Collaborative governance for sustainable development: wind resource ...

Sustainable Development Sust. Dev. 20, 85–97 (2012) Published online 1 June 2010 in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/sd.466

Collaborative Governance for Sustainable Development: Wind Resource Assessment in Xinjiang and Guangdong Provinces, China Daphne Ngar-yin Mah* and Peter Hills The Kadoorie Institute, The University of Hong Kong, Hong Kong

ABSTRACT Wind power is potentially a key energy option that can assist China in meeting its sustainability goals but at present plays only a limited role in the country’s energy system. Wind resource assessment (WRA) has been identified as a key impediment to the further development of this energy source. This paper examines whether collaborative governance can help to improve WRA in China, and if so through what mechanisms. Collaborative initiatives involving WRA in two Chinese provinces, Xinjiang and Guangdong, are reviewed. This suggests that, while the central government has an important role to play, there are many opportunities for locally based collaborative initiatives to function as an alternative, complementary approach to facilitate WRA. Contextual elements such as local resources (including leadership and local knowledge) and governance structures (such as social networks) are identified as key conditions facilitating collaboration. The paper concludes that a broader perspective placing more emphasis beyond the central government in capacity building for WRA is required to enhance the prospects for the transition to a more sustainable energy system in China. Copyright © 2010 John Wiley & Sons, Ltd and ERP Environment. Received 14 December 2009; revised 13 February 2010; accepted 1 March 2010 Keywords: China; wind energy; wind resource assessment; sustainable energy; collaboration; governance

Introduction

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ENEWABLE ENERGY, INCLUDING WIND ENERGY, ALTHOUGH CAPABLE OF MAKING A SIGNIFICANT CONTRIBUTION TO sustainable development, has yet to reach its full potential in either developed or developing countries (Jefferson, 2008). The gaps in current knowledge about how and why the concept of sustainable development is difficult to implement remain, and particularly so in the context of China. This paper focuses on the development of wind energy in China as an example of an energy technology that has the potential to contribute to the sustainability transition in a key sector of the economy. Our specific focus is the issue of wind resource assessment (WRA) – the theoretical and empirical analysis undertaken to provide estimates of the wind energy potential of particular regions, localities or sites. We explore the linkages between the

* Correspondence to: Daphne Ngar-yin Mah, Senior Research Associate, The Kadoorie Institute, The University of Hong Kong, 8/F Tsui Tsin Tong Building, The University of Hong Kong, Pokfulam Road, Hong Kong.E-mail: [email protected] Copyright © 2010 John Wiley & Sons, Ltd and ERP Environment

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theoretical concept of collaborative governance and the empirical development of WRA in two Chinese provinces, Xinjiang and Guangdong, and examine whether and how collaborative governance can facilitate WRA in China. Wind energy has been regarded as one of the key energy options for achieving sustainability goals in both developed and developing countries (WWEA, 2009). China has also been increasing its investment in wind energy. The country’s energy supply system dominated by coal and its energy consumption patterns are widely recognized as unsustainable, raising issues of energy security, climate change impacts, environmental degradation and social instability (Economy, 2007; MIT, 2007; Pozon and Mench, 2007). Wind energy has the potential to become a mainstream, rather than just a supplementary, energy source (US Department of Energy (DOE), 2008). It is relatively cost competitive with conventional energy technologies (IEA, 2007). Experience elsewhere has also demonstrated that the wind power industry has the potential to generate green jobs and to revive local economies (BMU, 2007; US Department of Energy (DOE), 2008). Wind energy also has an important role to play in rural electrification (GWEC, 2009b; NREL, 2004a, 2004b; Wang et al., 2006). Following the enactment of China’s Renewable Energy Law in 2005 and the introduction of a number of important supportive policies that now cover pricing, technology, grid access and other policy domains, wind energy installations have greatly increased in recent years. China’s installed capacity of wind power doubled each year from 2004 to 2009, and reached 24 GW by the end of 2009 (CHECC, 2010; Martinot and Li, 2007). The country now ranks third in the world in terms of the size of its wind power sector (CHECC, 2010). The outlook for wind energy in China is however clouded by various factors. It remains a fringe energy source, contributing only 1.4 percent of the country’s total electricity generation and accounting for just 2.8 percent of total installed generating capacity (end 2009) (CHECC, 2010; NDRC, 2010). Wind resources vary over time and location (Reeves, 2003). A good understanding and estimation of wind resources is therefore essential to the development process, from energy planning to site planning and predictions of the economic viability and financial risks of potential wind farm projects (Singh et al., 2006). However, WRA is a difficult process that demands good siting of anemometer towers, appropriate choice of measurement techniques and modelling procedures, trained staff, quality equipment and thorough data analysis techniques (NREL, 1997). The lack of high-quality WRA has been identified as one of the major barriers to the development of wind energy in China (Wang et al., 2009). Collaborative governance has grown in importance as a strategy for achieving sustainability goals in part due to its multi-sector and bottom-up approach to problem-solving. Understanding whether collaborative governance can strengthen the capacity of China in the task of WRA is therefore of importance to policy-makers and investors. This paper uses the concept of collaborative governance to explore and evaluate the effectiveness of WRA in two Chinese provinces, Xinjiang and Guangdong. Specifically, we discuss whether collaborative governance facilitates WRA, and if so how it does so.

