Photovoltaic Models Parameters Estimation Based on Weighted Mean of Vectors

Renewable energy sources are gaining popularity,particularly photovoltaic energy as a clean energy source.This is evident in the advancement of scientific research aimed at improving solar cell performance.Due to the non-linear nature of the photovoltaic cell,modeling solar cells and extracting their parameters is one of the most important challenges in this discipline.As a result,the use of optimization algorithms to solve this problem is expanding and evolving at a rapid rate.In this paper,a weIghted meaN oF vectOrs algorithm(INFO)that calculates the weighted mean for a set of vectors in the search space has been applied to estimate the parameters of solar cells in an efficient and precise way.In each generation,the INFO utilizes three operations to update the vectors’locations:updating rules,vector merging,and local search.The INFO is applied to estimate the parameters of static models such as single and double diodes,as well as dynamic models such as integral and fractional models.The outcomes of all applications are examined and compared to several recent algorithms.As well as the results are evaluated through statistical analysis.The results analyzed supported the proposed algorithm’s efficiency,accuracy,and durability when compared to recent optimization algorithms.

Optimal Implementation of Photovoltaic and Battery Energy Storage in Distribution Networks

Recently,implementation of Battery Energy Storage(BES)with photovoltaic(PV)array in distribution networks is becoming very popular in overall the world.Integrating PV alone in distribution networks generates variable output power during 24-hours as it depends on variable natural source.PV can be able to generate constant output power during 24-hours by installing BES with it.Therefore,this paper presents a new application of a recent metaheuristic algorithm,called Slime Mould Algorithm(SMA),to determine the best size,and location of photovoltaic alone or with battery energy storage in the radial distribution system(RDS).This algorithm is modeled from the behavior of SMA in nature.During the optimization process,the total active power loss during 24-hours is used as an objective function considering the equality and inequality constraints.In addition,the presented function is based on the probabilistic for PV output and different types of system load.The candidate buses for integrating PV and BES in the distribution network are determined by the real power loss sensitivity factor(PLSF).IEEE 69-bus RDS with different types of loads is used as a test system.The effectiveness of SMA is validated by comparing its results with those obtained by other well-known optimization algorithms.

Operational Reliability Model of Hybrid MMC Considering Multiple Time Scales and Multi-state Submodule

Environmental and electrical factors such as wind speed,air temperature and switching frequency have significant influences on the operational reliability of hybrid modular multilevel converter(MMC),which is commonly used for the wind power transmission.However,the existing reliability model of hybrid MMC based on statistics cannot accurately reflect the impact of these factors.In this paper,a new operational reliability model of hybrid MMC is presented.The reliability index of the hybrid MMC is coupled with its operation characteristics by calculating multi-term thermal cycling.In addition,an operation strategy of hybrid MMC is proposed to improve its reliability.The multi-state submodule(SM)is developed,which is capable of bypassing specific faulty power modules instead of the whole SM.Case studies show that the proposed operational reliability model could describe the impact of environmental and electrical factors.Also,the proposed operation strategy can improve the reliability of hybrid IMMC by extending the operation time of SMs.