DG System Research Articles

MARCO LEGAL DA GERAÇÃO DE ENERGIA PRÓPRIA: O QUE MUDA PARA O CONSUMIDOR

In the early days, man sought to create new technologies to reduce the effort of activities essential to his existence, and much of this search took place through the use of new energy sources. The research is extremely relevant, opinions differ, although some see the legal framework of distributed generation as a new step towards enabling the growth of the Brazilian solar industry. In the case of a constitutional right, the right to a properly balanced environment. In view of this, Absolar estimates that the country’s own energy generation totals 9 gigawatts. In this way, the question arises: Legal framework for own energy generation: what changes for the consumer? The general objective of the research was to understand the legal framework of own energy generation and what changes for the consumer. The type of research carried out in this work was a literature review, in which books, dissertations and selected scientific articles were consulted through a search in the following book databases, database sites. That is, the credits generated by DG systems are no longer deducted from this part of the energy bill. The observations made through the text research, on the other hand, exempts distributed generation producers from paying the availability fee.

An Islanding Detection Method Based on the Reactive Power Disturbance for Multiple Inverter-Based DG Systems

In this paper, an islanding detection method for multiple inverter-based distributed generation systems is proposed, which is based on perturbing reactive power output. An asymmetric form of positive and negative reactive power disturbance is presented so that there always exists a certain total amount of disturbance in the system. To decrease the disturbance amplitude without expanding the non-detection zone, a positive feedback of frequency difference is added to the disturbance. A reactive power disturbance synchronization method without communication among inverters is proposed so that the averaging effect caused by unsynchronized reactive disturbances can be eliminated and the island can be detected in a multiple-DG system. Additionally, the islanding detection criterion is improved by establishing the relationship between the direction of disturbance and the numerical symbol of frequency difference, so there is no misjudgment of islanding detection in a weak grid. Finally, an experimental platform consisting of three 6kW three-phase grid-connected inverters and a 99.9kVA islanding detection test device is established. The experimental and simulation results indicate that the proposed method performs fast and precise islanding detection for the multiple-DG system with small NDZ and little impact on power quality. Additionally, no misjudgment happens in a weak grid.

Comparison of a Novel AFPSO-SFS & PSO-SFS Approaches for Islanding Protection of Inverter-Based DGs

The most significant of the active islanding detection techniques is “Sandia Frequency Shift” (SFS), and this employs frequency drifting to identify extra Nondetection Zone. Inappropriate tuning parameters, such as the acceleration factor and chopping factor, result in frequency drifting, which degrades the quality of the power and causes the continuous power mode to fail. The failure can be overcome by considering optimized parameters to identify the nondetection zone (NDZ) in small DG system (120 kVA) at constant power/current mode. This article discusses, a new Adaptive Fuzzy Particle Swarm Optimization-SFS (AFPSO-SFS) technique is recommended to attain optimal parameters of SFS anti-islanding detection technique for validation of the proposed algorithm Particle Swarm Optimization–SFS (PSO-SFS) is also implemented. Furthermore, the ability of this method is to identify an islanding situation which deteriorates the major scientific issues for small DG system. Thus, the optimized parameter helps to attain an anti-islanding as well as less impact on power quality. Moreover, this article concerns serious issue of the grid interconnected DG model in an islanding condition, when the utility line would be unintentionally isolated. The grid detachment is generally considered as a fault. When an islanding occurs, the DG protection system must be inactive to detect the fault. For the investigation of power mismatches, the output of considered system using the proposed methods is contrast with results obtained from PSO-SFS and conventional SFS. The recommended strategy analyzes islands more effectively and diagnoses nondetection zones more accurately. The recommended method’s reliability is calculated quantitatively and emulated with MATLAB/Simulink.