Wind Resource Assessments in China WRAs were first undertaken in China in the 1970s by the central government. Three national wind resource surveys were completed in 1978, 1988 and 2006 respectively (SDPC and SPC, undated; CAMS, 2010; CMA, 2006). The third national survey concluded that total wind energy potential on land is 4300 GW: of this, 297 GW available to be exploited in practice (CMA, 2006). The survey also estimates that the on-land wind resource in China is rich enough to produce electricity which is approximately 22 times greater than possibly generated by the Three Gorges Hydroelectricity Power Station (CMA, 2006). To date, the Chinese government has produced national wind resource maps, including mean annual wind speeds, using data from over 2500 meteorological stations across China (Interview BJ/01/2006). As China has committed itself to increasing the output of wind energy (Martinot and Li, 2007), the government established the Centre for Wind and Solar Energy Resources Assessment under the China Meteorology Administration (國家氣象局 Guojia Qixiangju; CMA) in 2006 (CCChina, 2006). The establishment of the centre is a major institutional development to strengthen the capacity of the government in WRA. Under the leadership of the National Development and Reform Commission (NDRC) and Ministry of Finance, the CMA started the fourth major national WRA initiative in 2007. This is officially called the Wind Resource Copyright © 2010 John Wiley & Sons, Ltd and ERP Environment

Sust. Dev. 20, 85–97 (2012) DOI: 10.1002/sd

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Detailed Survey and Evaluation Project (风能资源详查和评价项目 Fengneng Ziyuan Xiangcha he Pingjia Xiangmu) (CMA, 2009a). This initiative aims to establish a national network of wind monitoring stations consisting of 400 anemometer towers, ranging from 70 to 100 meters in height, to collect data (CMA, 2009a; Interview BJ/01/2006). By July 2009, 393 anemometer towers had already been built in 28 provinces (Wang and Hu, 2009). WRA in China is largely managed in a state-directed, top-down, hierarchical manner. The national wind resource surveys have been conducted by the central government at the national level with the key responsible agencies including the then National Meteorology Bureau and its successor, the CMA. The national surveys used data supplied by the extensive network of sub-national meteorological bureaus across China (CMA, 2009b). The active involvement of the NDRC and the Ministry of Finance in the on-going fourth national survey reflects attempts to introduce new institutional arrangements at the top central level to strengthen the capacity to undertake WRAs. The fourth national WRA aims to establish a centralized infrastructure to facilitate the collection, management, analysis, use and sharing of wind data, and to use the database to generate a national wind atlas. While the central government has a pivotal role in WRA, there has also been collaboration between the state and external parties including international organizations and international consultancy firms as well as other countries (Badger, 2009; CRESP, 2008; Martinot and Wallace, 2003; Wallace et al., 2006). However, such collaboration with actors outside the state apparatus has remained limited and largely peripheral to the WRA process. Independent institutions providing professional WRAs, although common in many developed countries, have not been active in China. In-house WRAs conducted by Chinese wind farm developers themselves are however more common (Interview GD/03/2007). Despite the state-led model for WRA, which has made some significant progress over the years, several key issues remain unresolved. These are the following. Data inaccuracies. The accuracy of WRA is a major issue affecting the future development of wind energy in China. Accuracy is of paramount importance because the energy potential of wind is proportional to the wind speed cubed (Christiansen et al., 2006). While it is commonly believed that the national surveys have underestimated the scale of wind resources in China, there are cases of individual wind farms where the micro-siting assessment has overestimated the resources available. A wind farm in Guangdong, for example, has reported a 30 percent discrepancy between the projected and actual energy yield (Interview GD/05/2008). Such inaccuracies in the estimation of wind resources in China can be attributed to three factors. First, the Chinese national surveys tend to underestimate the wind resource because they use data from meteorological stations that monitor wind data at a standard height of 10 meters. This is a key factor affecting the accuracy of WRA because wind turbine rotor hub heights are usually between 80 and 100 meters and wind speed typically increases with height above ground (Hau, 2006; Reeves, 2003). Second, the meteorological masts are usually located far from the potential wind-farm sites as these locations were chosen for the purpose of weather forecasting rather than specifically for WRA (Interview BJ/01/2006). Third, some in-house WRAs conducted by Chinese wind farm developers lacked accreditation by professional and independent third parties (Interviews GD/03/2007, GD/05/2008). Delays in responding to the needs for WRA. State-directed WRA efforts have exposed various problems including the lack of continuous assessment and evaluation of data, relatively slow work progress, and tardiness in responding to new needs. The three national wind resource surveys were conducted in the 1970s, 1980s and 2000s respectively (Interview BJ/01/2006). The time lags, which are decade long between the surveys, indicate the lack of continuous assessment of wind resources. Progress with the on-going fourth national WRA initiative has been relatively slow, partly because high-level coordination across the central agencies, in particular between the NDRC and Ministry of Finance, tends to be time consuming. This problem can be illustrated by the funding of the fourth national WRA. A budget of approximately 200 million yuan (1 US$ = Yuan 6.83 approx. at February 2010) for the WRA was approved in 2006 but was only fully allocated to the CMA by the end of 2008 (CMA, 2009a; Interview BJ/03/2009). Copyright © 2010 John Wiley & Sons, Ltd and ERP Environment

