Suchergebnisse

The three-rivers headwater region (THRHR) of Qinghai province, China plays a key role as source of fresh water and ecosystem services for central and eastern China. Global warming and human activities in the THRHR have threatened the ecosystem since the 1980s. Therefore, the Chinese government has included managing of the THRHR in the national strategy since 2003. The State Integrated Test and Demonstration Region of the THRHR highlights the connection with social engineering (focus on improving people's livelihood and well-being) in managing nature reserves. Based on this program, this perspective attempts a holistic analysis of the strategic role of the THRHR, requirements for change, indices of change, and approaches to change. Long-term success of managing nature reserves requires effective combination of ecological conservation, economic development, and social progress. Thus, the philosophy of social engineering should be employed as a strategy to manage the THRHR.

Large‐scale outages on real‐world critical infrastructures, although infrequent, are increasingly disastrous to our society. In this article, we are primarily concerned with power transmission networks and we consider the problem of allocation of generation to distributors by rewiring links under the objectives of maximizing network resilience to cascading failure and minimizing investment costs. The combinatorial multiobjective optimization is carried out by a nondominated sorting binary differential evolution (NSBDE) algorithm. For each generators–distributors connection pattern considered in the NSBDE search, a computationally cheap, topological model of failure cascading in a complex network (named the Motter‐Lai [ML] model) is used to simulate and quantify network resilience to cascading failures initiated by targeted attacks. The results on the 400 kV French power transmission network case study show that the proposed method allows us to identify optimal patterns of generators–distributors connection that improve cascading resilience at an acceptable cost. To verify the realistic character of the results obtained by the NSBDE with the embedded ML topological model, a more realistic but also more computationally expensive model of cascading failures is adopted, based on optimal power flow (namely, the ORNL‐Pserc‐Alaska) model). The consistent results between the two models provide impetus for the use of topological, complex network theory models for analysis and optimization of large infrastructures against cascading failure with the advantages of simplicity, scalability, and low computational cost.

AbstractLike income inequality, housing inequality in urban China is strongly affected by state policies that give preferential treatment to insiders. In this case, the key policies are related to their residence status, which involves not only their migration history but also their legal position. Using data from the Chinese census of 2000 for eight large cities, this study shows how residence status affects access to various pathways to housing. In addition to the well‐known marginal housing situation of the recent 'floating population', it documents surprising advantages for migrants with urban registration status and persistent disadvantages for rural migrants regardless of how long they have lived in the city.RésuméComme l'inégalité de revenu, l'inégalité de logement dans les villes chinoises est nettement affectée par les mesures étatiques qui privilégient les résidents en place. En l'occurrence, les politiques déterminantes s'attachent au statut de résidence, ce qui recouvre à la fois l'historique migratoire des individus et leur situation juridique. À partir des données du recensement chinois de 2000 dans huit grandes villes, l'étude montre comment le statut de résidence influe sur l'accès aux différents canaux conduisant à un logement. Outre la condition de logement marginale bien connue de la «population flottante» récente, sont exposés les surprenants atouts des migrants qui sont enregistrés comme urbains, et les inconvénients persistants que rencontrent les migrants ruraux quelle que soit la durée pendant laquelle ils ont vécu dans la ville.

AbstractIn recent years, the increased frequency of natural hazards has led to more disruptions in power grids, potentially causing severe infrastructural damages and cascading failures. Therefore, it is important that the power system resilience be improved by implementing new technology and utilizing optimization methods. This paper proposes a data‐driven spatial distributionally robust optimization (DS‐DRO) model to provide an optimal plan to install and dispatch distributed energy resources (DERs) against the uncertain impact of natural hazards such as typhoons. We adopt an accurate spatial model to evaluate the failure probability with regard to system components based on wind speed. We construct a moment‐based ambiguity set of the failure distribution based on historical typhoon data. A two‐stage DS‐DRO model is then formulated to obtain an optimal resilience enhancement strategy. We employ the combination of dual reformulation and a column‐and‐constraints generation algorithm, and showcase the effectiveness of the proposed approach with a modified IEEE 13‐node reliability test system projected in the Hong Kong region.