Wind Integration Workshop 2020.