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D. Ngar-yin Mah and P. Hills Non-state resources remain largely untapped. While meteorological stations across China have provided useful data for the national wind resource surveys, the state-managed WRA system has only limited access to and integration with the vast data system that exists in the economic sector. Outside the state system, additional detailed wind measurements have been conducted at specific sites by potential wind farm developers to provide more reliable predictions with which to assess the financial viability of projects. There are about 1600 such wind monitoring masts across China, but as many as 1500 of them have been built and are owned by enterprises. Only about 100 have been built by the meteorology agencies. The CMA therefore has access to data from only about 100 of those masts, not the majority of the wind monitoring sites (Interview BJ/01/2006). There is therefore a clear boundary between the state and the private sector in WRA. Limited public access to information. Although published isopleth maps of wind energy across China are publicly available (Singh et al., 2006), there is limited public access to the more detailed wind resource data available in local meteorology bureaus. Wind resource data held by the National Meteorology Bureau and the Meteorology Institute were previously available on a fee-paying basis (Singh et al., 2006). Although data produced by state agencies have become increasingly transparent in recent years as a result of the central policy to enhance information transparency (Interview BJ/01/2006), non-state actors have still experienced limited access to the state-held data. Access to the data is sometimes subject to the discretion of individual local bureaus (Interviews GD/01/2007, GD/02/2006). Wind data from the economic sector is usually confidential and is not available in the public domain. The WRA system in China is essentially state directed, hierarchical and characterized by a clear boundary between the state and the economic sector. There has been involvement of actors outside the state apparatus, but this tends to be ad hoc in nature, and limited in both scale and continuity. Resources for assessments are however relatively abundant, in terms of the availability of wind data and funding, in the economic sector. Under these circumstances, while the national wind resource surveys are useful for general wind energy appraisals, they have major weaknesses. For the decision-makers these surveys are too rough to be used to set wind targets at the national or provincial levels (QXB, 2009). For potential wind farm developers, these surveys also fail to address site-specific problems because there is a poor understanding of the characteristics of extreme weather such as typhoons and sand storms and their impact on turbine performance (Interview BJ/02/2005).

Despite these problems at the national level, locally based collaborative initiatives to facilitate WRA have emerged in some Chinese provinces. The experience of Xinjiang highlights the workings of an enterprise-led collaboration, while the development in Guangdong shows bottom-up collaborative initiatives between an NGO, a local university and an international consultant. Before we proceed to the detailed case studies of Xinjiang and Guangdong, we shall first discuss the use of collaborative governance as an analytical framework and the methodology of this paper in the sections that follow.

Collaborative Governance and Wind Resource Assessment Collaborative Governance: a Normative Perspective Collaborative governance has received growing interest from scholars and policy-makers as an innovative strategy to respond to many different types of problem in contemporary societies (Huxham and Vangen, 2005). Studies of collaborative governance have been undertaken across a wide spectrum of major public policy domains, from the environment (de Bruijn and Hofman, 2002; Hartman et al., 2002) to public health (Roussos and Fawcett, 2000), and housing (Boyle, 1989). In the studies on environment and sustainability, collaboration has grown in importance as a key element for sustainable development (Lozano, 2007). Collaborative governance is defined as a governing arrangement where public agencies engage non-state stakeholders with the aim of making or implementing public policy or managing public assets (Ansell and Gash, 2008). It has its roots in the theoretical perspective of governance. The central theoretical insight of the governance perspective is the shift from government to governance. In view of the traditional state’s limited ability to cope with Copyright © 2010 John Wiley & Sons, Ltd and ERP Environment