Network losses with photovoltaic and storage

Recent development of dispersed generation technologies employing sustainable energy resources has encouraged the entry of power generation at distribution level. The close distance between load and generation reduces the network losses. However, DG system with electronic devices gives harmonic distortion. Harmonics introduce additional losses and could cause premature ageing as well as earlier re-investment of network components. This paper examines the network losses of a grid-connected photovoltaic (PV). The fundamental and harmonic losses of main network components, including transformer and cables, are calculated and compared among three cases: 1) without PV, 2) with PV, and, 3) with PV and storage.

Power Flow Control of the Grid-Integrated Hybrid DG System using an ARFMF Optimization

A power flow control scheme for a grid-integrated Hybrid DG System (HDGS) is presented in this work, utilizing an advanced random forest algorithm combined with the moth-flame optimization (ARFMF) approach. The proposed control scheme combines the random forest algorithm (RFA) and moth-flame optimization algorithm (MFO) for consolidated execution. The random forest algorithm (RFA), an AI technique, is well-suited for nonlinear systems due to its accurate interpolation and extrapolation capabilities. It is an ensemble learning method that combines multiple decision trees to make predictions. The algorithm constructs a forest of decision trees and aggregates their predictions to produce the final output. The moth-flame optimization (MFO) process is a meta-heuristic optimization procedure inspired by the transverse orientation of moths in nature. It improves initial random solutions and converges to superior positions in the search area. Similarly, the MFO is effective in nonlinear systems as it accurately interpolates and extrapolates arbitrary information. In the proposed technique, the RFA performs the calculation process to determine precise control gains for the HDGS through online implementation based on power variation between the source side and the load side. The recommended dataset is used to implement the AI approach for online execution, reducing optimization process time. The learning process of the RFA is guided by the MFO optimization algorithm. The MFO technique defines the objective function using system information based on equal and unequal constraints, including the accessibility of renewable energy sources, power demand, and state of charge (SOC) of storage systems. Storage devices such as batteries stabilize the energy generated by renewable energy systems to maintain a constant, stable output power. The proposed model is implemented on the MATLAB/Simulink platform, and its execution is compared to previous approaches.

Zero power mismatch islanding detection algorithm for hybrid distributed generating system

Distributed generation is essential for both keeping up with the rising power demand and reducing the amount of money spent on fossil fuels. There is widespread agreement that the world should prioritize the development of renewable energy systems such as wind and solar energy. This study describes the design and utility-grid integration of a hybrid distributed generating system that utilizes photovoltaic and wind-driven permanent magnet synchronous generators (hybrid PMSG-PV systems). To prevent damage to the grid, hybrid distributed generation systems, consumer devices, and line workers must be protected from islanding. Detection of islanding in hybrid DG systems has been suggested using passive islanding and time-spectral analysis. Measuring and amplifying the ripple content present in voltage at point of common coupling (PCC) about 0.4 seconds after the permissible delay time after the circuit breaker opens on the utility grid side is how islanding is discovered using this method. Compared to other methods, the proposed method has smoother islanding detection waveforms owing to increases in both the window size and threshold limit. The suggested method detects islanding in 40 ms and is verified in a variety of non-islanding scenarios, such as fault occurrence, parallel feeder loss, and load shift. In addition, the cost is reduced, the response time is rapid, and there is no non-detection zone (NDZ) when using these methods. Unlike active islanding detection methods, their function is unaffected by the size, quantity, or type of distributed generators linked to the utility grid; hence, there are no power quality concerns.

RFMFA Technique for Islanding Detection Scheme in Integrated DG System

EEE 1547 specifies time limits for the completion of DG interconnection tasks, and one of these tasks is the detection of islanding, which must be completed within two seconds of the task's start. This thesis provides new and effective islanding detection algorithms for a hybrid distributed generating system connected to the grid. The suggested technique is a hybrid of two different optimization algorithms: Random Forest (RF) and Moth Flame Optimization (MFO). At the objective stage, this technique employs the ROCOF. The suggested methods are distinguished by their ease of use due to the lack of a mandatory minimum. Furthermore, they are unaffected by the capacity or kind of Distributed Generation linked to the utility grid and not affected by system factors. In addition, the NDZ is not present after applying these processes. When compared to the standard approaches, these methods show a marked improvement in their ability to classify events into islanding and non-islanding categories. Several elements, including varying load situations, switching operations, and network conditions, must be considered before determining the proposed solutions' viability. The MATLAB/Simulink platform provides a setting where the suggested procedures may be implemented.

