This study examines niche approaches to electrolyser integration into the electricity system. Electrolysers are directly connected to offshore wind farms to lower electricity supply costs. The system integrates onsite electricity and hydrogen storage, exporting to or importing from the grid only when prices are favourable. Electricity price arbitrage in this system could reduce the levelised cost of hydrogen (LCOH) by 17%–29% for offshore wind-powered systems without batteries, and by 1%–2% for grid-powered systems under UK electricity market prices in 2023–24. For offshore wind systems with battery storage, LCOH reductions of 1%–3% are achievable through arbitrage. Profitability also depends on electrolyser type, hydrogen demand, and structural variations in electricity pricing. These findings highlight the importance of incorporating such niche configurations into energy and electricity system models.

Against the backdrop of rapidly growing global photovoltaic (PV) power generation, its inherent intermittency and volatility challenge power grid stability. This paper presents a comprehensive model for PV power forecasting and optimizing active/reactive support capabilities of distributed PV-storage stations. First, a hybrid EMD-KPCA-LSTM model is developed to address PV output variability. It employs Empirical Mode Decomposition (EMD) for multi-scale feature extraction from meteorological data, Kernel Principal Component Analysis (KPCA) for dimensionality reduction, and Long Short-Term Memory (LSTM) networks for high-precision forecasting. Experimental results show significantly improved accuracy and robustness compared to single LSTM or EMD-LSTM models, with effective quantification of prediction uncertainties. Second, a nonlinear programming model based on robust optimization and Sequential Quadratic Programming (SQP) is proposed to optimize active/reactive support. By refining energy storage charging/discharging strategies, the model maximizes grid support while mitigating PV uncertainty via robust optimization and solving efficiently with SQP. Case studies validate that optimized PV-storage stations effectively dampen PV fluctuations, providing stable and substantial active/reactive support to enhance grid flexibility, stability, and renewable energy integration. This work offers critical theoretical and practical insights for developing smarter, greener, and more reliable modern power systems.

Rajasthan is the largest state in India by area and has the highest renewable energy (RE) potential in the country, estimated at around 450 GW (solar and wind combined). The state aims to install approximately 95 GW of RE capacity towards the national target of 500 GW by 2030. The transmission network plays a vital role in integrating and evacuating power from the generating stations to the load centres. Since a transmission infrastructure has a significantly longer gestation period than that of RE projects, the transmission network needs to be planned well in advance to prevent curtailment of power generated from RE sources due to network unavailability. In this context, our paper examines the transmission network availability in Rajasthan to integrate the power generated by the proposed RE projects and meet the projected state demand for the financial year 2029-30. Our study modelled the transmission network at voltage levels of 220 kV and above, using the PSS/E software, and executed load-flow analysis to evaluate the network’s availability to accommodate the increasing RE-based power generation in the state. The study identified the network constraints and also estimates the investment required to execute the recommended network strengthening measures.

With the rapid development of onshore solar power plants in China, land resources have gradually become scarce. To explore alternative solutions, floating photovoltaic (FPV) systems have garnered significant attention, particularly the offshore floating photovoltaic (OFPV) systems. Beyond saving land resources, offshore wind power plants and offshore PV power plants exhibit complementarity in their power generation profiles. However, the most critical challenge lies in the high capital expenditure (CAPEX) of OFPV systems, and the industry has not yet reached a consensus on a mature design scheme. In this study, to reduce the cost of OFPV systems, a three-column OFPV platform with an asymmetric water-area layout is proposed, and a feasibility analysis is conducted accordingly. For the purpose of comparative research, two types of platforms are introduced as reference: the truss-spar platform and the classic four-column semi-submersible platform.

As a common foundation type, bucket foundations for offshore wind turbines are often used in the design of offshore wind turbine foundations in single or multiple configurations. However, the factors influencing the ultimate bearing capacity of off-shore wind turbine bucket foundations are complex. This study focuses on the single-bucket foundation of offshore wind turbines, using the finite element software Abaqus to conduct a three-dimensional finite element analysis of the bearing characteristics of suction bucket foundations in clay soil. By quantitatively varying the structural parameters (length-to-diameter ratio, embedment depth) and soil parameters of the cylindrical foundation, the impact on the ultimate bearing capacity was investigated. The results show that the vertical load-displacement relationship exhibits a gradual curve, while the horizontal load-displacement relationship shows a steep curve. The length-to-diameter ratio is positively correlated with the ultimate bearing capacity.

The growing penetration of inverter-based resources (IBRs) in modern power systems has raised significant challenges related to system strength and stability. Unlike traditional synchronous generators, which provide inherent inertia and short-circuit system strength, renewable sources such as wind and solar lack these stabilising characteristics, making networks more vulnerable to instability. Addressing system strength is therefore critical, but the exact requirements and methods of assessment remain uncertain. Conventional electromagnetic transient (EMT) simulations are often employed to study small signal oscillations, but these are computationally intensive and not always necessary. An alternative is impedance-based frequency domain stability analysis, which characterises the interaction between system components by evaluating network impedance. This approach offers valuable insights into stability margins using the Nyquist criterion and is particularly effective for analysing power electronic systems. Although both synchronous machines and grid-forming (GFM) inverters are recognised as contributors to system strength, there is no generally accepted methodology to quantify their impact. This paper presents an impedance-based approach to assess the contribution of System Strength Mitigating Devices (SSMDs), focusing on small-signal stability. Three SSMDs; two GFM Battery Energy Storage Systems (BESS) and a synchronous condenser are compared, highlighting that stability support depends more on frequency response characteristics than nominal MVA short circuit capacity.

One of the key challenges in enhancing wind turbine reliability and longevity is mitigating tower oscillations, which arise from dynamic wind loads on the rotor and wave-induced excitations at the tower base. This can be achieved using active tower damping techniques. In this study, a model-based approach is used to quantify the impact of active tower dampers on tower oscillations. By focusing on generator torque and pitch angle control, the research explores the coupled dynamics of fore-aft and side-to-side oscillations. A linearized representation of the non-linear system is developed to assess tower oscillations in the full-load operating region. The proposed method quantitatively evaluates the effects of damping controllers directly from the linearised model. The results indicate that implementing fore-aft active tower damping leads to a reduction in tower oscillations in both directions up to 4.7 dB near the tower’s natural frequency. The findings are validated through simulations conducted in OpenFAST, using the 5 MW NREL monopile offshore wind turbine as a case study.