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social problems, governing needs to move away from a reliance on the mere capacity of the formal state apparatus to a policy-making system that is more decentralized, flexible and inclusive (Fischer, 2006; Hall, 1993). Specifically, collaborative governance involves a process in which diverse stakeholders are engaged to bring together their individual inputs for collective goals (Cordery, 2004; Hartman et al., 2002). The essential features of collaborative governance include the engagement of a broader spectrum of interdependent actors beyond national government (i.e., including local governments and non-state actors such as business organizations and local communities) (Ansell and Gash, 2008; Cordery, 2004; Cuthill, 2002; Eweje, 2007), a strong emphasis on information sharing, respect for dissenting views and a commitment to a long-term interacting process (Thomson and Perry, 2006), and the achievement of not only individual ends but also additional, shared benefits (Thomson and Perry, 2006). What encourages or drives people, organizations or governments to enter into collaboration? The literature suggests that, as individual efforts have limits in addressing problems, collaboration allows opportunities for actors from various sectors to combine their complementary resources and expertise (Widdus, 2001). The main benefits of collaboration include creating trusting relationships that are needed to address complex societal problems, achieving efficiency by coordination and sharing costs or risks (Huxham, 2000). Collaborative efforts, however, can be jeopardized by different forms of inertia. Institutional inertia and disciplinary inertia, for example, can inhibit cross-sectoral or transdisciplinary collaboration (Rickson et al., 1990). Power imbalances or information asymmetry may also undermine the effectiveness of collaborative efforts during the bargaining process (Huxham and Vangen, 2005; Koontz et al., 2004; Yoder, 1999). Furthermore, consensus decision practices that are central to collaboration can limit opportunities to make bold, innovative policy recommendations. An incremental approach, which may not be sufficiently decisive to meet the needs of the sustainability transition, may instead drive the decision-making process (Koontz et al., 2004; Shirk, 1993; Wright, 2000; Yan, 2001; Yoder, 1999).

Collaborative Governance as a Framework for Understanding WRA WRA is the statistical analysis of wind power density and wind energy in a given region or location (Mani and Rangarajan, 1996). The critical information is the speed and direction of the wind, its consistency and the factors influencing wind characteristics at any particular location (Mani and Rangarajan, 1996). WRA is more than a science. The process for WRA, from data collection to management, analysis and the use and sharing of wind data, can be viewed as a governing process. Collaborative governance is a relevant conceptual framework to analyze WRA in China for a number of reasons. WRA is complex, large scale and subject to numerous uncertainties. It is complex because it involves different measurement and analysis techniques, and falls into different disciplines and across sectors. For example, wind data can be obtained from in situ measurement, that is from meteorological masts, or can be retrieved from satellite data (NREL, 1997). Furthermore, wind data may not rest solely in the hands of the state. Wind farm developers and wind turbine manufacturers, for example, may obtain useful wind data from their own wind towers. The complexity of WRA implies that a multi-actor, multi-technique and transdisciplinary approach is required to conduct the task more efficiently and effectively. Effective WRA is also an enormous task. It is a multi-scale and multi-location activity, implying a major investment of time, and financial and human resources. The issue of scale is of particular concern because WRAs conducted at different levels (e.g. from a macro-scale national or regional assessment to a meso-scale and to a site-specific micro-siting scale) are highly complementary (Hau, 2006; NREL, 1997). Because of its scale and complexity, WRA also involves many uncertainties. The complex interactions across a wide spectrum of actors make simple, linear models of cause and effect invalid (Voß and Kemp, 2007). Rather, in such uncertain situations, feedback becomes important (Voß and Kemp, 2007). An undesirable implication associated with uncertainty is that actors need to make choices without adequate information to assess, for example, the expected outcomes of a wind farm investment (Haas, 2001). Investigating the potential role of collaborative governance in enhancing the effectiveness and quality of WRA in China may contribute to a better understanding of the opportunities and constraints associated with the sustainability transition in the country. Literature on collaboration in the context of the sustainability transition of energy Copyright © 2010 John Wiley & Sons, Ltd and ERP Environment

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systems has been limited, and is particularly so in the context of China. The complex mechanisms of how collaboration works or does not work, particularly at the local level, need to be explored. We adopt the concept of collaborative governance as an analytical framework to guide our analysis of WRA initiatives in two Chinese provinces. The framework focuses on the interactions between key actors, the form of these interactions (i.e. the models), the conditions that appear to make collaboration work or not work (i.e. the positive and negative conditions) and the outcomes of these collaborative interactions.

