Critical Review of Different Methods for Siting and Sizing Distributed-generators

Due to several benefits attached to distributed generators such as reduction in line losses, improved voltage profile, reliable system etc., the study on how to optimally site and size distributed generators has been on the increase for more than two decades. This has propelled several researchers to explore various scientific and engineering powerful simulation tools, valid and reliable scientific methods like analytical, meta-heuristic and hybrid methods to optimally place and size distributed generator(s) for optimal benefits. This study gives a critical review of different methods used in siting and sizing distributed generators alongside their results, test systems and gaps in literature

Energy Production Analysis and Optimization of Mini-Grid in Remote Areas: The Case Study of Habaswein, Kenya

Rural electrification in remote areas of developing countries has several challenges which hinder energy access to the population. For instance, the extension of the national grid to provide electricity in these areas is largely not viable. The Kenyan Government has put a target to achieve universal energy access by the year 2020. To realize this objective, the focus of the program is being shifted to establishing off-grid power stations in rural areas. Among rural areas to be electrified is Habaswein, which is a settlement in Kenya’s northeastern region without connection to the national power grid, and where Kenya Power installed a stand-alone hybrid mini-grid. Based on field observations, power generation data analysis, evaluation of the potential energy resources and simulations, this research intends to evaluate the performance of the Habaswein mini-grid and optimize the existing hybrid generation system to enhance its reliability and reduce the operation costs. The result will be a suggestion of how Kenyan rural areas could be sustainably electrified by using renewable energy based off-grid power stations. It will contribute to bridge the current research gap in this area, and it will be a vital tool to researchers, implementers and the policy makers in energy sector

Optimal location and sizing of PV sources in DC networks for minimizing greenhouse emissions in diesel generators

This paper addresses the problem of the optimal location and sizing of photovoltaic (PV) sources in direct current (DC) electrical networks considering time-varying load and renewable generation curves. To represent this problem, a mixed-integer nonlinear programming (MINLP) model is developed. The main idea of including PV sources in the DC grid is minimizing the total greenhouse emissions produced by diesel generators in isolated areas. An artificial neural network is employed for short-term forecasting to deal with uncertainties in the PV power generation. The general algebraic modeling system (GAMS) package is employed to solve the MINLP model by using the CONOPT solver that works with mixed and integer variables. Numerical results demonstrate important reductions of harmful gas emissions to the atmosphere when PV sources are optimally integrated (size and location) to the DC grid

Stochastic Modeling and Planning of Wind-Based Distributed Generators in Distribution System

The increasing strain on the Earth resulting from pollution, climate change, and finite resources has established the development of renewable energy sourcing methods, such as wind, solar and geothermal energy. By reorganizing the power system structures, and the growth in customer demand, the development of Distributed Generation (DG) play a vital role in the power system planning. Furthermore, because of the inexhaustibility and cleanliness of the renewable DG units, they are inevitably the key to a sustainable energy supply infrastructure. Nevertheless, the random nature associated with the renewable DG units produces specific challenges that have to be addressed to accelerate the expansion of the renewable DG units in the distribution system. Firstly, a new method for the determination of the wind speed distribution based on hourly wind speed data is proposed. Thus, instead of using only the well-known unimodal distributions such as Weibull and Rayleigh, a combination of probability density functions (PDFs) is taken into account, considering four sets of parameters in which each set represents a distribution. Furthermore, this model enhances the likelihood of the estimated wind speed probabilities. The maximum likelihood estimation (MLE) method for finite mixture models through the expectation-maximization (EM) algorithm is used to estimate the optimal parameters of the mixture distribution. Then two types of error measurements assessed the performance of each unimodal and multimodal distribution. As a result, the mixture of Gamma (MoG) distribution returned the most accurate results. Secondly, the results of wind speed modeling will be used in the siting and sizing wind-based DG units. The methodology addresses a probabilistic generation load model that combines all possible operating conditions of the wind-based DG units and load levels with their probabilities. The objective of siting and sizing formulation is to minimize the annual energy losses of the system as well as keeping the system constraints such as voltage limits at different buses (slack and load buses) of the system, feeder capacity, discrete size of the DG units, maximum investment on each bus, and maximum penetration limit of DG units in an acceptable limit

Voltage Rise Problem in Distribution Networks with Distributed Generation: A Review of Technologies, Impact and Mitigation Approaches

