Optimal allocation of solar photovoltaic distributed generation in electrical distribution networks using Archimedes optimization algorithm

This paper proposes to resolve optimal solar photovoltaic(SPV)system locations and sizes in electrical distribution networks using a novel Archimedes optimization algorithm(AOA)inspired by physical principles in order to minimize network dependence and greenhouse gas(GHG)emissions to the greatest extent possible.Loss sensitivity factors are used to predefine the search space for sites,and AOA is used to identify the optimal locations and sizes of SPV systems for reducing grid dependence and GHG emissions from conventional power plants.Experiments with composite agriculture loads on a practical Indian 22-bus agricultural feeder,a 28-bus rural feeder and an IEEE 85-bus feeder demonstrated the critical nature of optimally distributed SPV systems for minimizing grid reliance and reducing GHG emissions from conventional energy sources.Additionally,the voltage profile of the network has been enhanced,resulting in significant reductions in distribution losses.The results of AOA were compared to those of several other nature-inspired heuristic algorithms previously published in the literature,and it was observed that AOA outperformed them in terms of convergence and redundancy when solving complex,non-linear and multivariable optimization problems.

Global Harmonic Rate Assessment in the Electricity Distribution Network in Niamey City:Case Studies of Domestic,Industrial and Hospital Substations

Like others countries of the world, in Niger also, we are witnessing an increasing use of non-linear electric loads in the domestic, hospital and industrial sectors. However, these loads degrade the shape of the electrical signal and cause disastrous effects to the equipment of the distribution system and the devices which are connected to the network. This article highlights the presence of electric harmonics in the distribution network in Niamey city. In order to do this, measurements were taken at the secondary level of the substations using an energy quality analyze r (FLUKE 1735). By using this measuring instrument, we quantified the voltage and current Total Harmonic Distortion (THD) in the three substations. The results obtained show that, although the statutable rates set by the standards are not exceeded for phase conductors, the neutral contains a very critical percentage of distortion on the residential and hospital substations. Moreover, this assessment made it possible to observe the variation of harmonics in the presence of voltage drops.

Optimization of the Placement and Size of Photovoltaic Source

This paper presents a new optimization study of the placement and size of a photovoltaic source(PVS)in a distribution grid,based on annual records of meteorological parameters(irradiance,temperature).Based on the recorded data,the production output as well as the daily average power(24-h vector)of the PVS is extracted over the year.When a power vector is available,it can be used as an input when searching for the optimal size of the PVS.This allows to take into account the constraint of the variation of the power generated by this source considering the variation of the power consumed by the electrical loads during the whole day.A multi-objective fitness function has been considered.The latter minimizes the active losses and maximizes the voltage stability index during the day,while considering the constraints of the system,that is,the security,technical,geographical,and meteorological constraints.This problem was solved using the Non-dominated Sorting Genetic Algorithm NSGA-II optimization technique under MATLAB 2021.It was applied to the distribution network of Ghardaïa of 59 nodes.

Electrical Properties of Medium Voltage Electricity Distribution Networks

An increasing amount of low carbon technologies(LCT)such as solar photovoltaic,wind turbines and electric vehicles are being connected at medium and low voltage levels to electric power networks.To support high-level decision-making processes,the impacts of the LCTs on large numbers of different types(e.g.,rural,suburban,urban)of distribution networks need to be fully understood and quantified.However,detailed modeling of large numbers of real-world networks is challenging for two reasons.First,access to real-world network data is limited,and second,cleaning the data requires a significant amount of time,even before modeling of the networks.This paper offers a novel systematic methodology aimed at identifying and quantifying the key electrical properties of medium-voltage level distribution networks.The methodology allows for characterizing different types(e.g.,suburban,urban)of distribution networks and obtaining'depth'dependent electrical properties of the models of the networks.Two key sets of(electrical)data were used for the study.The first set was installed capacities of distribution substations;and the second set was the conductor cross sections of the distribution lines.In the graph models of real-world networks,'nodes'represent the distribution sub-stations,switchgears,busbars and consumers locations of the network.'Links/edges'stand for the connections between the nodes through distribution lines.The results of the investigation of the real-world networks showed that,the substation capacities and the conductor cross sections could characterize the electrical properties of suburban and urban type distribution networks.The resulted probability density functions(PDF)of the electrical properties of suburban and urban type distribution networks have the potential to be directly used in generating realistic distribution network models.

Strategic Bidding in Distribution Network Electricity Market Focusing on Competition Modeling and Uncertainties

Developing the electricity market at the distribution level can facilitate the energy transactions in distribution networks with a high penetration level of distributed energy resources(DERs)and microgrids(MGs).However,the lack of comprehensive information about the marginal production cost of competitors leads to uncertainties in the optimal bidding strategy of participants.The electricity demand within the network and the price in the wholesale electricity market are two other sources of the uncertainties.In this paper,a day-ahead-market-based framework for managing the energy transactions among MGs and other participants in distribution networks is introduced.A game-theory-based method is presented to model the competition and determine the optimal bidding strategy of participants in the market.Robust optimization technique is employed to capture the uncertainties in the marginal cost of competitors.Additionally,the uncertainties in demand are modeled using a scenario-based stochastic approach.The results ob-tained from case studies reveal the merit of considering competition modeling and uncertainties.

Network-Constrained Energy Consumption Game for Dynamic Pricing Markets

The electricity distribution network is experiencing a profound transformation with the concept of the smart grid,providing possibilities for selfish consumers to interact with the distribution system operator(DSO)and to maximize their individual energy consumption utilities.However,this profitseeking behavior among consumers may violate the network constraints,such as line flows,transformer capacity and bus voltage magnitude limits.Therefore,a network-constrained energy consumption(NCEC)game among active load aggregators(ALAs)is proposed to guarantee the safety of the distribution network.The temporal and spatial constraints of an ALA are both considered,which leads the formulated model to a generalized Nash equilibrium problem(GNEP).By resorting to a well-developed variational inequality(VI)theory,we study the existence of solutions to the NCEC game problem.Subsequently,a two-level distributed algorithm is proposed to find the variational equilibrium(VE),a fair and stable solution to the formulated game model.Finally,the effectiveness of the proposed game model and the efficiency of the distributed algorithm are tested on an IEEE-33 bus system.