Methodology This study adopts a comparative case-study methodology to examine and contrast the process of collaborative initiatives in relation to wind resource assessment in Xinjiang and Guangdong. A case-study approach is well suited to provide answers to ‘how’ and ‘why’ questions (Yin, 2003), and is therefore a useful research methodology to understand the workings of collaborative governance. Through studying the two cases of Xinjiang and Guangdong our aim is to increase generalizability, and to deepen understanding and enhance explanation of the mechanism of collaborative governance (Miles and Huberman, 1994). Specifically, the comparative analysis of the two cases provides a better understanding of the local diversity of collaborative initiatives, how and why collaboration may work, and why it may not. It also illuminates the prospects for and limits to collaborative initiatives in the Chinese context. Xinjiang and Guangdong are two of the 34 provincial-level administrative units in China’s five-tiered hierarchical politico-administrative structure (Qi et al., 2008; OECD, 2005). Both provinces have experienced significant development of wind energy in recent years (CHECC, 2008). They exhibit significant differences in their political, economic, social and environmental characteristics. Xinjiang is an autonomous region that is economically backward and politically unstable, and has been under the close control of the central government (Becquelin, 2000; Chung, 2003; Shichor, 2005). In contrast, Guangdong is one of the wealthiest Chinese provinces (HKTDC, 2008) and has enjoyed a higher level of policy autonomy granted through the ‘special policy and flexible measures’ (Cheung, 2002). However, both Xinjiang and Guangdong face similar constraints under central control. The extent of the discretionary powers of provinces, the emergence of civil society and the roles of economic actors in Chinese provinces are still largely subject to central control (Li, 1997; OECD, 2005). These broad similarities in the governance landscape across China therefore create a comparative setting that holds the cross-case comparison of Xinjiang and Guangdong. The case studies presented here draw on data and information derived from desktop research, semi-structured interviews and field visits. Thirteen semi-structured interviews with key informants were conducted in Beijing, Xinjiang and Guangdong between 2005 and 2009. A total of ten informants were interviewed and three of them were interviewed twice. The informants were either directly involved in collaborative initiatives or were knowledgeable about wind resource assessment and wind energy policies in China. Among them, five are government officials, two are from enterprises, two are academics and one is a civil society actor. All but two of the interviews were face-to-face interviews while the remaining two were conducted by telephone. As some interviewees agreed to be interviewed only anonymously, this study indicates interviews by number. The first two letters indicate the location (BJ for Beijing, XJ for Xinjiang and GD for Guangdong), the two digits indicate the interview numbers, and this is followed by the year of the interviews. The list of interviews is provided in the appendix. Drawing on the data gathered, we first offer a description of the key processes and outcomes of the collaborative initiatives in the two case studies. We then identify key mechanisms of collaboration.

Wind Resource Assessments in Chinese Provinces Xinjiang: an Enterprise-Led Model Located in the far northwest of China, Xinjiang possesses some of the best wind resources in the country. It is also the location of the Danbancheng Wind Farm, one of the largest wind farms in Asia. Goldwind, a Copyright © 2010 John Wiley & Sons, Ltd and ERP Environment

