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As the penetration of renewable energy sources into a power system increases, the significance of precise short-term forecasts for wind power generation becomes paramount. However, the erratic and non-periodic nature of wind poses challenges in accurately predicting the output. This paper presents a comprehensive investigation into forecasting wind power generation for the following day, using three machine learning models: long short-term memory (LSTM), convolutional neural network-bidirectional LSTM (CNN-biLSTM), and light gradient boosting machine (LGBM). In addition, this paper proposes a method to improve the prediction performance of LGBM by separating data according to the distribution of features, and training and testing each separated dataset with a distinct model. This study includes a comparative analysis of the performance of the proposed models in predicting wind turbine output, offering valuable insights into their respective efficiencies. The results of this investigation were analyzed for two geographically distinct wind farms (Korea and the UK). The findings of this study are expected to facilitate the selection of efficient prediction models within the forecast accuracy auxiliary service market and assist grid operators in ensuring reliable power supply for the grid. [ABSTRACT FROM AUTHOR]

This paper proposes a methodology for tuning a supervisory and frequency-response outer loop control system of a multi-terminal direct current (MTDC) grid designed to transmit offshore wind energy to an onshore AC grid, and to provide frequency support during over-frequency events. The control structure is based on a master–slave scheme and ensures the achievement of frequency response, with specific implementation of the UK national grid code limited-frequency sensitive (LFSM) and frequency-sensitive (FSM) modes. The onshore AC grid is modelled with an equivalent frequency-response model to simulate the onshore AC grid dynamics under frequency deviations. The main innovation of this paper is the development of a methodology for tuning simultaneously two hierarchical levels of a MTDC coordinated control structure, i.e., the MTDC supervisor, given by the active power set point for slave terminal, and the slope of frequency-response functions at onshore terminals. Based on these two hierarchical levels, different strategies are evaluated in terms of frequency peak reductions and change of the frequency order type. Moreover, tuning guidance is given when a different MTDC control structure or different synchronous generator characteristics of the onshore AC grid are considered. [ABSTRACT FROM AUTHOR]

Due to the increasing use of renewable, non-controllable energy generation systems energy storage systems (ESS) are seen as a necessary part of future power delivery systems. ESS have gained research interest and practical implementation over the past decade and this is expected to continue into the future. This is due to the economic and operational benefits for both network operators and customers, battery energy storage system (BESS) is used as the main focus of this research paper. This paper presents an analytical study of the benefits of deploying distributed BESS in an electrical distribution network (DN). The work explores the optimum location of installing BESS and its impact on the DN performance and possible future investment. This study provides a comparison between bulk energy storage installed at three different locations; medium voltage (MV) side and low voltage (LV) side of the distribution transformer (DT) and distributed energy storage at customers' feeders. The performance of a typical UK DN is examined under different penetration levels of wind energy generation units and BESS. The results show that the minimum storage size is obtained when BESS is installed next to the DT. However, the power loss is reduced to its minimum when BESS and wind energy are both distributed at load busbars. The study demonstrates that BESS installation has improved the loss of life factor of the distribution transformer. [ABSTRACT FROM AUTHOR]

Most of the UK Continental Shelf (UKCS) oil and gas (OG) installations have traditionally adopted in situ power generation, which is not only inefficient but also generating about 70% of the offshore CO2 emissions. The offshore wind and energy storage technologies for deep water are developing at a fast pace, enabling great opportunities for the OG installations located in the North Sea. In this paper, a pathway for the UKCS offshore OG installations electrification is introduced. The aim is to provide different power architectures that facilitate the OG installations' electrification, while benefiting from the existing and planned UK offshore wind power. Four hypothetical case studies (based on real data) were created, along the UKCS, where the corresponding power architectures were proposed. The selection of each architecture power component (e.g., transformers, converters and cables), as well as the transmission and distribution technology (e.g., AC or DC), is also provided and justified. Further, an overview cost estimation is carried out to predict the architecture capital cost. It is concluded that the four architectures can be mimicked not only along the UKCS but also worldwide, promoting the UKCS potential for a world-leading offshore energy hub and fostering the UK offshore wind-energy resources. [ABSTRACT FROM AUTHOR]

The use of wind power has grown strongly in recent years and is expected to continue to increase in the coming decades. Solar power is also expected to increase significantly. In a power system, a continuous balance is maintained between total production and demand. This balancing is currently mainly managed with conventional power plants, but with larger amounts of wind and solar power, other sources will also be needed. Interesting possibilities include continuous control of wind and solar power, battery storage, electric vehicles, hydrogen production, and other demand resources with flexibility potential. The aim of this article is to describe and compare the different challenges and future possibilities in six systems concerning how to keep a continuous balance in the future with significantly larger amounts of variable renewable power production. A realistic understanding of how these systems plan to handle continuous balancing is central to effectively develop a carbon-dioxide-free electricity system of the future. The systems included in the overview are the Nordic synchronous area, the island of Ireland, the Iberian Peninsula, Texas (ERCOT), the central European system, and Great Britain. [ABSTRACT FROM AUTHOR]

