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This paper presents a planning model that utilizes mobile energy storage systems (MESSs) for increasing the connectivity of renewable energy sources (RESs) and fast charging stations (FCSs) in distribution systems (DSs). The proposed planning model aims at enabling high penetration levels of green technologies while minimizing the total DS cost that includes investment, operating, and emission costs. The proposed model determines the optimal MESS sizes and transportation schedules as well as the optimal sizes and locations of wind-based distributed generators (DGs), photovoltaic (PV) DGs, and FCSs. The model takes into account techno-economic and environmental factors in addition to the power variations of RESs, FCSs, and load demands. The proposed planning model is applied on two benchmark test systems (i.e., 33-bus and 69-bus DSs). To evaluate the efficacy of the proposed model, the results obtained from the model are compared to those obtained from a traditional planning technique. The comparison of the results demonstrates that the proposed model with MESSs successfully achieves a significant cost saving and increases the penetration levels of RESs and FCSs. [ABSTRACT FROM AUTHOR]

Background: since COVID-19 emergence in December 2019, health systems in collaboration with scientists all over the world struggled to face this pandemic. Population acceptance of vaccination is a very important factor necessary to achieve herd immunity. This study aimed to assess the prevalence of vaccine acceptance and its predictors among the Egyptian population. Methods: An online cross-sectional study was conducted on a total sample of 846 individuals selected by using the non-probability snowball sampling technique during August and September 2021. Data was collected by An Arabic questionnaire which included data on the socio-economic characters of the participants, health-related variables, and the outcome variable (participants' vaccine acceptance). The odds ratio and 95% confidence interval were used to identify the association between vaccine acceptance and socio-demographic and health-related variables. Results: Of 846 participants, 467 accept vaccination representing 55.2% of the total sample. Vaccine acceptance was associated with a higher age group (>50 years), male gender, urban residents, educated, married, high-income individuals, and healthcare workers. Also, vaccine acceptance was associated with a history of chronic disease, fair/poor self-rated health status, negative history of COVID-19 infection, and a high perception of the infection risk. About 83.4% of vaccine refusals believed that the vaccine is not safe, while 50.7% believed it is ineffective. Conclusion: Socio-demographic and some health-related characters are significant predicators of vaccine acceptance among the population. These variables must be taken into consideration in interventions aimed to increase the population vaccination rate. [ABSTRACT FROM AUTHOR]

High penetration of distributed generation (DG) results in technical problems as voltage rise, voltage unbalance, substation reverse power, and transformer overloading. These problems adversely affect the connectivity of DGs either in the planning stage by decreasing the number of connected DGs, or in the operation stage by applying DGs’ active power curtailment (APC). This paper presents a techno-economic approach for the enhancement of photovoltaic (PV) DGs connectivity. The proposed approach first employs a probabilistic economic technique for determining the non-curtailable portion of the PV DG power that ensures profitable DG investment. This portion is integrated, as an economic constraint, in the planning phase of the proposed approach that aims to maximize the number of PV DGs connected to the system. In the operation phase, the proposed approach utilizes the capabilities of the existing equipment on the system, i.e., regulators, capacitors, DGs reactive power, and DGs APC to mitigate all technical problems. The overall objective of this stage is to minimize the total DGs APC while fulfilling all technical and economic constraints. The proposed approach is tested on the modified IEEE 123-bus feeder. The results clarify the efficiency of the proposed techniques in increasing the connectivity of PV DGs while maintaining profitable DG project. [ABSTRACT FROM AUTHOR]

This paper proposes a two-stage energy management scheme (EMS) for AC–DC hybrid smart distribution systems (DSs). The proposed EMS is formulated as a multi-objective optimization problem to minimize the DS operation costs and energy losses. The proposed EMS is achieved in two stages. In the first stage, a network reconfiguration algorithm determines the optimal day-ahead reconfiguration schedule for a hybrid DS. In the second stage, a real-time optimal power flow algorithm determines the real-time operational schedule of the energy resources. This paper also introduces a new linearized power flow model for AC–DC hybrid DSs. This new model facilitates the formulation of the first-stage algorithm as a mixed-integer linear programming problem and the formulation of the second-stage algorithm as a linear programming problem. The proposed two-stage EMS was tested on a case study of a hybrid DS that included different types of loads and distributed generators. The results demonstrate the efficacy of the proposed EMS: the optimal day-ahead reconfiguration schedule was successfully obtained in the first stage, and the proper and optimal real-time operation was achieved in the second stage. [ABSTRACT FROM AUTHOR]

This paper proposes a novel stochastic planning model for AC-DC hybrid distribution systems (DSs). Taking into account the possibility of each line/bus being AC or DC, the model finds the optimal AC-DC hybrid configuration of buses and lines in the DS. It incorporates consideration of the stochastic behavior of load demands and renewable-based distributed generators (DGs). The stochastic variations are addressed using a Monte-Carlo simulation technique. The objective of the planning model is the minimization of DS installation and operation costs. The optimal planning solution is obtained by dividing the hybrid planning problem into two nested optimization problems: 1) the main problem is formulated using a genetic algorithm (GA) to search for the optimal AC-DC configuration and 2) the subproblem is used for determining the optimal power flow solution for each configuration generated by the GA. The proposed model has been employed for finding the optimal configuration for a suggested case study that included photovoltaic panels, wind-based DG, and electric vehicle charging stations. The same case study was also solved using a traditional AC planning technique in order to evaluate the effectiveness of the proposed model and the associated cost-savings. The results demonstrate the advantages offered by the proposed model. The proposed framework represents an effective technique that can be used by DS operators to identify the optimal AC-DC network configuration of future DSs. [ABSTRACT FROM PUBLISHER]

This paper proposes a unified load flow (LF) model for AC–DC hybrid distribution systems (DSs). The proposed model can be applied in hybrid DSs with mixed configurations for AC/DC buses and AC/DC lines. A new classification of DS buses is also introduced for LF analysis. A set of generic LF equations has been derived based on comprehensive analysis of the possible AC–DC hybrid system configurations. Three binary matrices, which are used as a means of describing the configuration of the AC and DC buses and lines, have been employed in the construction of the unified power equations. These matrices enable a single configuration at a time to be activated in the power equations. The proposed LF model is generic and can be used for both grid-connected and isolated hybrid DSs. The new model has been tested using several case studies of hybrid DSs that include different operational modes for the AC and DC distributed generators. As a means of evaluating the effectiveness and accuracy of the proposed model, the LF solution was compared to the solution produced by PSCAD/EMTDC. A comparison of the results reveals the efficacy of the proposed model. [ABSTRACT FROM AUTHOR]