25 research outputs found
A Framework for Profit Maximization in a Grid-Connected Microgrid with Hybrid Resources Using a Novel Rule Base-BAT Algorithm
In this paper, an energy management system (EMS) is proposed for optimal operation of a microgrid (MG). Dispersed photovoltaic arrays (PVs) and wind turbine generators (WTs) as renewable energy sources (RES) supply a major part of the network demanded energy. Also, an energy storage system (ESS), a micro-turbine unit (MT), and a fuel cell unit (FC) are integrated. The uncertainty and stochastic nature of the network load and RES data are treated via probabilistic modeling and scenario-selection approach. The predicted day-ahead data of the most diverse hourly scenarios are entered into the proposed EMS to determine the active and reactive power (P-Q) participations of local distributed resources. Likewise, it specifies the discharging/charging power and state of the ESS in addition to the exchanged active/reactive power amounts with the main network. The main goal is to maximize the profit of the secondary grid while satisfying all technical constraints. In the proposed EMS, the day-ahead energy management is developed as a comprehensive optimization problem. Moreover, the paper proposes novel modifications to improve the BAT optimization technique. The optimization problem of the energy management in the microgrid is implemented using a new integrated rule base-improved BAT method. Furthermore, the proposed EMS competence is proven by comparing its performance to recent literature. © 2013 IEEE.Ministry of Higher Education, Egypt, MHEThis work was supported by the Ministry of Higher Education, Egypt
Power management and control strategies for off-grid hybrid power systems with renewable energies and storage
This document is the Accepted Manuscript of the following article: Belkacem Belabbas, Tayeb Allaoui, Mohamed Tadjine, and Mouloud Denai, 'Power management and control strategies for off-grid hybrid power systems with renewable energies and storage', Energy Systems, September 2017. Under embargo. Embargo end date: 19 September 2018. The final publication is available at Springer via https://doi.org/10.1007/s12667-017-0251-y.This paper presents a simulation study of standalone hybrid Distributed Generation Systems (DGS) with Battery Energy Storage System (BESS). The DGS consists of Photovoltaic (PV) panels as Renewable Power Source (RPS), a Diesel Generator (DG) for power buck-up and a BESS to accommodate the surplus of energy, which may be employed in times of poor PV generation. While off-grid DGS represent an efficient and cost-effective energy supply solution particularly to rural and remote areas, fluctuations in voltage and frequency due to load variations, weather conditions (temperature, irradiation) and transmission line short-circuits are major challenges. The paper suggests a hierarchical Power Management (PM) and controller structure to improve the reliability and efficiency of the hybrid DGS. The first layer of the overall control scheme includes a Fuzzy Logic Controller (FLC) to adjust the voltage and frequency at the Point of Common Coupling (PCC) and a Clamping Bridge Circuit (CBC) which regulates the DC bus voltage. A maximum power point tracking (MPPT) controller based on FLC is designed to extract the optimum power from the PV. The second control layer coordinates among PV, DG and BESS to ensure reliable and efficient power supply to the load. MATLAB Simulink is used to implement the overall model of the off-grid DGS and to test the performance of the proposed control scheme which is evaluated in a series of simulations scenarios. The results demonstrated the good performance of the proposed control scheme and effective coordination between the DGS for all the simulation scenarios considered.Peer reviewedFinal Accepted Versio
A new algorithm for allocating multiple distributed generation units based on load centroid concept
Allocation of distributed generation (DG) units is commonly formulated as a constrained nonlinear optimization problem solved by complex iterative mathematical or heuristic techniques. Heavy computational burden, very long solution time, probable divergence and possibility of getting only a sub-optimal solution are some serious drawbacks. In this paper, a systematic simple approach to allocate multiple DG units in radial/meshed distribution network is proposed. The concept of equivalent load is introduced and extended to identify the load centroid precisely with two methods. A performance index that combines the power system real power loss and average node voltage is defined. Based on load centroid and performance index, a straightforward algorithm for sizing and locating multiple DG units is developed. The proposed technique is applied to radial and meshed test systems. Results confirm stability, integrity and efficacy of the proposed approach
Proposed wavelet-neurofuzzy combined system for power quality violations detection and diagnosis
Optimal allocation of fault current limiters for sustaining overcurrent relays coordination in a power system with distributed generation
