Estimation of wind power generation in dense urban area

Yang, An-Shik; Su, Ying; Wen, Chih-Yung; Yu, Jiang; Wang, Wei-Siang; Cheng, Chiang-Ho

doi:10.1016/j.apenergy.2016.03.007

Cited by 130 publications

(71 citation statements)

References 44 publications

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“…This strategy can be considered as transforming the actual search space into another in which the computational working is much easier. From a mathematical point of view, if G is the set containing all of the candidate graphs and C is the set of chromosomes that encodes each of them (c G ), this representation is equivalent to defining a bijection, Ξ : G ←→ C (15) so that any candidate graph is represented by a unique chromosome Ξ( …”

Section: Encoding Methodsmentioning

confidence: 99%

“…Efficiently integrating distributed RE generation systems [3][4][5] is a key research topic because the most used renewable energies-photovoltaic (PV) solar energy [6,7], wind energy [8,9] and marine energy [10]-are intermittent and more difficult to store [11] and integrate without affecting the quality of the electrical network [12] or the electricity prices [13]. The current proliferation of small-scale urban PV in buildings [14] and urban wind generators [15] can help home electricity consumers become also producers ("prosumers") [16] using the smart grid (SG) [17,18] and micro-grids (µ−Gs) [19] concepts.…”

Section: Introductionmentioning

confidence: 99%

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Optimizing the Structure of Distribution Smart Grids with Renewable Generation against Abnormal Conditions: A Complex Networks Approach with Evolutionary Algorithms

et al. 2017

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Abstract:In this work, we describe an approach that allows for optimizing the structure of a smart grid (SG) with renewable energy (RE) generation against abnormal conditions (imbalances between generation and consumption, overloads or failures arising from the inherent SG complexity) by combining the complex network (CN) and evolutionary algorithm (EA) concepts. We propose a novel objective function (to be minimized) that combines cost elements, related to the number of electric cables, and several metrics that quantify properties that are beneficial for SGs (energy exchange at the local scale and high robustness and resilience). The optimized SG structure is obtained by applying an EA in which the chromosome that encodes each potential network (or individual) is the upper triangular matrix of its adjacency matrix. This allows for fully tailoring the crossover and mutation operators. We also propose a domain-specific initial population that includes both small-world and random networks, helping the EA converge quickly. The experimental work points out that the proposed method works well and generates the optimum, synthetic, small-world structure that leads to beneficial properties such as improving both the local energy exchange and the robustness. The optimum structure fulfills a balance between moderate cost and robustness against abnormal conditions. Our approach should be considered as an analysis, planning and decision-making tool to gain insight into smart grid structures so that the low level detailed design is carried out by using electrical engineering techniques.

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Section: Encoding Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimizing the Structure of Distribution Smart Grids with Renewable Generation against Abnormal Conditions: A Complex Networks Approach with Evolutionary Algorithms

et al. 2017

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“…Kim et al (2015) conducted a comprehensive analysis of the economic and environmental performance of the geothermal system according to the entering water temperature from life cycle perspective, using the GLHEPro software program [115]. (4) Wind turbine system: As the wind speed is a very important factor for the wind turbine system, most of the previous studies on it analyzed its technical performance by applying it to the rooftop or to a high-rise building (refer to Table 10) [120][121][122][123][124][125][126][127][128]. Li et al (2013) assessed the feasibility of implementing the wind turbine system in a tall building through wind tunnel tests.…”

Section: Part B-1: Renewable Energy (Re)mentioning

confidence: 99%

Advanced Strategies for Net-Zero Energy Building: Focused on the Early Phase and Usage Phase of a Building’s Life Cycle

Hong

Kim

et al. 2017

Sustainability

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Abstract:To cope with 'Post-2020', each country set its national greenhouse gas (GHG) emissions reduction target (e.g., South Korea: 37%) below its business-as-usual level by 2030. Toward this end, it is necessary to implement the net-zero energy building (nZEB) in the building sector, which accounts for more than 25% of the national GHG emissions and has a great potential to reduce GHG emissions. In this context, this study conducted a state-of-the-art review of nZEB implementation strategies in terms of passive strategies (i.e., passive sustainable design and energy-saving technique) and active strategies (i.e., renewable energy (RE) and back-up system for RE). Additionally, this study proposed the following advanced strategies for nZEB implementation according to a building's life cycle: (i) integration and optimization of the passive and active strategies in the early phase of a building's life cycle; (ii) real-time monitoring of the energy performance during the usage phase of a building's life cycle. It is expected that this study can help researchers, practitioners, and policymakers understand the overall implementation strategies for realizing nZEB.

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“…There has been some progress made from independent and collaborative studies related to characterization of turbulence and power curves of SWTs in the built environment [7][8][9], structural behaviour of wind turbines and design optimization [10,11], numerical analyses on turbine placement and effect of buildings/obstacles on oncoming wind profile [12][13][14]15]. Researchers at Murdoch University have studied the characteristics of the urban wind on a 1.5 kW swift wind turbine installed on the rooftop of a Bunnings Ltd. warehouse in the suburb of Port Kennedy (PK) in Perth Western Australia [3].…”

Section: Introductionmentioning

confidence: 99%

The suitability of the IEC 61400-2 wind model for small wind turbines operating in the built environment

Evans

Bradney

et al. 2017

Renew. Energy Environ. Sustain.

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Abstract. This paper investigates the applicability of the assumed wind fields in International Electrotechnical Commission (IEC) standard 61400 Part 2, the design standard for small wind turbines, for a turbine operating in the built environment, and the effects these wind fields have on the predicted performance of a 5 kW Aerogenesis turbine using detailed aeroelastic models developed in Fatigue Aerodynamics Structures and Turbulence (FAST). Detailed wind measurements were acquired at two built environment sites: from the rooftop of a Bunnings Ltd. warehouse at Port Kennedy (PK) (Perth, Australia) and from the small wind turbine site at the University of Newcastle at Callaghan (Newcastle, Australia). For both sites, IEC 61400-2 underestimates the turbulence intensity for the majority of the measured wind speeds. A detailed aeroelastic model was built in FAST using the assumed wind field from IEC 61400-2 and the measured wind fields from PK and Callaghan as an input to predict key turbine performance parameters. The results of this analysis show a modest increase in the predicted mean power for the higher turbulence regimes of PK and Callaghan as well as higher variation in output power. Predicted mean rotor thrust and blade flapwise loading showed a minor increase due to higher turbulence, with mean predicted torque almost identical but with increased variations due to higher turbulence. Damage equivalent loading for the blade flapwise moment was predicted to be 58% and 11% higher for a turbine operating at Callaghan and PK respectively, when compared with IEC 61400-2 wind field. Time series plots for blade flapwise moments and power spectral density plots in the frequency domain show consistently higher blade flapwise bending moments for the Callaghan site with both the sites showing a once-per-revolution response.

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Estimation of wind power generation in dense urban area

Cited by 130 publications

References 44 publications

Optimizing the Structure of Distribution Smart Grids with Renewable Generation against Abnormal Conditions: A Complex Networks Approach with Evolutionary Algorithms

Optimizing the Structure of Distribution Smart Grids with Renewable Generation against Abnormal Conditions: A Complex Networks Approach with Evolutionary Algorithms

Advanced Strategies for Net-Zero Energy Building: Focused on the Early Phase and Usage Phase of a Building’s Life Cycle

The suitability of the IEC 61400-2 wind model for small wind turbines operating in the built environment

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