Energy demand has constantly been on the rise due to aggressive industrialization and civilization. This rise in energy demand results in the massive penetration of distributed generation (DG) in the distribution network (DN) which has been a holistic approach to enhance the capacity of distribution networks. However, this has led to a number of issues in the low voltage network, one of which is the voltage rise problem. This happens when generation exceeds demand thereby causing reverse power flow and consequently leading to overvoltage. A number of methods have been discussed in the literature to overcome this challenge ranging from network augmentation to active management of the distribution networks. This paper discusses the issue of voltage rise problem and its impact on distribution networks with high amounts of distributed energy resources (DERs). It presents different DG technologies such as those based on conventional and unconventional resources and other DERs such as battery storage systems and fuel cells. The study provides a comprehensive overview of approaches employed to curtail the issue of voltage increase at the point of common coupling (PCC), which includes strategies based on the network reinforcement methodology and the active distribution network management. A techno-economic comparison is then introduced in the paper to ascertain the similarities and dissimilarities of different mitigation approaches based on the technology involved, ease of deployment, cost implication, and their pros and cons. The paper provides insights into directions for future research in mitigating the impact of voltage rise presented by grid-connected DGs without limiting their increased penetration in the existing power grid

Optimal Location and Operation of PV Sources in DC Grids to Reduce Annual Operating Costs While Considering Variable Power Demand and Generation

Due to the need to include renewable energy resources in electrical grids as well as the development and high implementation of PV generation and DC grids worldwide, it is necessary to propose effective optimization methodologies that guarantee that PV generators are located and sized on the DC electrical network. This will reduce the operation costs and cover the investment and maintenance cost related to the new technologies (PV distributed generators), thus satisfying all technical and operative constraints of the distribution grid. It is important to propose solution methodologies that require short processing times, with the aim of exploring a large number of scenarios while planning energy projects that are to be presented in public and private contracts, as well as offering solutions to technical problems of electrical distribution companies within short periods of time. Based on these needs, this paper proposes the implementation of a Discrete–Continuous Parallel version of the Particle Swarm Optimization algorithm (DCPPSO) to solve the problem regarding the integration of photovoltaic (PV) distributed generators (DGs) in Direct Current (DC) grids, with the purpose of reducing the annual costs related to energy purchasing as well as the investment and maintenance cost associated with PV sources in a scenario of variable power demand and generation. In order to evaluate the effectiveness, repeatability, and robustness of the proposed methodology, four comparison methods were employed, i.e., a commercial software and three discrete–continuous methodologies, as well as two test systems of 33 and 69 buses. In analyzing the results obtained in terms of solution quality, it was possible to identify that the DCPPSO proposed obtained the best performance in relation to the comparison methods used, with excellent results in relation to the processing times and standard deviation. The main contribution of the proposed methodology is the implementation of a discrete–continuous codification with a parallel processing tool for the evaluation of the fitness function. The results obtained and the reports in the literature for alternating current networks demonstrate that the DCPPSO is the optimization methodology with the best performance in solving the problem of the optimal integration of PV sources in economic terms and for any kind of electrical system and size. © 2022 by the authors

Optimal Number, Location, and Size of Distributed Generators in Distribution Systems by Symbiotic Organism Search Based Method

This paper proposes an approach based on the Symbiotic Organism Search (SOS) for optimal determining sizing, siting, and number of Distributed Generations (DG) in distribution systems. The objective of the problem is to minimize the power loss of the system subject to the equality and inequality constraints such as power balance, bus voltage limits, DG capacity limits, and DG penetration limit. The SOS approach is defined as the symbiotic relationship observed between two organisms in an ecosystem, which does not need the control parameters like other meta-heuristic algorithms in the literature. For the implementation of the proposed method to the problem, an integrated approach of Loss Sensitivity Factor (LSF) is used to determine the optimal location for installation of DG units, and SOS is used to find the optimal size of DG units. The proposed method has been tested on IEEE 33-bus, 69-bus, and 118-bus radial distribution systems. The obtained results from the SOS algorithm have been compared to those of other methods in the literature. The simulated results have demonstrated that the proposed SOS method has a very good performance and effectiveness for the problem of optimal placement of DG units in distribution systems

RNA Interference (RNAi) for plants

As we are facing global population development, strategies are required to improve agricultural production in the battle against hunger and poverty. Agricultural biotechnology provides a powerful method in combination of conventional breeding, new innovations and enhanced management of resources which improves the productivity of livestock, aquaculture, and crops. After the finding of RNA interference (RNAi), researchers have made considerable growth in improving this remarkable crop especially in defence technology. RNA interference is a vital plant growth, development and reaction regulator to various types of stresses. This technology leads to higher efficiency and potency of gene silencing, thus becoming the highly promising technology for crop improvements at a rapid rate with some advantages. Nowadays, RNAi has been widely used for the improvement in agricultural biotechnology and seems to be applicable and commercialized in other fields too

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