Operation and planning of distribution networks with integration of renewable distributed generators considering uncertainties: a review

YesDistributed generators (DGs) are a reliable solution to supply economic and reliable electricity to customers. It is the last stage in delivery of electric power which can be defined as an electric power source connected directly to the distribution network or on the customer site. It is necessary to allocate DGs optimally (size, placement and the type) to obtain commercial, technical, environmental and regulatory advantages of power systems. In this context, a comprehensive literature review of uncertainty modeling methods used for modeling uncertain parameters related to renewable DGs as well as methodologies used for the planning and operation of DGs integration into distribution network.This work was supported in part by the SITARA project funded by the British Council and the Department for Business, Innovation and Skills, UK and in part by the University of Bradford, UK under the CCIP grant 66052/000000

A new methodology called dice game optimizer for capacitor placement in distribution systems

Purpose. Shunt capacitors are installed in power system for compensating reactive power. Therefore, feeder capacity releases, voltage profile improves and power loss reduces. However, determination optimal location and size of capacitors in distributionsystems is a complex optimization problem. In order to determine the optimum size and location of the capacitor, an objective function which is generally defined based on capacitor installation costs and power losses should be minimized According to operational limitations. This paper offers a newly developed metaheuristic technique, named dice game optimizerto determine optimal size and location of capacitors in a distribution network. Dice game optimizer is a game based optimization technique that is based on the rules of the dice game.Цель. Шунтирующие конденсаторы в энергосистеме устанавливаются для компенсации реактивной мощности. Следовательно, снижается емкость фидера, улучшается профиль напряжения и снижаются потери мощности. Однако определение оптимального местоположения и размера конденсаторов в системах распределения является сложной задачей оптимизации. Чтобы определить оптимальный размер и расположение конденсатора, целевую функцию, которая обычно определяется на основе затрат на установку конденсатора и потерь мощности, следует минимизировать в соответствии с эксплуатационными ограничениями. Данная статья предлагает недавно разработанный метаэвристический метод, называемый оптимизатором игры в кости, для определения оптимального размера и расположения конденсаторов в распределительной сети. Оптимизатор игры в кости – это игровой метод оптимизации, основанный на правилах игры в кости

Voltage profile improvement and losses minimization for Hayin Rigasa radial network Kaduna using distributed generation

This research work has presented the application of distributed generation (DG) units in a simultaneous placement approach on IEEE 33 radial test systems for validation of the technique with further implementation on 56-Bus Hayin Rigasa feeder. The genetic algorithm (GA) is employed in obtaining the optimal sizes and load loss sensitivity index for locations of the DGs for entire active and reactive power loss reduction. The voltage profile index is computed for each bus of the networks to ascertain the weakest voltage bus of the network before and after DG and circuit breaker allocation. The simultaneous placement approach of the DGs is tested with the IEEE 33-bus test networks and Hayin Rigasa feeder network and the results obtained are confirmed by comparing with the results gotten from separate DGs allocation on the networks. For IEEE 33-bus system, the simultaneous allocation of DGs and of optimal sizes 750 kW, 800 kW and at locations of buses 2 and 6 respectively, lead to a 66.49 % and 68.64 % drop in active and reactive power loss and 3.02 % improvement in voltage profile. For the 56-bus Hayin Rigasa network in Kaduna distribution network, the simultaneous placement of DGs of sizes 1,470 kW and 1490 kW at locations of bus 16 and 23 respectively, lead to a 79.54 % and 73.98 % drop in active and reactive power loss and 15.94 % improvement in voltage profile. From results comparison, it is evident that the allocation of DGs using the combination GA and load loss sensitivity index, gives an improved performance in relations to power loss reduction and voltage profile improvements of networks when compared to without DGs

A hybrid algorithm for voltage stability enhancement of distribution systems

This paper presents a hybrid algorithm by applying a hybrid firefly and particle swarm optimization algorithm (HFPSO) to determine the optimal sizing of distributed generation (DG) and distribution static compensator (D-STATCOM) device. A multi-objective function is employed to enhance the voltage stability, voltage profile, and minimize the total power loss of the radial distribution system (RDS). Firstly, the voltage stability index (VSI) is applied to locate the optimal location of DG and D-STATCOM respectively. Secondly, to overcome the sup-optimal operation of existing algorithms, the HFPSO algorithm is utilized to determine the optimal size of both DG and D-STATCOM. Verification of the proposed algorithm has achieved on the standard IEEE 33-bus and Iraqi 65-bus radial distribution systems through simulation using MATLAB. Comprehensive simulation results of four different cases show that the proposed HFPSO demonstrates significant improvements over other existing algorithms in supporting voltage stability and loss reduction in distribution networks. Furthermore, comparisons have achieved to demonstrate the superiority of HFPSO algorithms over other techniques due to its ability to determine the global optimum solution by easy way and speed converge feature

