Statistical analysis of wind characteristics and wind energy potential in Hong Kong
Introduction
Over the past decades, the natural environments in many countries and regions have degraded noticeably in parallel with the rapid industrialization development. Undoubtedly, the excessive consumption of fossil fuels has displayed negative effect to the environments, which led to a variety of environmental problems [20]. Under such circumstances, the necessity to achieve sustainable development has been emphasized constantly on account of increasing awareness and expectation for the better natural environment. As one of the key elements of sustainable development, the exploration and harnessing of renewable energy has attracted broad attention. Currently, the most well-known renewable energy sources include solar, wind, ocean, hydropower and geothermal energy, among which wind energy is arguably one of the oldest sources of energy used by mankind [33].
Wind energy has demonstrated certain superiorities in comparison with traditional energy sources. Wind energy is energized by nature wind, therefore it can be considered as a clean and environmentally preferable source of energy [33]. Wind energy is literally inexhaustible and abundantly available worldwide, which can be used as a promising domestic source of energy in many countries. More importantly, with the continuous development of wind energy technologies, it has become one of the lowest-priced renewable energy sources [33]. Nowadays, the harvesting of wind power has been widely extended throughout the world. The world’s total installed wind power capacity has grown surprisingly fast, from 47.620 GW to 318.105 GW during the period of 2004–2013 [12]. The global annual installed wind capacity has continuously surpassed 35 GW since 2009 [12]. Regionally, China was well-placed to lead the total installed wind capacity with a value of 91.142 GW by the end of 2013, followed by USA and Germany [12]. Nevertheless, in spite of the rapid-growing wind energy industry, it is worth noting that due to the stochastic and variable nature of wind, electricity power generated by wind turbines is generally characterized with high intermittency, which may affect both the power quality and the planning of power systems [28]. Therefore, energy storage systems (ESSs) are usually introduced to facilitate the integration of intermittent wind energy [4]. Efforts have been made to enhance our understanding of energy storage systems. Barton and Infield [3] proposed a probabilistic method to estimate the capability of energy storage. Paatero and Lund [28] focused on the effects of energy storage to reduce the fluctuations of wind power. Beaudin et al. [4] provided a detailed review of several electrical energy storage systems in relation to renewable energy applications, while Díaz-González et al. [14] highlighted the energy storage technologies associated with wind power integration. Sundararagavan and Baker [32] investigated the economic feasibility of energy storage technologies. More recently, Hu et al. [19] introduced a dual-objective optimal charging strategy for two types of Li-ion batteries with attention on the conflict between charging time and charging loss. Shortly after, they also carried out a comparative analysis to evaluate the viability of three electrochemical energy storage systems applied to a hybrid bus powertrain [21].
As a highly developed city and the leading commercial center in Asia, Hong Kong needs a mass of energy supply to support its economic development. With nearly no indigenous fossil resources, Hong Kong demonstrates heavy dependence on external sources [7]. However, due to the gradual reduction of fossil fuel reserves and the environment degradation resulting from fossil fuel uses, the exploration of the available renewable energy source becomes prominently important.
Fortunately, Hong Kong has been benefited from wind power generation from early 2006, with the ever first wind turbine installed in Lamma Island [7]. In fact, investigations on the viability of wind power utilization in Hong Kong have been carried out successively over the years. Lun and Lam [27] derived the two Weibull distribution parameters for three different locations on the basis of a database including 30 years wind speed measurements. The results offered useful information for the further assessment of wind energy potential in Hong Kong. Li [25] presented a feasibility study on the application of offshore wind energy. Based on the analysis of wind data measured at Waglan Island in 1998, the mean wind power density was calculated as 310 W/m2. It showed that offshore wind energy has the potential to be a promising contributor for the city’s electricity supply. Wong and Kwan [34] conducted a comprehensive investigation of the wind characteristics in Hong Kong in relation to wind power. By applying the Weibull distribution model to analyze the wind data available at 13 meteorological stations, they stated that hilltops and offshore islands are the most attractive locations for exploiting wind energy, among which Tai Mo Shan has the highest wind power density with a value of 485 W/m2. Lu et al. [26] proposed a new simulation model to evaluate the potential of wind power generation at a given location. The case study indicates that Waglan Island is a satisfactory location for wind power generation, so are the islands surrounding Hong Kong. More recently, Gao et al. [15] identified the potential offshore wind farm locations in Hong Kong and highlighted four representative offshore wind farms with a total area of 421.48 km2. It was suggested that the potential annual wind power generation in Hong Kong’s offshore wind farms may reach to 112.81 × 108 kW h. Nevertheless, the implementation of wind power generation is still rare in Hong Kong.
This study attempts to explore the wind characteristics at different locations in Hong Kong, and estimate the wind energy potential by means of statistical analysis. The outcomes of the present paper tend to be advantageous for the strategic development of wind energy in later phases. The remainder of this paper is arranged as follows: Section 2 gives a brief introduction about the meteorological stations adopted in this study. Section 3 describes the wind data adjustment method. Section 4 highlights the estimation procedure of Weibull parameters, as well as other key parameters. Detailed interpretations and discussions of the results are addressed in Section 5 and the main findings of this study are presented in Section 6. A flowchart is given in Fig. 1 to illustrate the analysis procedure of this study.
Section snippets
Wind data measurement
For the assessment of wind energy potential, the wind characteristics at the desired locations should be fully understood. The Hong Kong Observatory has established 51 meteorological stations at various locations across the territory to monitor the wind climate. Anemometers are installed at different heights at the stations. In this study, the wind data available at five meteorological stations, namely Waglan weather station, Tai Mo Shan weather station, Hong Kong Observatory station, Cheung
Wind data adjustment
As illustrated hereinabove, the measurement heights at these meteorological stations are highly inhomogeneous. In addition, it is widely recognized that the measurements of wind speed vary with height. Therefore, in order to yield an accurate estimation of wind energy potential, it is imperative to extrapolate the measured wind data to the wind turbine hub height. The correlation of wind speed with height has been investigated extensively and several mathematical and empirical models have been
Wind speed probability distributions
The energy carrying by wind varies as the cube of wind speed. Hence, a well-established understanding of wind characteristics is essential for all aspects of wind energy exploitation [5]. Wind is highly variable, both geographically and temporally. This may inevitably increase the difficulty to give an accurate prediction of wind. The wind speed at any location may be subject to long-term variations, which is mainly attributed to the long-term temperature variations [5]. Unfortunately, the
Results and discussion
Fig. 3 shows the wind rose plots for different measurement sites. The 1-min wind speeds data obtained at anemometer heights are transformed into the turbine hub height (80 m above ground level), while the wind direction is assumed to be invariant with height. As can be seen, the directional distribution of wind speed varies considerably from site to site. For WGL, the wind climate is dominated by the wind originating from 0° (North) to 90° (East). For TMS, the wind direction is somewhat more
Conclusion
It is undoubtedly true that the exploration of renewable energy has gained wide attention due to the increasing awareness and expectation of sustainable development. Wind energy, as one of the most attractive renewable energy sources, has been extensively utilized as an alternative of traditional fossil energy source. In this study, based on the continuous wind data recorded at five meteorological stations with different terrain conditions, the wind characteristics and potential wind energy at
Acknowledgements
The authors would like to express their gratitude to Hong Kong Observatory for the provision of the wind data records and the permission of using the data for this study. The work described in this paper was fully supported by a grant from the Research Grants Council of Hong Kong Special Administrative Region, China (Project No: CityU 118213) and a grant from National Natural Science Foundation of China (Project No. 51478405).
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