Frequency-Locked Loop Based New Automatic Phase-Shift Method for Active Islanding Detection of Three-Phase MicroGrid

This paper proposes an active Islanding Detection Method (IDM) integrating Frequency Locked-Loop (FLL) for the detection of voltage phase and frequency at the point of common coupling (PCC) and a modified Auto Phase Shift (APS) method for three-phase Distributed Energy Resource (DER) serving a local RLC load. The FLL is composed of a double second-order generalized integrator (DSOGI) to attenuate the harmonics and pass the fundamental positive sequence components in a frequency adaptive manner. Different from traditional APS methods, a new variable frequency term with an exponential factor is injected into the phase shift algorithm to reduce the region of Non-Detection Zone (NDZ). This modified approach enables the decentralized power generation system to detect the islanding phenomenon more quickly. Simulations and experimental tests conducted on a DG system on OPALRT (OP5600) and hardware test-bed demonstrate the behaviour of the proposed model within IEEE Standards. Additionally, a comparative evaluation was performed on the seamless transition of a microgrid (MG) from Grid-connected mode to Islanded mode and vice versa, using two different MGs, each having a single voltage source converter (VSC) and a local load but with control circuits incorporating DSOGI-FLL and ROGI-FLL respectively. Hardware testing results indicated that the control circuit based on ROGI-FLL demonstrated superior performance.

Predicting the stability of smart grid for improving the sustainability using distributed generation technology

Distributed Generation balances the supply in the grid effectively. Numerous distributed power generation technologies need more efficiency, cost, and power output to meet the energy requirements. Hence, this paper has aimed to provide an efficient DG system by integrating a PV module with a smart grid through a 3-phase AC-DC converter. Numerous PV modules are combined through DC linking, and different inverter control strategies are used to control the network. The ANN algorithm is used to optimize the demand and supply in the network. PV modules are included in the network to boost up the renewable energy source for the network. The power generated from the PV module is converted to DC through 3 phase AC-DC converter. A DC-link modeling is carried out between various converters and PV modules. It helps balance the variation in the DC input from the PV modules converted by AC-DC converters. The input current is again sent into a closed-loop inverter system to control the input current appropriately based on the demand. The problems between demand and supply are sorted through an ANN algorithm that optimizes the whole model based on supply and demand. The whole is simulated, and the results obtained are discussed in detail. The results are compared with similar Distributed power generation technologies to compare their efficiency. The comparison clearly shows that the proposed model provides better environmental sustainability and expandability to the system.

Performance Analysis of Microgrid Using Wind Power Based on Steady-State Voltage Stability

This investigation is done for augmentation of steady-state voltage stability in microgrid with doubly fed induction wind generator for the growing need of DG systems in distribution and transmission network. A poor stability in voltage reduces the efficiency of the distributed generation system (DGs). Double Fed Induction Generator (DFIG) is a type of induction generator interconnected into microgrid and it acting an essential role during the performance of microgrid in distributed generation systems of distribution network. The performance characteristics of microgrid with DFIG is analyzed and improved by control strategy. The PI (proportional and integral) control strategy of microgrid with DFIG rooted in double-fed induction generator (DFIG) in pitch angle control in the energy storage system (ESS). The performance analysis microgrid with DFIG is implemented by means of simulink platform in MATLAB software. The outcome was evaluated in this article in favor of steady-state voltage stability enhancement in microgrid with DFIG. This work is done for the achievement of a stable operation microgrid in DG system against disturbances in wind. The proposed work is intended to produce 1.58 MW of reactive power without controller and 0.48 MW, 0.36 MW, and 0.32 MW of power with P, PI, and PID (Proportional–Integral–Derivative) controller with PAC.