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leading domestic wind turbine manufacturer in China, is based in Urumqi, the capital of the province (CHECC, 2008). The total installed capacity of wind energy in Xinjiang reached 577 MW by the end of 2008 (Shi, 2009). As in the rest of the country, official wind resource data are limited in Xinjiang. The official estimate which put Xinjiang’s wind resources at 120 GW (Interviews XJ/03/2007, XJ/04/2008) is based on the findings of the third national wind resource survey completed in 2006 and is widely perceived to be an under-estimate. The fourth national wind energy survey is ongoing, but the progress has been relatively slow. By the end of 2008, none of the 17 anemometer towers approved by the CMA had been set up in Xinjiang (Interview XJ/05/2008). It was only in June 2009 that all the towers were finally erected (Lin and Wang, 2009). Because of the relatively long history of wind farms in the region (with more than 400 wind turbines in operation), data held by local wind farm developers are relatively detailed (CHECC, 2008; Interview XJ/01/2008). It is against this backdrop that in late 2007 the Xinjiang Development and Reform Commission (DRC) initiated a collaborative project with XJWind to conduct a study of local wind resources and wind energy plans. In contrast to the conventional state-led model of WRA, this collaborative exercise is significant in various aspects. First, it is characterized by an enterprise-led model, in which XJWind played a pivotal role. Although XJWind was commissioned by the Xinjiang DRC to carry out this task, this project is collaborative in nature as the local government has not paid the company for the service. XJWind was willing to work with the local DRC on a goodwill basis in the absence of any financial reward. Such a commitment from XJWind was in part a reflection of the company’s aspiration to contribute to the development of wind energy in the region. It was also economically feasible for XJWind to do so because many of the data could be derived from its own existing wind energy monitoring masts and therefore involved minimal additional costs (Interview XJ/05/2008). XJWind also managed to make informal arrangements with other local wind farm developers and with Goldwind for free data-exchange. Such informal deals were possible largely due to the social networks and trust that XJWind had established with the other local developers over the years. As a shareholder of Goldwind, XJWind also had access to the data owned by this leading wind turbine manufacturer in China. Some data were also obtained from the Xinjiang Meteorology Bureau free of charge (Interview XJ/05/2008). Various advantages were derived from this enterprise-led collaboration. First, cost-sharing and efficiency were achieved. The WRA has been conducted in an efficient and cost-effective manner, with limited additional costs incurred by the Xinjiang government and the collaborating parties. The study only took a few months to complete and was subsequently utilized in the policy-making process. The study was commissioned in late 2007, completed in early 2008, and the findings were used by the Xinjiang DRC in mid 2008 to provide evidence to support its new wind energy plans (Interview XJ/05/2008). Second, the collaboration has enhanced policy legitimacy for more ambitious wind targets for Xinjiang. The findings of the WRA conducted by XJWind have become useful evidence for the Xinjiang DRC to formulate much more ambitious wind energy plans. In mid-2008, the Xinjiang DRC prepared a master plan entitled ‘Medium- and long-term wind energy plan in Xinjiang for the 11th Five Year Plan and by 2020’ (新疆’十一五’及 2020 年风电发展规划 Xinjiang Shiyiwu ji Erlingerlingnian Fengdian Fazhan Guihua). If the new plans are approved by the central government, the provincial wind energy target by 2020 would be at least 35 GW, substantially higher than the original target set in 2006 at 1.46 GW (Interviews XJ/02/2008, XJ/05/2008). How, then, did this collaboration work in the absence of both substantial state funding and state ownership of most of the wind data? Several local conditions were crucial in contributing to its success. In terms of local resources, local leadership and local knowledge were of vital importance. XJWind has demonstrated its leadership in mobilizing other stakeholders to collaborate. XJWind has long been a local wind energy advocate and its commitment and perseverance in wind energy development partly explained why it was able to mobilize other stakeholders to collaborate. The social networks and trusting relationships established over the years between XJWind and other stakeholders, including the local government, other local wind farm developers and Goldwind (a wind turbine manufacturer), have created the required governance structure for the collaboration to take place. Another key local resource for the collaboration was local knowledge relating to wind data. Wind resource data once scattered across a number of local wind farm developers and local government agencies was assembled, synthesized and analyzed by XJWind, and subsequently turned into valuable local knowledge used by the Xinjiang DRC in formulating new wind energy plans. This pool of local wind data is a valuable complement to the official Copyright © 2010 John Wiley & Sons, Ltd and ERP Environment

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data in part because they provide relatively long-term perspectives on the energy yield from the existing wind turbines, and in part because they can better reflect local wind energy characteristics.

