— The European Union is pushing to achieve a sustainable, competitive and secure energy supply in Europe. This has translated into significant long-term renewable energy targets towards 2050, and the ...ambition to improve the European grid. A large share of this development is expected to occur in the North Sea. This paper investigates which transmission architecture is the most beneficial to integrate large shares of renewable energy in the North Sea region, and the consequences of the planning horizon when planning such a system towards 2050 are analysed. This is achieved by performing investment optimisation of generation and transmission for different scenarios. It is found that: 1) an integrated offshore grid configuration planned over a long planning horizon leads to cost minimization; 2) the grid topology is not likely to influence the penetration of variable renewable energy, but it will affect the contribution of each variable renewable energy type and the system costs; and 3) not taking the future into account when developing the energy system is likely to lead to a more expensive system. These results remark the importance of long-term planning horizon for energy systems and grid expansion and calls for a political focus on planning and international cooperation.
•Investment optimisation for power generation and transmission is performed in the North Sea region towards 2050.•An integrated offshore grid configuration leads to lower costs than a project-based one.•The grid topology barely influences the overall penetration of variable renewable energy.•Expected future development should be considered when planning the energy system.
This reprint explores the latest developments and advancements in the application of artificial intelligence (AI) and machine learning (ML) for forecasting and optimization in the field of power ...engineering. In recent years, AI and ML methods have been gaining significant traction and are becoming two of the most important fields in computing. These methods have proven to be effective in solving forecasting and optimization problems in power engineering. The topics covered in the chapters fall into four categories: electricity demand forecasting, wind power forecasting, photovoltaic power forecasting, and optimization.
In the energy production sector, increasing the quantity and efficiency of renewable energies, such as hydropower plants, is crucial to mitigate climate change. This paper proposes a new and flexible ...model for optimising operational decisions in watershed systems with interconnected dams. We propose a systematic representation of watersheds by a network of different connection points, which is the basis for an efficient Mixed-Integer Linear Programming model. The model is designed to be adaptable to different connections between dams in both main and tributary rivers. It supports decisions on power generation, pumping and water discharge, maximising profit, and considering realistic constraints on water use and factors such as future energy prices and weather conditions. A relax-and-fix heuristic is proposed to solve the model, along with two heuristic variants to accommodate different watershed structures and sizes. Methodological tests with simulated instances validate their performance, with both variants achieving results within 1% of the optimal solution faster than the model for the tested instances. To evaluate the performance of the approaches in a real-world scenario, we analyse the case study of the Cávado watershed (Portugal), providing relevant insights for managing dam operations. The model generally follows the actual decisions made in typical situations and flood scenarios. However, in the case of droughts, it tends to be more conservative, saving water unless necessary or profitable. The model can be used in a decision-support system to provide decision-makers with an integrated view of the entire watershed and optimised solutions to the operational problem at hand.
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•New and flexible mathematical model to manage interconnected dams in a watershed.•Tailored relax-and-fix approach developed to solve the proposed model.•Case study in Cávado watershed (Portugal) brings insights into dam management.•The impact of flood, drought and regular seasons is analysed for Cávado watershed.
In this paper, the solid isotropic material with penalisation (SIMP) method for topology optimisation of 2D problems is reformulated in the non-uniform rational BSpline (NURBS) framework. This choice ...implies several advantages, such as the definition of an implicit filter zone and the possibility for the designer to get a geometric entity at the end of the optimisation process. Therefore, important facilities are provided in CAD postprocessing phases in order to retrieve a consistent and well connected final topology. The effect of the main NURBS parameters (degrees, control points, weights and knot-vector components) on the final optimum topology is investigated. Classic geometric constraints, as the minimum and maximum member size, have been integrated and reformulated according to the NURBS formalism. Furthermore, a new constraint on the local curvature radius has been developed thanks to the NURBS formalism and properties. The effectiveness and the robustness of the proposed method are tested and proven through some benchmarks taken from literature and the results are compared with those provided by the classical SIMP approach.
This study discusses the parameter estimation of the Hammerstein output-error moving average system using the dual-rate sampled data. The polynomial transformation technique is used to obtain the ...identification model of the discussed dual-rate sampled systems. The stochastic gradient optimisation method is an effective optimisation method. Compared with the Newton optimisation, it only needs to calculate the first derivative during the optimisation and the amount of calculation is relatively small. It is a good choice to use the stochastic gradient algorithm for the identification of Hammerstein dual-rate model after using the polynomial transformation technique. In order to improve the convergence speed, a maximum likelihood forgetting factor stochastic gradient identification algorithm is proposed by combining the maximum likelihood principle and the gradient search method. The convergence of the algorithm is analysed by using the stochastic process theory. Furthermore, in order to improve the estimation accuracy of the identification algorithm, a maximum likelihood multi-innovation forgetting factor stochastic gradient algorithm is proposed by using the multi-innovation identification theory. The effectiveness of the proposed algorithms is illustrated by a numerical simulation example and a water tank system.