An Extensive Review and Analysis of Islanding Detection Techniques in DG Systems Connected to Power Grids

Nowadays, the integration of distributed generators with the main utility grid is highly increasing due to the benefits which can be obtained, such as increasing the system efficiency and reliability. Apart from that, many technical and safety issues appear in the system due to this integration. One of these issues is the islanding condition, which has to be detected effectively and quickly before having any detrimental effects on the protection, stability, and security of the system. This study provides a detailed overview of several islanding detection approaches, which are divided into traditional methods, including local and remote methods, and modern methods, including methods based on signal processing and computational intelligence. Moreover, a comparison between each method based on various criteria, such as non-detected zone, quality factor, response time, implementation cost, degrading power quality, reliability, suitability for the type of distributed generators, suitability for multi-distributed generators system, and sensitivity to cyber-attacks, is carried out. Therefore, this review will offer a solid background in order to help researchers interested in this field distinguish between islanding detection methods and their relative advantages and disadvantages, as well as to be able to choose the most suitable islanding detection method among the others to be implemented in the network.

Implementation of artificial neural network based control for power quality enhancement of proton exchange membrane fuel cell powered distributed generation system

In this paper, a fuel cell and battery-based distributed generation system is demonstrated. A proton exchange membrane fuel cell is the primary power generator in this decentralized system, with a lead-acid battery providing backup power. A boost converter regulates the fuel cell’s output power to ensure its optimal performance. A bidirectional buck-boost converter has been employed to integrate battery using slope compensated current control. 5-level cascaded H-Bridge inverter is used to convert available DC power into AC power while integrating DG systems with the grid and improving power quality. The artificial neural network has been trained and used to generate the estimated reference current for sinusoidal pulse width modulation techniques. The artificial neural network has been fine-tuned using the scaled conjugate gradient with the performance value 0.094056. The THD of grid current has been reduced by 12.5% and 8.14% approximately for 30 Ω resistive, 30 mH inductive load and 20 Ω resistive, 15 mH inductive load respectively. The system has been simulated in Matlab/Simulink, and the findings have been validated. The results demonstrate the effectiveness of the methodology.

Developing an advanced reliability analysis framework for marine systems operations and maintenance

Power generation system reliability is of great concern for all ship operators irrespective of sector, as it provides the highest utility and ensures collective safety of operators, passengers, equipment and cargo. A novel approach to system reliability analysis using DFTA, FMECA and BBN applied to 4 DGs has been conducted. The outcomes provide insight on faults and component criticality to vessel maintenance and availability. Building from the understanding of how multiple factors can influenced maintenance in addition to routine or age-related wear and tear of machinery. This research looked into operators’ peculiar challenges regarding environment, operational demands and technology challenges that affects maintenance and system reliability. A framework based on outputs from DFTA minimal cut set, RPN from FMECA were used as inputs for BBN to analyse ship marine DG system availability. A BBN influence diagram was used to build a maintenance strategy DSS. Overall outcome for the maintenance strategy selection DSS indicates relatively high unavailability. Therefore, DGs with low availability were recommended to be on Corrective action and ConMon, while DGs with good availability were recommended to be on PMS.