This paper addresses the problem of overcurrent relays (OCRs) coordination in the presence of DGs. OCRs are optimally set to work in a coordinated manner to isolate faults with minimal impacts on customers. The penetration of DGs into the power system changes the fault current levels seen by the OCRs. This can deteriorate the coordinated operation of OCRs. Operation time difference between backup and main relays can be below the standard limit or even the backup OCR can incorrectly work before the main OCR. Though resetting of OCRs is tedious especially in large systems, it cannot alone restore the original coordinated operation in the presence of DGs. The paper investigates the optimal utilization of fault current limiters (FCLs) to maintain the directional OCRs coordinated operation without any need to OCRs resetting irrespective of DGs status. It is required to maintain the OCRs coordination at minimum cost of prospective FCLs. Hence, the FCLs location and sizing problem is formulated as a constrained multi-objective optimization problem. Multi-objective particle swarm optimization is adopted for solving the optimization problem to determine the optimal locations and sizes of FCLs. The proposed algorithm is applied to meshed and radial power systems at different DGs arrangements using different types of FCLs. Moreover, the OCRs coordination problem is studied when the system includes both directional and non-directional OCRs. Comparative analysis of results is provided
NRAAF: A Framework for Comparative Analysis of fMRI Registration Algorithms and Their Impact on Resting-State Neuroimaging Accuracy
The rapid evolution of neuroimaging techniques underscores the necessity for robust medical image registration algorithms, essential for the precise analysis of resting-state networks. This study introduces a comprehensive modular evaluation framework, designed to assess and compare the differences of four state-of-the-art algorithms in the field: FSL, ANTs, DARTEL, and AFNI. Our framework highlights the critical importance of algorithm selection in neuroimaging, addressing the unique challenges and strengths each algorithm presents in processing complex brain imaging data. Our rigorous evaluation delves into the algorithms’ differences, with a focus on spatial localisation accuracy and the fidelity of resting-state network identification. The comparative analysis uncovers distinct advantages and limitations inherent to each algorithm, illuminating how specific characteristics can shape neuroimaging study outcomes. For instance, we reveal FSL’s robustness in handling diverse datasets, ANTs’ precision in spatial normalization, DARTEL’s suitability for large-scale studies, and AFNI’s adaptability in functional and structural image analysis. The findings highlight the nuanced considerations necessary in choosing the right registration algorithm for neuroimaging data, advocating for a bespoke approach based on the unique requirements of each study. This detailed analysis advances the field, guiding researchers towards more informed algorithm selection and application, thus aiming to improve the accuracy and reliability of neuroimaging outcomes. Presenting a clear, comprehensive overview of each algorithm within our novel framework, the study addresses the needs of the neuroimaging community and paves the way for future advancements in medical image registration
Co-digestion of concentrated black water and kitchen refuse in an accumulation system within the DESAR (decentralized sanitation and reuse) concept
Co-digestion of concentrated black water and kitchen refuse within the DESAR concept was the objective of this pilot research. The digestion took place in two, non-mixed accumulation reactors (AC1 and AC2) inoculated with digested primary sludge from a WWTP at a temperature of 20degreesC for a period of around 150 days. Reactor AC1 was fed with a mixture of faeces, urine and kitchen refuse in the equivalent amount that one individual generates per day. The AC2 was fed with a mixture of faeces and kitchen refuse in the equivalent amount that two individuals produce per day. Some contribution of urine to AC2 was not to be avoided. Detailed characterisation of waste(water) was performed. The performance of the stratified reactor was followed by monitoring the reactor content for several reactors' heights as well as being based on the biogas production. In general the system exposed good process stability. The methanisation of 34 and 61% was obtained for AC1 and AC2 respectively. The biogas yield was 26.5 and 50.8 L/p/d for the respective reactors. Proper choice of inoculum as well as good buffering capacity did not lead to accumulation of VFA and an inhibitive effect due to relatively high ammonium concentration. The chosen process is a promising technology showing good process stability especially for high strength influent
Anaerobic biodegradability and treatment of Egyption domestic sewage
The anaerobic biodegradability of domestic sewage for four Egyptian villages and four Egyptian cities was determined in batch experiments. The results showed that the biodegradability of the Egyptian-villages sewage (73%) was higher than that of the cities (66%). The higher biodegradability of the soluble COD of village sewage (69%) as compared to that of the cities (46%) was the reason for the higher biodegradability of the total COD of the villages sewage. The biodegradability of suspended COD was similar for the sewage of both villages and cities (73-74%). The results of a mathematical-model, developed based on anaerobic digestion model number 1, indicate that at applying a UASB reactor for the treatment of Egyptian villages and cities sewage, an optimum HRT of, respectively, 16 and 8 h is required. At these HRTs, a total COD removal and a conversion to methane of, respectively, 62-70% and 59-64% can be achieved for the sewage of cities and, respectively, 71-77% and 67-69% for the villages sewage. The model results also show that in the treatment of villages sewage in a two-step (anaerobic filter + UASB reactor) system a higher total COD removal can be obtained (77-81%) at a short HRT of 10 h (4 + 6 h). However, the excess sludge from the first-step of the two-step system will be less stabilize