In this paper we use computational structural optimisation to consider the multi-objective design of piezoelectric materials for both stiffness and piezoelectric properties. We design new ...single-poled piezoelectric materials to maximise a linear combination of the effective hydrostatic coupling constant, d̄h, and effective bulk modulus, B̄E. We utilise the Solid Isotropic Material with Penalisation (SIMP) method and derive the sensitivities of the homogenised piezoelectric properties using an adjoint method. Our optimisation results suggest that the hydrostatic coupling constant and bulk modulus cross-property space is convex. Furthermore, the optimised materials have competitive piezoelectric figures of merit when the optimisation objective prioritises d̄h, and this indicates their suitability for sensor and hydrophone applications. While computational design of piezoelectric materials is a sparse research field, our work demonstrates the potential of structural optimisation for discovering piezoelectric meta-materials with enhanced properties.
This paper presents a systematic methodology to optimise the geometry of a three-body hinge-barge wave energy converter, to maximise the energy extraction of the device in given sea states and in ...site-specific wave climates. To that end, a 5-degree-of-freedom mathematical model is proposed to describe the system dynamics in two-dimensional space and a two-layer optimisation is designed to find the optimal design and control variables. The inner-layer optimisation is used to find the optimal control parameters of the power take-off system and the outer-layer optimisation, which uses a genetic algorithm, is employed to find the optimal design parameters of barge lengths and of optimal ballast positioning. In the case study, this methodology is applied to a 1:20 scale prototype of the McCabe Wave Pump device. Numerical results indicate that the optimal dimensions of the device, under given sea states, can be found efficiently and accurately, and that there appears to be no obvious benefit in the use of three barges, over a two-barge system.
•Geometric optimisation of a 3-barge hinge barge device (no comparable work to date).•Combined optimisation of geometry AND optimal positions for ballast masses.•2-level optimisation, updating the control for each geometry/ballast specification.•The analysis points to an optimal 2-barge configuration.
The global impact of corona virus (COVID-19) has been profound, and the public health threat it represents is the most serious seen in a respiratory virus since the 1918 influenza A(H1N1) pandemic. ...In this paper, we have focused on reviewing the results of epidemiological modelling especially the fractional epidemic model and summarized different types of fractional epidemic models including fractional Susceptible-Infective-Recovered (SIR), Susceptible-Exposed-Infective-Recovered (SEIR), Susceptible-Exposed-Infective-Asymptomatic-Recovered (SEIAR) models and so on. Furthermore, we propose a general fractional SEIAR model in the case of single-term and multi-term fractional differential equations. A feasible and reliable parameter estimation method based on modified hybrid Nelder-Mead simplex search and particle swarm optimisation is also presented to fit the real data using fractional SEIAR model. The effective methods to solve the fractional epidemic models we introduced construct a simple and effective analytical technique that can be easily extended and applied to other fractional models, and can help guide the concerned bodies in preventing or controlling, even predicting the infectious disease outbreaks.
The hybridisation of two or more algorithms is recently emerging to detect superior solutions to the optimization troubles. In this study, a new hybrid cuckoo search algorithm and grey wolf optimiser ...(CSA–GWO) optimisation technique is exercised and exhibited to optimally design and tune the controller parameters installed in the voltage source converter (VSC) of an offshore wind farm (OWF). One of the widely used control strategies for VSC is the proportional–integral (PI) closed-loop control system. The new hybrid optimisation algorithm is used to design and tune the PI controllers' parameters to improve the performance of OWF. It shall be mentioned that these parameters are usually hard to obtain owing to the high level of embedded non-linearity in such energy systems. The performance of such optimally designed PI controllers is presented in both dynamic and transient conditions. To examine the realistic stability of the proposed algorithm, real wind speed pattern has been captured from Egypt wind farm at Zafarrana and simulated. The obtained results from this new hybrid optimisation CSA -GWO control system reflect its superiority over other traditional algorithms, such as genetic algorithm, especially during symmetrical and unsymmetrical faults. CSA–GWO algorithm was examined using MATLAB/Simulink.
•Eigen-frequencies and dynamic compliance are integrated in a Topology Optimisation (TO) algorithm based on Non-Uniform Rational Basis Spline (NURBS) hypersurfaces.•The NURBS continuous parameters ...(i.e. control points and weights) are the design variables of the TO problem.•A sensitivity analysis of the optimised topology to the NURBS discrete parameters is carried out.•NURBS properties allow reducing the number of design variables and provide the definition of an implicit filter zones.•The post-processing phase involving the CAD reconstruction of the optimised geometry is immediate for 2D problems and needs few operations in 3D.
The formulation of Topology Optimisation (TO) problems related to dynamics is particularly challenging, due to some intrinsic difficulties of mathematical and numerical nature. This paper deals with the integration of specific physical quantities, such as eigen-frequencies and dynamic compliance, in a special TO algorithm, which combines a classical pseudo-density field with Non-Uniform Rational Basis Spline (NURBS) entities. In this framework, wherein some of the NURBS continuous parameters (i.e. control points and weights) are the new design variables, important advantages can be exploited. In particular, beyond the reduction of the number of design variables and the definition of an implicit filter zones, the post-processing phase involving the CAD reconstruction of the optimised geometry is immediate for 2D problems and it needs few operations in 3D. Classical TO problems dealing with structural dynamics, as the maximisation of the first eigen-frequency and the minimisation of the dynamic compliance, are formulated in the NURBS framework. Accordingly, the analytical expressions of the gradients of the considered physical quantities are derived in closed form. In order to show the effectiveness of the proposed approach, an exhaustive numerical campaign is proposed and the algorithm is applied to both 2D and 3D benchmarks. Moreover, a sensitivity analysis of the final optimised solutions to the NURBS discrete parameters is provided as well.
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