An Advanced Control and Stability Analysis of Wind Solar Integrated Microgrid

In this article, we suggest a micro-grid methodology based on renewable energy sources (RES) in order to make more efficient use of renewable energy sources and use less energy from the traditional power grid. Off-grid, RES likes solar (generated by a photovoltaic panel) and wind can be stored in a battery and utilised to power loads. As an additional measure, a Fuzzy logic-based energy-saving method has been applied. Microgrids are used to integrate these systems in a decentralised fashion, and they provide a suite of technology solutions that facilitate communication between end users and dispersed power plants. This raises the question of how best to administer these systems. In order to guarantee that both the generating and distribution systems produce energy at low operating costs, energy management in microgrids is described as a data and monitoring network that allows the required functions. In this study, we discuss the difficulties associated with using RES and managing a microgrid. Voltage and frequency variations result from the dynamic nature of DG systems. Unpredictable dynamics result from the load's unknowability. As a result of this nonlinear dynamic, there are observable changes to the microgrid's operation. In this study, we test the efficiency of the microgrid in a variety of settings. We compare the PI controller's performance on the MATLAB/Simulink platform to that of a Fuzzy logic-based controller with various levels of complexity.

An Advanced Control and Stability Analysis of Wind Solar Integrated Microgrid

In this article, we suggest a micro-grid methodology based on renewable energy sources (RES) in order to make more efficient use of renewable energy sources and use less energy from the traditional power grid. Off-grid, RES likes solar (generated by a photovoltaic panel) and wind can be stored in a battery and utilised to power loads. As an additional measure, a Fuzzy logic-based energy-saving method has been applied. Microgrids are used to integrate these systems in a decentralised fashion, and they provide a suite of technology solutions that facilitate communication between end users and dispersed power plants. This raises the question of how best to administer these systems. In order to guarantee that both the generating and distribution systems produce energy at low operating costs, energy management in microgrids is described as a data and monitoring network that allows the required functions. In this study, we discuss the difficulties associated with using RES and managing a microgrid. Voltage and frequency variations result from the dynamic nature of DG systems. Unpredictable dynamics result from the load's unknowability. As a result of this nonlinear dynamic, there are observable changes to the microgrid's operation. In this study, we test the efficiency of the microgrid in a variety of settings. We compare the PI controller's performance on the MATLAB/Simulink platform to that of a Fuzzy logic-based controller with various levels of complexity.

Technoeconomic Analysis of a Hybrid Energy System for an Academic Building

This work is mainly based on the optimal design of a standalone Hybrid Renewable Energy System (HRES) consisting of PV/diesel/battery systems, implemented in an academic building. Different hybrid system configurations such as PV-diesel generator-battery, diesel generator-battery, and PV-diesel generator are compared based on Net Present Cost (NPC) and Cost Of Energy (COE) to find out the best economically viable and environmentally friendly solution. Li-ion and lead-acid batteries were taken into consideration, and the optimization was done in HOMER PRO software. The PV-DG-Li-ion battery configuration emits approximately 2825387kg/year CO2 whereas the conventional DG system emits 4565074kg/year. It is concluded that the PV-DG-Li-ion battery configuration provides the cleanest and most environment-friendly and techno-economically feasible solution.

Analysis of multi-distributed generation systems based on solar/biomass/natural gas/diesel energy resources for off-grid application

This study presents the analysis of multi-distributed generation systems for 20 off-grid homes in Ogun State based on the techno-environmental analysis planning (TEAP) approach. The technical aspect includes the load, DG capacities, energy generation/year, and the unmet energy demand (UED. The paper considers and compares different energy configurations such as the PV-based DG, the hybrid DGs: PV/biogas, PV/biogas/natural gas, PV/biogas/diesel, PV/diesel, and the diesel-based DGs. The environmental aspect examines the emissions produced by the DGs compared to a diesel-based DG system. The paper also examines the effect of temperature on the performance of the PV system. The simulation is based on a total daily demand of 99.04 kWh/d, and the solar, ambient temperature and the biomass data in Hybrid Optimization of Multiple Energy Resources (HOMER) environment. The size of the PV-based DG obtained is 36.9 kW, which generates 54,565 kWh/yr without temperature effect. Result shows that this value reduced to 48,268 kWh/yr with temperature effect and the value of UED is 7.84 %. The biogas, natural gas and diesel generators have the same size of 13.2 kW. The hybrid DGs achieve a UED of 0% implying 100 % system availability. Results further demonstrate that the mentioned hybrid DGs have CO2 emissions that range between 2.21 and 15, 448 kg/yr, compared to a value of 40, 273 kg/yr obtained when the homes are entirely run on a diesel-based DG. The study can help to understand energy systems analysis.

