Abstract Settlements in coastal cities have various complex problems, one of which is the area of flooding and sinking. This study aims to examine how the adaptation response of the community to ...their residential area, which used to be in the form of a land dimension, is now sinking into a water dimension. Using qualitative methods, this research uses a GIS approach to observe physical changes in the area and in-depth interviews to obtain information related to community adaptation. The result is that there are three adaptations, namely Resistant Settlement Adaptations, Adaptation of Settlement Increase, and Reduced Settlements Adaptation. This adaptation occurs because of the encouragement of internal and external factors, giving rise to various forms of adaptation, especially in the Adaptation of Settlement Increase which is a new thing in this study.
•A methodology to analyze the vulnerability of PTSs from the perspective of RC.•The functionality of PTSs is measured by the accessibility of RC.•An algorithm is proposed to calculate the ...accessibilities of each RC.•The vulnerability of PTSs is analyzed under several daily disruption modes.
Public transit systems (PTSs) in a city usually consist of multiple systems with different transit modes, such as bus and subway systems, and the connection relationships among those systems can be described in terms of the geographical proximity of different stations. This paper proposes a methodology to analyze the vulnerability of the PTSs in a city from the perspective of their common functionality of providing residential communities access to critical services, including commuting, medical, commercial and education services. The proposed methodology is built upon a multi-layer network, with each layer describing a particular type of public transit system. This paper applies the proposed methodology to analyze the vulnerability of the bus and subway systems in Wuhan, China, under several types of disruptions, including random vehicle accidents, recurrent traffic jams and a real rainstorm disaster.
Enhancing community resilience against hurricanes, one of the costliest natural hazards to impact the United States over the past four decades, is an essential requirement for the nation’s security ...and welfare. A fundamental step in this direction is to provide computational frameworks that are able to quantify the response of the community to the hazard immediately after its impact and during its recovery process. Existing frameworks focus on estimating damage and losses immediately subsequent to the hurricane impact through vulnerability models. This paper provides a framework that integrates damage estimated from vulnerability models with a probabilistic recovery model for quantifying community resilience against hurricanes. The framework is based on five resilience limit states that identify the required recovery activities for each building based on the amount of damage. A building-level recovery model, based on discrete functionality states, translates these limit states to a building-level recovery function. By aggregating building recovery functions, a community recovery function and resilience measure are obtained. The framework is embedded in a Monte Carlo simulation strategy for uncertainty propagation therefore enabling a fully probabilistic quantification of community resilience. The framework is illustrated with a case study consisting of a typical residential neighborhood in Miami, FL.
•A resilience framework is presented for residential communities subject to hurricanes.•The framework introduces a novel recovery model for wind excited buildings.•Uncertainty is considered in the framework through Monte Carlo simulation.•A case study consisting in a residential community in Miami, FL, is presented.•The importance of uncertainty and external debris in resilience estimation is shown.
Demand for electricity is a key bottleneck for the development of remote areas. Grid extension to remote areas has previously been constrained due to difficult terrain for construction and vast ...investment. Fast development of decentralized renewable energy production technologies provides opportunity for tackling the challenges. The study aims to demonstrate the techno-economic feasibility of off-grid hybrid renewable energy system for remote rural electrification, via a case study of a village in West China by performing simulation, optimization and sensitivity analysis. Daily and seasonal characteristics of energy supply as well as demand sizes and patterns of remote rural areas are considered. Different combinations of PV panels, wind turbine and biogas generator are modeled and optimized in Hybrid Optimization Model for Electric Renewables (HOMER). The most cost competitive configuration is determined whilst ensuring a reliable power supply featuring residential, community, commercial and agricultural demand of the village. Comparison of the off-grid hybrid power system and grid extension has been carried out. Results show that a hybrid power system comprising solar, wind and biomass is a reliable and cost-effective option for sustainable remote rural electrification whilst achieving environmental benefits.
