A Survey of Artificial Neural Network in Wind Energy Systems

This article presents a review of the state of the art of the Wind Farm Design and Optimization (WFDO) problem. The WFDO problem refers to a set of advanced planning actions needed to extremize the performance of wind farms, which may be composed of a few individual Wind Turbines (WTs) up to thousands of WTs. The WFDO problem has been investigated in different scenarios, with substantial differences in main objectives, modelling assumptions, constraints, and numerical solution methods. The aim of this paper is: (1) to present an exhaustive survey of the literature covering the full span of the subject, an analysis of the state-of-the-art models describing the performance of wind farms as well as its extensions, and the numerical approaches used to solve the problem; (2) to provide an overview of the available knowledge and recent progress in the application of such strategies to real onshore and offshore wind farms; and (3) to propose a comprehensive agenda for future research.

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A Review of Methodological Approaches for the Design and Optimization of Wind Farms

Renewable energy technologies׳ systems are major components of the strategy to reduce harmful emissions and deal with depleting energy resources. It is necessary to deploy renewable energy sources in the best possible way such that cost is minimized and generation is maximized. In this paper, we present a review of different optimization methods for deployment and operation of renewable energy sources based generating units. Unlike other existing reviews, we carry out a general review of this research area, without limiting ourselves to any particular issue or geographic location. We examine this area with respect to different types of renewable energy sources, different modes of operations, types of objective functions for optimization and different geographical areas from which research publication are emanating. We present a general resource allocation problem and specify different possibilities for input, output, objective function and constraints. In addition, we review different objectives used in defining the optimization problems. We also present different types of linear and non-linear optimization algorithms used in renewable energy sources. Finally, we review optimization techniques for applications with respect to different end users.

Optimization classification, algorithms and tools for renewable energy: A review

Benefits analysis of Soft Open Points for electrical distribution network operation

Expectations for energy storage are high but large-scale underground hydrogen storage in porous media (UHSP) remains largely untested. This article identifies and discusses the scientific challenges of hydrogen storage in porous media for safe and efficient large-scale energy storage to enable a global hydrogen economy. To facilitate hydrogen supply on the scales required for a zero-carbon future, it must be stored in porous geological formations, such as saline aquifers and depleted hydrocarbon reservoirs. Large-scale UHSP offers the much-needed capacity to balance inter-seasonal discrepancies between demand and supply, decouple energy generation from demand and decarbonise heating and transport, supporting decarbonisation of the entire energy system. Despite the vast opportunity provided by UHSP, the maturity is considered low and as such UHSP is associated with several uncertainties and challenges. Here, the safety and economic impacts triggered by poorly understood key processes are identified, such as the formation of corrosive hydrogen sulfide gas, hydrogen loss due to the activity of microbes or permeability changes due to geochemical interactions impacting on the predictability of hydrogen flow through porous media. The wide range of scientific challenges facing UHSP are outlined to improve procedures and workflows for the hydrogen storage cycle, from site selection to storage site operation. Multidisciplinary research, including reservoir engineering, chemistry, geology and microbiology, more complex than required for CH4 or CO2 storage is required in order to implement the safe, efficient and much needed large-scale commercial deployment of UHSP.

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Enabling large-scale hydrogen storage in porous media – the scientific challenges

The paper presents a decision-making algorithm that has been developed for the optimum size and placement of distributed generation (DG) units in distribution networks. The algorithm that is very flexible to changes and modifications can define the optimal location for a DG unit (of any type) and can estimate the optimum DG size to be installed, based on the improvement of voltage profiles and the reduction of the network’s total real and reactive power losses. The proposed algorithm has been tested on the IEEE 33-bus radial distribution system. The obtained results are compared with those of earlier studies, proving that the decision-making algorithm is working well with an acceptable accuracy. The algorithm can assist engineers, electric utilities, and distribution network operators with more efficient integration of new DG units in the current distribution networks.

Development of a Decision-Making Algorithm for the Optimum Size and Placement of Distributed Generation Units in Distribution Networks

The worldwide increasing demand for electricity, coupled with governmental policy changes for "green" energy has led to significant interest in distributed generation (DG). Integrating DG into an electricity network, especially close to load centres, has many significant benefits but also brings with it many drawbacks such as voltage drop, and power losses. In this paper the impact of three different types of distributed generation (diesel generator, wind turbine and photovoltaic (PV)) on distribution networks' voltage profile and power losses is studied. NEPLAN software and the extended Newton-Raphson method have been used in the analysis. The obtained results show that different types of DG influence differently the distribution network and that their precise location and size are vital in reducing power losses and improving the voltage stability.

The Impact of Distributed Generation in the Distribution Networks' Voltage Profile and Energy Losses

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Power Quality Improvement in Power Grids with the Integration of Energy Storage Systems

Estimation of wind turbines optimal number and produced power in a wind farm using an artificial neural network model

Hybrid energy systems can provide various benefits to an island diesel power system. This paper analyses the technical and economic viability of hybrid energy system in the Masirah Island power system in Oman. The methodology involves the use of Hybrid Optimization Model for Electric Renewable (HOMER) for the optimization of the proposed hybrid system. The simulation software package DIgSILENT is used to model and simulate the integration of the proposed hybrid system to the existing network. Different scenarios are considered in both the hybrid system optimization and the assessment of the impact of the hybrid energy system integration implemented different connection scenarios. The obtained results show that the hybrid energy system composed of diesel, photovoltaic and wind generator units is the most economically feasible option since it provides the lowest system net present cost, operating cost and cost of energy, while it also improves the voltage profile at the point of connection.

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Vasiliki Vita

Papers

Development of a Decision-Making Algorithm for the Optimum Size and Placement of Distributed Generation Units in Distribution Networks

The Impact of Distributed Generation in the Distribution Networks' Voltage Profile and Energy Losses

Power Quality Improvement in Power Grids with the Integration of Energy Storage Systems

Estimation of wind turbines optimal number and produced power in a wind farm using an artificial neural network model

Techno-Economic Assessment of Hybrid Energy Off-Grid System - A Case Study for Masirah Island in Oman