Comparing the International Knowledge Flow of China’s Wind and Solar Photovoltaic (PV) Industries: Patent Analysis and Implications for Sustainable Development

Climate-relevant technologies, like wind and solar energy, are crucial for mitigating climate change and for achieving sustainable development. Recent literature argues that Chinese solar firms play more active roles in international knowledge flows, which may better explain their success in international markets when compared to those of Chinese wind firms; however, empirical evidence remains sparse. This study aims to explore to what extent and how do the international knowledge flows differ between China’s wind and solar photovoltaic (PV) industries? From a network perspective, this paper develops a three-dimensional framework to compare the knowledge flows in both explicit and tacit dimensions: (i) inter-country explicit knowledge clusters (by topological clustering of patent citation network); (ii) inter-firm explicit knowledge flow (patent citation network of key firms); and, (iii) inter-firm tacit knowledge flow (by desktop research and interviews). The results show that China’s PV industry has stronger international knowledge linkages in terms of knowledge clustering and explicit knowledge flow, but the wind power industry has a stronger tacit knowledge flow. Further, this study argues that the differences of global knowledge links between China’s wind and solar PV industries may be caused by technology characteristics, market orientation, and policy implementation. This suggests that these industries both have strong connections to global knowledge networks, but they may involve disparate catch-up pathways that concern follower-modes and leader-modes. These findings are important to help us understand how China can follow sustainable development pathways in the light of climate change

About using the minimum energy dissipation to find the steady-state flow distribution in networks

[EN] The incorrect analysis of the flow distribution through HVACduct-networks has an economical and environmental impact.The existence ofnegativehead loss coefficients at branched junc-tions poses a difficulty. However the dissipated energy is inher-ently positive and simplifies the solution. The paper exploresthe use of a variational method based on the minimization of thedissipated mechanical energy to find the actual steady-state flowdistribution through a network. To our knowledge, Robert Nivenwas the first to propose/explore this idea but unfortunately dis-carded the method. The paper begins with a short explanation,afterwards extends previous outcomes [1] and ends with an ex-ampleSoto Francés, VM.; Pinazo Ojer, JM.; Sarabia Escrivà, EJ.; Martínez-Beltrán, P. (2019). About using the minimum energy dissipation to find the steady-state flow distribution in networks. Taylor Francis. 1-6. http://hdl.handle.net/10251/1905161

Multiflow Transmission in Delay Constrained Cooperative Wireless Networks

This paper considers the problem of energy-efficient transmission in multi-flow multihop cooperative wireless networks. Although the performance gains of cooperative approaches are well known, the combinatorial nature of these schemes makes it difficult to design efficient polynomial-time algorithms for joint routing, scheduling and power control. This becomes more so when there is more than one flow in the network. It has been conjectured by many authors, in the literature, that the multiflow problem in cooperative networks is an NP-hard problem. In this paper, we formulate the problem, as a combinatorial optimization problem, for a general setting of $k$-flows, and formally prove that the problem is not only NP-hard but it is $o(n^{1/7-\epsilon})$ inapproxmiable. To our knowledge*, these results provide the first such inapproxmiablity proof in the context of multiflow cooperative wireless networks. We further prove that for a special case of k = 1 the solution is a simple path, and devise a polynomial time algorithm for jointly optimizing routing, scheduling and power control. We then use this algorithm to establish analytical upper and lower bounds for the optimal performance for the general case of $k$ flows. Furthermore, we propose a polynomial time heuristic for calculating the solution for the general case and evaluate the performance of this heuristic under different channel conditions and against the analytical upper and lower bounds.Comment: 9 pages, 5 figure

Managing five paradoxes of knowledge exchange in networked organizations: new priorities for HRM?

The life-blood of most organizations is knowledge. Too often, the very mechanisms set up to facilitate knowledge-flow militate against it. This is because they are instituted in a top-down way, they are cumbersome to manage and the bridges of trust fail to get built. In their thirst for innovation, the tendency is for firms to set up elaborate transmission channels and governance systems. As a result, staff are drowned in a deluge of mundane intranet messages and bewildered by matrix structures, while off-the-wall ideas and mold-breaking insights are routinely missed. Added to this is the challenge of operating across professional, cultural, regional and linguistic boundaries, where ways of sharing knowledge differ markedly, even within the same project team. Drawing upon extensive research with scientists in the ATLAS collaboration (a high-energy particle physics experiment comprising 3,500 scientists from 38 countries) we explore five paradoxes associated with knowledge exchange in global networks. Each paradox leads to a proposition which takes the theory and practice of knowledge management in a fresh direction. We conclude by outlining a number of HRM priorities for international knowledge-intensive organizations