With the development of economy and society, people have growing demand for healthy living environments. However, there are more than 170,000 old residential communities in China, where aging ...buildings, old facilities and environmental degradation are common problems that need to be urgently improved. Determining subsidy funding and benefit evaluation is often the blind spot, posing difficulties in government decision-making. In this study, the Fuzzy Delphi Method (FDM) was first adopted to propose a set of standards for outdoor environment renovation of old residential communities in China based on the WELL Community Standard (WCS). On the basis of the I-S model and zero-one integer programming (ZOIP), an optimal decision-making model (ODM) was developed and applied in practical projects. The result showed that ODM can not only help government managers to determine the budget rationally, but also provide a way to promote multiple participations to achieve optimal improvement strategies. It is recommended that ODM should be further expanded on more projects to review and modify the application of ODM in different regions of China.
This paper studies the solution of joint energy storage (ES) ownership sharing between multiple shared facility controllers (SFCs) and those dwelling in a residential community. The main objective is ...to enable the residential units (RUs) to decide on the fraction of their ES capacity that they want to share with the SFCs of the community in order to assist them in storing electricity, e.g., for fulfilling the demand of various shared facilities. To this end, a modified auction-based mechanism is designed that captures the interaction between the SFCs and the RUs so as to determine the auction price and the allocation of ES shared by the RUs that governs the proposed joint ES ownership. The fraction of the capacity of the storage that each RU decides to put into the market to share with the SFCs and the auction price are determined by a noncooperative Stackelberg game formulated between the RUs and the auctioneer. It is shown that the proposed auction possesses the incentive compatibility and the individual rationality properties, which are leveraged via the unique Stackelberg equilibrium solution of the game. Numerical experiments are provided to confirm the effectiveness of the proposed scheme.
This article proposes a reflection on the educational skills of residential institutions that welcome mothers with their children following the assessment of their vulnerability in terms of parental ...functioning. The reflections conducted will be supported by testimonies collected in various training contexts addressed to educators of the mother/child communities and in some group meetings held with mothers whose children have been entrusted to foster families. How can the residential community that welcomes them constitute itself as a "symbolic parent" to repair those ancient wounds that have made them incomplete daughters and now "fragile" mothers? These are the questions we are going to answer. Keywords. Parenting narratives - residential communities - educational interventions
This paper presents a reliable microgrid for residential community with modified control techniques to achieve enhanced operation during grid connected, islanded, and resynchronization mode. The ...proposed microgrid is a combination of solar photovoltaic, battery storage system and locally distributed generation (DG) systems with residential local loads. A modified power control technique is developed such that local load reactive power demand, harmonic currents, and load unbalance are compensated by respective residential local DG. However, active power demand of all local residential load is shared between the microgrid and respective local DG. This control technique also achieves constant active power loading on the microgrid by supporting additional active power local load demand of respective residential DG. Hence, proposed modified power control technique achieves transient free operation of the microgrid during residential load disturbances. An additional modified control technique is also developed to achieve seamless transition of microgrid between grid-connected mode and islanded mode. The dynamic performance of this microgrid during grid-connected, islanded, and resynchronization mode under linear and nonlinear load variations is verified using real-time simulator.
A deep recurrent neural network with long short-term memory units (DRNN-LSTM) model is developed to forecast aggregated power load and the photovoltaic (PV) power output in community microgrid. ...Meanwhile, an optimal load dispatch model for grid-connected community microgrid which includes residential power load, PV arrays, electric vehicles (EVs), and energy storage system (ESS), is established under three different scheduling scenarios. To promote the supply-demand balance, the uncertainties of both residential power load and PV power output are considered in the model by integrating the forecasting results. Two real-world data sets are used to test the proposed forecasting model, and the results show that the DRNN-LSTM model performs better than multi-layer perception (MLP) network and support vector machine (SVM). Finally, particle swarm optimization (PSO) algorithm is used to optimize the load dispatch of grid-connected community microgrid. The results show that EES and the coordinated charging mode of EVs can promote peak load shifting and reduce 8.97% of the daily costs. This study contributes to the optimal load dispatch of community microgrid with load and renewable energy forecasting. The optimal load dispatch of community microgrid with deep learning based solar power and load forecasting achieves total costs reduction and system reliability improvement.
•The residential power load and PV power output are forecasted.•The proposed model outperforms other methods.•The forecasting results are used as the input of the microgrid optimization model.•The adoption of EVs and ESS in microgrid contributes to 8.97% cost reduction.
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