Guangdong: a Bottom-Up, Society–University–Enterprise Model Possessing an extensive coastline (Cheung, 2002), Guangdong enjoys excellent access to wind energy resources in many coastal areas. By the end of 2008, the total installed capacity of wind energy in Guangdong had reached 367 MW (Shi, 2009). A distinctive feature of collaboration in WRA in Guangdong has been its bottom-up approach, with important roles played by non-state rather than state actors. These non-state actors included Greenpeace China, Garrad Hassan (an international wind energy consultancy firm), Sun Yat-sen University (a local university) and Honghaiwan Wind Farm (a local wind farm developer). Two major collaborative WRA initiatives in Guangdong were identified. The first was initiated and led by Greenpeace China in 2004. Greenpeace China commissioned Garrad Hassan and the Research Centre of Wind Resource under the School of Engineering at Sun Yat-sen University (中山大学工业院风资源研究中心, RCWR) in Guangzhou to conduct a WRA for Guangdong. A major output of the collaboration was the release of a report entitled Wind Guangdong in 2005 by Greenpeace China. The report estimated that the wind energy potential in Guangdong is very large and could reach 20 GW – approximately one-third of the total installed capacity of the province’s power system in 2007 (Greenpeace, 2005). This collaboration turned out to be much more than a conventional commissioning experience. It enabled knowledge transfer and resource pooling between Garrad Hassan and the RCWR to take place. There was a transfer of western WRA technology and experience to China from Garrad Hassan through academic conferences and lectures offered by a number of experts from the company. Particularly useful knowledge gained by the RCWR was how to better integrate and adjust the model parameters with feedback from field experience of wind farms (Interview GD/03/2007). Another important contribution of this society–university collaboration was less tangible but equally important. The recognition by Garrad Hassan of the work of the RCWR has strengthened the confidence of this newly established centre in its research agenda and strategy (Interviews GD/01/2007, GD/03/2007). In this sense, the recognition that RCWR as a young research institute received from internationally recognized experts has strengthened the capacity of the RCWR to continue to work in this field. Although the RCWR did not have a clear intention to become an independent institution in the near term, the experience and knowledge gained through this collaboration was nevertheless a valuable step in its development process. Another major initiative in Guangdong was an enterprise–university collaboration between Shanwei Honghaiwan Wind Farm and the RCWR. This started in 2005 as an informal collaboration based on personal networks. The wind farm developer wanted to establish why the actual energy yield from the wind farm was substantially lower – about 30 to 40 percent – than the projected figure. Building on the personal ties between the team leader of the RCWR and the senior management of the wind farm, the two bodies collaborated to undertake a validation study of the WRA for this specific site. An exchange of wind resource data took place between the collaborating partners (Interviews GD/04/2008, GD/05/2008). The findings of the validation studies were found to be mutually useful to both parties. The wind farm developer found that the work conducted by the RCWR, which integrated different wind data-sets and different techniques, offered a more accurate and comprehensive analysis of the site’s wind resources. The RCWR also gained from this collaboration, as the in situ wind energy measurements owned by the wind farm developer allowed it to gain field experience and help it to fine-tune its computing parameters (Interviews GD/04/2008, GD/05/2008). No monetary payment was involved in this collaboration. Mutual trust and resource exchange were the major preconditions and incentives for this example of collaboration (Interview GD/04/2008).

Collaborative Governance as a Strategy for Enhancing Wind Resource Assessments This paper contributes to research on collaborative governance for sustainable development through its focus on the conceptual and practical linkages between the concept of collaboration and WRA in China. WRA raises a Copyright © 2010 John Wiley & Sons, Ltd and ERP Environment

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number of interesting issues. The availability of accurate resource assessments is essential for the efficient and cost-effective development of the sector. While the existing state-led WRA model in China has demonstrated its strengths, it has also revealed certain weaknesses at the central government level. The state-led model was not able to produce accurate data, respond quickly or mobilize resources that were actually available from non-state sources. An examination of the recent development of WRA in Xinjiang and Guangdong suggests that a collaborative governance approach has facilitated WRA. This paper has identified some of the potential benefits and explained the mechanisms of collaboration. Our findings suggest that relationships forged between enterprises, civil society and the state enhanced WRA capacity at the local level. The benefits of collaboration were achieved by combining different resources and skills that are located both within and outside the state. These observations reinforce one of the key insights of the theory of governance, namely that because of the limits of the traditional state new forms of governance and more sophisticated state–market–society interactions are needed to enhance the capacity to govern (Kooiman, 1993; Meadowcroft, 2008; Scharpf, 1997). What, then, are the specific achievements of these WRA collaborative initiatives? Our analysis suggests that local capacity to deal with the task of WRA was enhanced in various ways. Efficiency was improved through cost-sharing and resource-pooling across a wide range of sectors (and even across a number of actors in a particular sector). In Xinjiang the collaboration also appeared to empower the local government to move towards more evidence-based decision-making in setting wind energy targets, which are now more ambitious. The collaboration also appeared to enhance the capacity of university actors to provide independent, professional WRA services. Locally based initiatives do however have some limitations. First, they tend to be ad hoc, small in scale and limited in continuity, and lack long-term institutionalized incentives. Another key observation is the inactive role played by the local meteorology bureaus in the two case studies. Our findings suggest that there are inadequate institutional incentives for the local bureaus to explore new partnership roles in such initiatives. Problems of rent seeking, the issue of disciplinary inertia, and the limits of budgetary and personnel resources in China, which have been extensively documented in the literature (see for example Wedeman, 2003; Wu and Wang, 2007), also existed in our cases and appeared to be key factors inhibiting local meteorological bureaus from participating in the collaborative process. In Guangdong, for example, while the work of the Guangdong Meteorological Bureau and that of the RCWR were highly complementary, the experience of the RCWR suggested that there was inertia in the local meteorological bureau which discouraged it from collaborating on interdisciplinary studies. The RCWR even had difficulties in accessing the government meteorological data for its own studies, as data sharing in the public domain is not effectively institutionalized (Interviews GD/01/2007, GD/02/2006). These observations suggest that, in order to better realize the potential benefits of collaboration in China, there is need to introduce new institutional arrangements to provide the right structures and incentives for the actors, in particular the state actors, to participate. Our findings reflect the specific features of WRA in the context of China, but we suggest that the features of complexity, scale and uncertainty that characterize WRA are also typical of many other environmentally related technological innovations in both developed and developing countries (Australian Government, 2003; Radulovic, 2005). Technological innovations such as hydrogen fuel cell vehicles and solar energy have to deal with complex and large-scale tasks at various phases in the development process from basic R&D to applied research and commercialization (Kemp and Rotmans, 2004). We argue therefore that our findings concerning the relationships between collaboration and governing capacity to deal with complex tasks can be generalized to other technological innovations. Our study also demonstrates that locally based collaboration can take place in different modes in different local contexts. Thus, Xinjiang is characterized as an enterprise-led model while Guangdong takes the form of a society– university–enterprise collaboration characterized by a strong bottom-up process. Despite their differences, these locally based collaborative initiatives appear to confirm some of the key principles of good governance such as reciprocity, transparency and shared responsibility (Chaskin, 2001; Thomson and Perry, 2006). It also appears that the provinces cannot rely on the central state to deal with all the complex tasks associated with the transition to a more sustainable future. Rather, provinces need to formulate their own local, sometimes unique, initiatives to move towards good governance better suited to the sustainability transition. We therefore expect that our Copyright © 2010 John Wiley & Sons, Ltd and ERP Environment