Optimal control of distributed generators and capacitors by hybrid DPSO

In this paper, a comprehensive planning methodology is proposed that can minimize the line loss, maximize the reliability and improve the voltage profile in a distribution network. The injected active and reactive power of Distributed Generators (DG) and the installed capacitor sizes at different buses and for different load levels are optimally controlled. The tap setting of HV/MV transformer along with the line and transformer upgrading is also included in the objective function. A hybrid optimization method, called Hybrid Discrete Particle Swarm Optimization (HDPSO), is introduced to solve this nonlinear and discrete optimization problem. The proposed HDPSO approach is a developed version of DPSO in which the diversity of the optimizing variables is increased using the genetic algorithm operators to avoid trapping in local minima. The objective function is composed of the investment cost of DGs, capacitors, distribution lines and HV/MV transformer, the line loss, and the reliability. All of these elements are converted into genuine dollars. Given this, a single-objective optimization method is sufficient. The bus voltage and the line current as constraints are satisfied during the optimization procedure. The IEEE 18-bus test system is modified and employed to evaluate the proposed algorithm. The results illustrate the unavoidable need for optimal control on the DG active and reactive power and capacitors in distribution networks

Reduction of Power Losses in the Distribution System by Controlling Tap Changing Transformer using the PSO Algorithm

Energy is an essential commodity for everyone, with electrical energy being the most preferred form. Unfortunately, non-renewable energy resources are gradually depleting, and renewable energy sources take several years to establish. To mitigate this problem, technology has shifted from non-renewable energy sources to electrical devices and machines, including household appliances like washing machines and air conditioners. However, the generation of electricity is still inadequate to meet the growing demand. This leads to two critical issues: Excessive power loss and inadequate voltage stability, making it difficult for power distribution companies to ensure a consistent and reliable power supply. The objective of this study is to tackle the issue of reduction and minimization of power dissipation By employing the PSO technique, adjusting the transformer tap settings. The proposed approach uses the 14-bus system as a reference and calculates losses for this system using the backward-forward sweeping technique

Optimal PV Distributed Generators Allocation using Metaheuristic Algorithm to Enhance Voltage Profile

In this paper, the authors propose a methodology to identify the key locations to install integration of Solar & windbased distributed generators((DG) and the optimal amount of CapacityDGs required to maintain a steady voltage profile and voltage stability. The optimal amount of DG required is obtained via Gorilla troops optimizer(GTO)Metaheuristic algorithm and ,the locations where Integration of DG installation results in maximum benefit are obtained through the voltage stability index. The methodology tested in the Indian28 bus system shows that the proposed technique effectively identifies the critical locations and optimizes the required Integration DG capacity

Planning and Operation of DSTATCOM in Electrical Distribution Systems

In present day scenario, it is most essential to consider the maximum asset performance of the power distribution systems to reach the major goals to meet customer demands. To reach the goals, the planning optimization becomes crucial, aiming at the right level of reliability, maintaining the system at a low total cost while keeping good power quality. There are some problems encountered which are hindering the effective and efficient performance of the distribution systems to maintain power quality. These problems are higher power losses, poor voltage profile near to the end customers, harmonics in load currents, sags and swells in source voltage etc. All these problems may arise due to the presence of nonlinear loads, unpredictable loads, pulse loads, sensor and other energy loads, propulsion loads and DG connections etc. Hence, in order to improve the power quality of power distribution systems, it is required to set up some power quality mitigating devices, for example, distribution static synchronous compensator (DSTATCOM), dynamic voltage restorer (DVR), and unified power quality conditioner (UPQC) etc. The goal of this project work is to devise a planning of optimal allocation of DSTATCOM in distribution systems using optimization techniques so as to provide reactive power compensation and improve the power quality