Optimal Sizing and Techno-Economic Analysis of Grid-Independent Hybrid Energy System for Sustained Rural Electrification in Developing Countries: A Case Study in Bangladesh

The absence of electricity is among the gravest problems preventing a nation’s development. Hybrid renewable energy systems (HRES) play a vital role to reducing this issue. The major goal of this study is to use the non-dominated sorting genetic algorithm (NSGA)-II and hybrid optimization of multiple energy resources (HOMER) Pro Software to reduce the net present cost (NPC), cost of energy (COE), and CO2 emissions of proposed power system. Five cases have been considered to understand the optimal HRES system for Kutubdia Island in Bangladesh and analyzed the technical viability and economic potential of this system. To demonstrate the efficacy of the suggested strategy, the best case outcomes from the two approaches are compared. The study’s optimal solution is also subjected to a sensitivity analysis to take into account fluctuations in the annual wind speed, solar radiation, and fuel costs. According to the data, the optimized PV/Wind/Battery/DG system (USD 711,943) has a lower NPC than the other cases. The NPC obtained by the NSGA-II technique is 2.69% lower than that of the HOMER-based system.

Optimal Planning of Remote Microgrids with Multi-Size Split-Diesel Generators

This paper proposes a multi-size Split-diesel generator (Split-DG) model with three different sizes of DGs and more switching configurations compared to the existing split-DG models. The proposed multi-size Split-DG system is examined for optimal sizing of remote microgrids with and without renewable-battery system. As a novel concept, multi-size Split-DG is used to reduce contamination, cost, and dumped power by using multiple small DGs to replace the single-size large DG. As another contribution of this study, a practical model is developed by considering the capacity degradation of components, spinning reserve, as well as DG’s and fuel tank’s constraints. The optimization problem is solved using a variable weighting particle swarm optimization (VW-PSO) algorithm. The effectiveness of the proposed Split-DG systems, optimized by the developed VW-PSO, is verified by comparing the results with conventional single-size DG system and the system optimized by conventional PSO. While the formulated optimization problem is general and can be used for any remote microgrids, an aboriginal community in South Australia is examined in this study. For this purpose, realistic data of load and weather, as well as technical and economic data of components, are used. It is found that the Split-DG-PV-WT-BES system has the lowest electricity cost compared to the systems without BES, or without PV and WT.

Geographic information-driven two-stage optimization model for location decision of solar power plant: A case study of an Algerian municipality

This paper presents an interdisciplinary framework for optimal mapping and integration of solar photovoltaic based DG systems. In a two-stage process, the proposed framework combines both spatial and technical-economic analysis, and uses efficient optimization techniques to make decisions. First, a GIS and a MCDM are used to identify the sites with the highest potential for hosting PV power plants. Second, the Backward-Forward Sweep (BFS) load flow algorithm is used to investigate nominated sites, taking into account three indices, namely, active power losses, VSI, and voltage profile improvement. In addition, a techno-economic feasibility assessment is performed based on the characteristics of a real distribution grid in N'goussa region, Algeria. The results show that 78% of the studied area is suitable for installing PV farms. The optimal zone represents only 1.52% of the obtained suitable area. In addition, two zones are eliminated from 7 suitable zones, as they are too far from the existing grid busbars. Based on the BFS method, and considering VSI and voltage profile, the busbar 104 is the optimal point for the connected PV-farm. Furthermore, the techno-economic assessment for the investigated system indicates that the LCOE is decreased by 0.4 $/kWh for each penetration-rate.