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findings can be generalized to other Chinese provinces in relation to a wide range of environmental and sustainability issues. This paper is not arguing that local collaborative initiatives can completely replace the central government in the context of WRA. The central government performs an important role in high-level coordination and datasharing. The central issue is rather how the central government and the localities can coordinate to better capture the potential additional capacity and value added that can be generated by locally based collaboration. Existing policies for wind energy have tended to overlook the role of localities in enhancing governance capacity. This paper has implications for future research on collaborative governance. The local diversity in the modes of collaboration in our cases suggests that there may be considerable variation in the modes of governance across Chinese provinces. Such a diversity of local governance is interesting from a theoretical point of view. While this study focused on identifying the mechanisms and modes of collaborative initiatives, future research could examine the contextual factors that are important in influencing the processes and outcomes of collaboration in China and elsewhere. Research could also examine different policy domains in the context of sustainable energy, particularly areas such as R&D policy where there is also a need for collaboration between state and non-state actors.

Acknowledgements The authors would like to acknowledge the assistance of the interviewees, particularly Yu Wuming of Xinjiang Wind Energy Company and several other anonymous interviewees in Xinjiang and Guangdong, for providing useful information. Any error in the findings, interpretations and conclusions expressed in this paper are entirely those of the authors.

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Appendix: List of Interviews Code

BJ/01/2006 BJ/02/2005 BJ/03/2009 XJ/01/2008 XJ/02/2008 XJ/03/2007 XJ/04/2008 XJ/05/2008 GD/01/2007 GD/02/2006 GD/03/2007 GD/04/2008 GD/05/2008

Interviewee’s background

A senior official of China Meteorological Administration Yang Fuqiang, Vice President, The Energy Foundation, Chief Representative, Beijing Office A senior official of China Meteorological Administration Zhang Yanjun, Division Head, Electricity Division, The Economic and Trade Commission of Xinjiang Uyghur Autonomous Region A mid-ranking officer, Xinjiang Uyghur Autonomous Region Development and Reform Commission A senior official of the Climate Centre of Xinjiang Uyghur Autonomous Region Same interviewee as in XJ/03/2007 Yu Wuming, former general manager of Xinjiang Wind Energy Company; the deputy director of NWTC; and an expert advisor to the Xinjiang government A senior researcher of the Research Centre of Wind Resource (RCWR) under the School of Engineering at Sun Yat-sen University Same interviewee as in GD/01/2007 A researcher of the Research Centre of Wind Resource (RCWR) under the School of Engineering at Sun Yat-sen University Same interviewee as in GD/03/2007 A senior manager of a wind farm in Guangdong

Types of interview

Date of interview

FI FI

30 Oct 2006 24 Mar 2005

FI FI

22 Oct 2009 21 Oct 2008

FI

22 Oct 2008

FI FI FI

23 Oct 2007 23 Oct 2008 25 Oct 2008

FI

22 Aug 2007

FI FI

7 Jan 2006 22 Aug 2007

TI TI

12 Dec 2008 4 Jan 2008

* The interview formats included face-to-face interview (FI) and telephone interview (TI).

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Sust. Dev. 20, 85–97 (2012) DOI: 10.1002/sd