KNOWLEDGE-BASED NEURAL NETWORK FOR LINE FLOW CONTINGENCY SELECTION AND RANKING

The Line flow Contingency Selection and Ranking (CS & R) is performed to rank the critical contingencies in order of their severity. An Artificial Neural Network based method for MW security assessment corresponding to line outage events have been reported by various authors in the literature. One way to provide an understanding of the behaviour of Neural Networks is to extract rules that can be provided to the user. The domain knowledge (fuzzy rules extracted from Multi-layer Perceptron model trained by Back Propagation algorithm) is integrated into a Neural Network for fast and accurate CS & R in an IEEE 14-bus system, for unknown load patterns and are found to be suitable for on-line applications at Energy Management Centers. The system user is provided with the capability to determine the set of conditions under which a line-outage is critical, and if critical, then how severe it is, thereby providing some degree of transparency of the ANN solution

Managing five paradoxes of knowledge exchange in networked organizations: new priorities for HRM?

The life-blood of most organizations is knowledge. Too often, the very mechanisms set up to facilitate knowledge-flow militate against it. This is because they are instituted in a top-down way, they are cumbersome to manage and the bridges of trust fail to get built. In their thirst for innovation, the tendency is for firms to set up elaborate transmission channels and governance systems. As a result, staff are drowned in a deluge of mundane intranet messages and bewildered by matrix structures, while off-the-wall ideas and mold-breaking insights are routinely missed. Added to this is the challenge of operating across professional, cultural, regional and linguistic boundaries, where ways of sharing knowledge differ markedly, even within the same project team. Drawing upon extensive research with scientists in the ATLAS collaboration (a high-energy particle physics experiment comprising 3,500 scientists from 38 countries) we explore five paradoxes associated with knowledge exchange in global networks. Each paradox leads to a proposition which takes the theory and practice of knowledge management in a fresh direction. We conclude by outlining a number of HRM priorities for international knowledge-intensive organizations

Management and assessment of performance risks for bioclimatic buildings

Given high energy demands of buildings, developing countries need to be sensitive to the critical role of building energy efficiency in the fight against climate change. Especially in tropical countries where the thermal flow is strong and the lack of electricity distribution networks is a sad reality. The consolidation of this energy efficiency requires the preservation of nature through a harmony between the building and its environment on one hand and an effective evaluation of energy performance on the other hand. Faced with these challenges, the bioclimatic concept is one of the best alternatives to weave this harmony between the building and its environment. Furthermore a meaningful energy performance assessment of buildings based on the knowledge of capitalization with the experience feedback processes can be used to structure the different phases of implementation of the buildings. Firstly, this article presents the general concept of bioclimatic buildings with emphasis on thermal notions that influence thermal comfort inside a building. Secondly, the effort focuses on identifying non-qualities and factors of discomfort whose resolution helps to improve the energy and environmental performance of buildings. This approach supported by land surveys to interview the building actors and users to collect data favourable or not favourable to energy-performance. These data are then processed for the generation of graphical representations used by methods developed on the basis of knowledge and strategies of bioclimatic concepts. After the capitalized knowledge from experience feedback processes allows us to offer corrective solutions and share best practices to address the identified performance problems

On using the minimum energy dissipation to estimate the steady-state of a flow network and discussion about the resulting power-law:application to tree-shaped networks in HVAC systems

[EN] The paper analyses how to compute the steady-state flow distribution through a given network by using the Minimum Entropy Production (MinEP) principle. For isothermal and incompressible flows, this is equivalent to the minimal dissipation of energy. The conditions that make this method equivalent to the conventional one are studied. There must exist a power-law for the energy dissipation (entropy generation) where the exponent must be the same for the whole network. To our knowledge, Niven was the first to get to this result. However he applied MinEP only to parallel pipes and unfortunately discarded it as a general method. The paper shows why it cannot be discarded yet. We discuss the role of the chosen exponent m and its link to the underlying physical phenomena. Moreover it is shown that there is a ¿hidden¿ fixed point value problem that must be studied further. The method introduced in this paper is developed specially for tree-shaped duct-networks which are frequently encountered in HVAC (Heating Ventilation and Air Conditioning) systems. The paper explains briefly what triggered this research; specifically, difficulties related with branched junctions, mainly in return-type networks.Soto Francés, VM.; Pinazo Ojer, JM.; Sarabia Escrivà, EJ.; Martínez, PJ. (2019). On using the minimum energy dissipation to estimate the steady-state of a flow network and discussion about the resulting power-law:application to tree-shaped networks in HVAC systems. Energy. 172:181-195. https://doi.org/10.1016/j.energy.2019.01.060S18119517