A significant amount of conventional power plants in the European power system is anticipated to be replaced by solar and wind power in the future. This may require alternative sources for inertia support. The purpose of the paper is to learn about the consequences on the frequency deviation after a fault in the European power system when more wind and solar are introduced and when wind is considered as a possible provider of inertia. This study quantifies the expected maximum requirement for additional inertia in the future European power system up to 2050. Furthermore, we investigated the possibility of wind power to meet this additional need by providing emulated inertia. The European power system of the EU-28 countries has been clustered to the five synchronous grids, UCTE, Nordic, UK, Baltic and Irish. The future European energy mix is simulated considering twelve different scenarios. Production units are dispatched according to their expected environmental impacts, which closely follow the minimum natural contribution of inertia, in descending order. The available capacity for all the types of production is considered the same as the installed. For all the simulated scenarios the worst case is examined, which means that a sudden disconnection of the largest production unit of the dispatched types is considered. Case study results reveal that, in most cases, additional inertia will be required but wind power may fully cover this need for up to 84% of all simulated horizons among all the scenarios on the UCTE grid, and for up to 98%, 86%, 99% and 86% on the Nordic, UK, Baltic and Irish grids, respectively. [ABSTRACT FROM AUTHOR]

Hydrogen presents an attractive option to decarbonise the present energy system. Hydrogen can extend the usage of the existing gas infrastructure with low-cost energy storability and flexibility. Excess electricity generated by renewables can be converted into hydrogen. In this paper, a novel multi-energy systems optimisation model was proposed to maximise investment and operating synergy in the electricity, heating, and transport sectors, considering the integration of a hydrogen system to minimise the overall costs. The model considers two hydrogen production processes: (i) gas-to-gas (G2G) with carbon capture and storage (CCS), and (ii) power-to-gas (P2G). The proposed model was applied in a future Great Britain (GB) system. Through a comparison with the system without hydrogen, the results showed that the G2G process could reduce £3.9 bn/year, and that the P2G process could bring £2.1 bn/year in cost-savings under a 30 Mt carbon target. The results also demonstrate the system implications of the two hydrogen production processes on the investment and operation of other energy sectors. The G2G process can reduce the total power generation capacity from 71 GW to 53 GW, and the P2G process can promote the integration of wind power from 83 GW to 130 GW under a 30 Mt carbon target. The results also demonstrate the changes in the heating strategies driven by the different hydrogen production processes. [ABSTRACT FROM AUTHOR]

Trading energy from wind and other forms of stochastic generation in competitive electricity markets is challenging due to the limited predictability of these resources. This paper examines the specific case of single-price balancing markets and derives risk-constrained strategies in a probabilistic framework, going beyond the trivial zero/max solution, which would have participants offer either zero or their maximum energy production based on a prediction of whether the system will be in net up- or down-regulation. The zero/max approach is unacceptable in reality as it exposes the participant to potentially huge imbalance charges, and would violate price taker assumption for a portfolio of significant size. Here, we propose several trading strategies that control risk by hedging against penalising balancing prices in favour of rewarding ones by contracting forecast generation plus some adjustment. These strategies are formulated in a probabilistic framework to address the presence of forecast uncertainty and asymmetric costs in balancing markets. A case study using data from the Great Britain electricity market is presented and it is shown that the proposed strategies are able to simultaneously increase revenue and reduce risk using risk-constrained strategies. Furthermore, the required forecasts of electricity prices and system length are produced using standard tools and widely available explanatory information and are found to have sufficient skill to increase revenue compared to not hedging. [ABSTRACT FROM AUTHOR]

We address the valuation of an operating wind farm and the finite-lived option to invest in it under different reward/support schemes: a constant feed-in tariff, a premium on top of the electricity market price (either a fixed premium or a variable subsidy such as a renewable obligation certificate or ROC), and a transitory subsidy, among others. Futures contracts on electricity with ever longer maturities enable market-based valuations to be undertaken. The model considers up to three sources of uncertainty: the electricity price, the level of wind generation, and the certificate (ROC) price where appropriate. When analytical solutions are lacking, we resort to a trinomial lattice combined with Monte Carlo simulation; we also use a two-dimensional binomial lattice when uncertainty in the ROC price is considered. Our data set refers to the UK. The numerical results show the impact of several factors involved in the decision to invest: the subsidy per MWh generated, the initial lump-sum subsidy, the maturity of the investment option, and electricity price volatility. Different combinations of variables can help bring forward investments in wind generation. One-off policies, e.g., a transitory initial subsidy, seem to have a stronger effect than a fixed premium per MWh produced. [ABSTRACT FROM AUTHOR]

Predicting flow patterns that develop on the roof of high-rise buildings is critical for the development of urban wind energy. In particular, the performance and reliability of devices largely depends on the positioning strategy, a major unresolved challenge. This work aims at investigating the effect of variations in the turbulent inflow and the geometric model on the flow patterns that develop on the roof of tall buildings in the realistic configuration of the University of Birmingham's campus in the United Kingdom (UK). Results confirm that the accuracy of Large Eddy Simulation (LES) predictions is only marginally affected by differences in the inflow mean wind speed and turbulence intensity, provided that turbulence is not absent. The effect of the presence of surrounding buildings is also investigated and found to be marginal to the results if the inflow is turbulent. The integral length scale is the parameter most affected by the turbulence characteristics of the inflow, while gustiness is only marginally influenced. This work will contribute to LES applications on the urban wind resource and their computational setup simplification. [ABSTRACT FROM AUTHOR]