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In this paper, a multiobjective framework for simultaneous reconfiguration and allocation of photovoltaic (PV) energy resources in radial distribution networks is performed for minimizing the power losses, lowering network loading factor, and reducing cost of energy resources as well as increasing the voltage stability index. A novel algorithm called the improved clouded leopard algorithm is used to find the set of optimum decision factors in the combined execution of restructuring and also PV resource distribution. The clouded leopard optimization (CLO) algorithm, which is widely used, takes its cues from the sleeping and foraging habits of the animal, and the improved CLO (ICLO) is formed using adaptive inertia weight to overcome premature convergence. In five cases of base distribution network and different contribution of reconfiguration and PV allocation, single- and multiobjective approach has been applied on 33- and 69-bus distribution networks. According to the findings, the best case includes simultaneous reconfiguration and PV allocation in the radial networks based on the multiobjective approach unlike the single-objective method which obtained the highest network performance with the best compromise between different goals. Also, in the best lowest losses, the decrease in the network loading and cost of energy resources and the better voltage profile and stability are obtained satisfying the constraints. The losses, network loading, voltage profile, and voltage stability are improved by 60.40%, 37.89%, 6.17%, and 27.5% for 33-bus network and also enhanced by 71.77%, 41.23%, 4.76%, and 20.48% for 69-bus network, respectively. Also, the results showed that network reconfiguration only has the weakest performance among other cases based on reconfiguration or photovoltaic sources. Moreover, the superior capability of the ICLO in addressing the aim of the study is proved in comparison with the traditional CLO and well-known particle swarm optimization (PSO) and manta ray foraging optimization (MRFO) to obtain the better objective value and statistical criteria to solve the best case. [ABSTRACT FROM AUTHOR]

As the integration of distributed energy into the power grid continues to rise, the significance of electricity transactions in promoting renewable energy consumption grows substantially. This necessitates the establishment of a robust electricity trading framework to facilitate reliable and trustworthy transactions for prosumers. This paper introduces an innovative blockchain-based electricity trading framework. Within this framework, we present a decentralized collaborative model training approach aimed at predicting the power generation of distributed photovoltaic power stations. Simultaneously, we propose a graph-based algorithm for efficiently matching producers and consumers. Our experiments, conducted on the Hyperledger Fabric blockchain platform using real-world datasets, demonstrate enhanced prediction accuracy compared to existing models. The framework effectively handles transactions within one second, sustaining a sending rate of up to 200 transactions per second. The outcomes of this study not only surpass the performance of existing prediction models but also provide valuable insights for the development of trading frameworks in actual production environments. The proposed framework stands as a reference point for constructing reliable trading infrastructures, thereby contributing to the acceleration of green electricity trading. [ABSTRACT FROM AUTHOR]

One of the essential capabilities of a smart distribution network is to improve network restoration performance using the postfault islanding method. Islanding of the faulty area can be done offline and online. Online islanding will decrease load shedding and operation cost. In this study, a novel two-step mathematical method for system restoration after the fault is presented. A new mathematical model for the optimal arrangement of the system for the faulty area in the first layer is proposed. In this layer, the main objective is to decrease the distribution system's load shedding and operational costs. In this regard, after the fault event, the boundary of the islanded MGs is determined. Then, in the second layer, the problem of unit commitment in the smart distribution network is addressed. In addition to the load shedding, optimal planning of energy storage systems (ESSs) and nondispatchable distributed generation (DG) resource rescheduling are also determined in this layer. The important advantages of the proposed approach are low execution time and operational costs. A demand response (DR) program has also been used for optimal system restoration. Solving the problem using the multiobjective method with the epsilon-constraint method is another goal of the paper, which simultaneously minimizes the cost and the emissions of the smart distribution network. The proposed model has been tested on an IEEE 33-bus system. Better performance of the proposed model compared to the techniques in the literature has been proven. [ABSTRACT FROM AUTHOR]

The high level of integration of distributed generation systems (DGSs), especially distributed wind and solar, significantly affects the flexibility and controllability of the power system. Aggregating local DGSs and shared energy storage systems (ESSs) within an energy community offers an economically and environmentally viable solution. However, the coupling of shared ESSs with the energy community, while considering subjectivity, is often overlooked. Therefore, this study introduces a two-layer optimization framework that enables DGSs to trade energy freely, voluntarily, and independently and to share ESSs within the energy community, considering participants' subjectivity. The upper layer optimizes the size of shared ESSs, while the lower layer, structured as a two-layer model, simulates participant interactions. The numerical case shows that, compared to DGSs operating individually, the shared ESS case indicates that community self-sufficiency and self-consumption rates increase by 16.22% and 21.98%, respectively. Additionally, the annual operating cost is reduced by approximately 27.10%, and CO2 emissions are decreased by about 33.24%. Considering DGS' subjectivity, the self-sufficiency and self-consumption rates are 3.04% lower, and the total operating costs and CO2 emissions are 3.26% and 6.86% higher, respectively. [ABSTRACT FROM AUTHOR]

The fluctuation of microgrid power flow leads to serious voltage problems at the point of common coupling (PCC). The quantitative representation of the disturbance parameters of the voltage waveform at the PCC is necessary for evaluating and controlling the impact of distributed generation in the microgrid on the power system. An improved atomic decomposition (IAD) method is proposed to represent the disturbance parameters quantitatively and efficiently. Based on the disturbance characteristics of the PCC voltage, a coherent atom dictionary composed of four subdictionaries is constructed to improve the decomposition efficiency. To further improve the computational efficiency, an improved matching pursuits algorithm is proposed by alternating the search way to extract the disturbance components in the atomic decomposition. Meanwhile, simulation results show that the proposed IAD method has better antinoise and disturbance parameters quantization ability than wavelet transform. [ABSTRACT FROM AUTHOR]

The distributed generation (DG) units' penetrations in power systems are becoming more prevalent. The majority of recent studies are now focusing on how to best position and size PV-DG units to further improve grid performance. In actuality, and as a result of ideal design requirements, the size and position of the PV are chosen and executed, and no luxury for a change. In this work, the PV-DG unit sizing and location were determined and placed beforehand. Also, load change is a fact and is to be highly considered in the grid. Studying the grid performance and how to enhance it under these conditions is the main objective of this study. This examination was executed using an IEEE 15 bus system in a MATLAB environment. Distribution lines were proposed to connect the PV-DG from its restricted location to the required bus. The purpose of this study is therefore to evaluate the grid's performance with various actual loads on each bus while connecting a PV-DG unit through a distribution line while taking the available transfer capacity (ATC) of the network into account to find the optimally connected bus. The results said that the optimally connected bus is changed by changing the load which is not doable on land. The results obtained indicate that breaking up PV-DG units into smaller units in the same location and connecting them to every bus was the best option for improving grid performance. [ABSTRACT FROM AUTHOR]