DG Sources Research Articles

Real Power Losses Reduced by Network Reconfiguration the Distribution Systems using Modified BAT Algorithm

This research paper is proposed to achieving the minimum power losses in all the branches, minimum number of switching operations, maximizing the power flow through the placing the DG sources, minimizing the voltage deviations with satisfying all the constraints using the modified BAT algorithm. The effect of the offered method is tested on standard systems like IEEE 33, 69 buses and Indian standard 62 bus distribution systems. The mBAT effect is estimated with the recent algorithm including Shuffled Frog, Stud krill, Dingo, Grey Wolf, and Antlion algorithms. MATLAB results are proved that the total power active power losses and branch voltages and number of switches, capacity of DG sources and cost of the DG sources are drastically reduced. The results are compared with many techniques are tabulated. Moreover, the mBAT algorithm is more superior and confirmed with other animal-related algorithms like Antlion, Grey wolf, Gross Hopper, Dingo, sturd Krill, cuckoo crunch algorithm and Shuffled Frog algorithms. In view of more speed of convergence and high accuracy and processed in less number repetition. Also, the results of the proposed techniques are encouraging and helpful to future research.

Optimum management of microgrid generation containing distributed generation sources and energy storage devices by considering uncertainties

In recent years, the financial and energy crises have made the economical and safe operation of distribution microgrids one of the main challenges for operators. In this regard, the optimal distribution of the microgrid, considering the favorable indicators of Generation and consumption, significantly improves the quality of the development and economic operation of electricity grids. On the other hand, distribution microgrids have many problems and complications due to the presence of DG sources and the uncertainties caused by them in Generation and consumption, such as the inability to solve optimal load distribution using common and common calculation methods. Therefore, grid technical indicators such as voltage deviation and losses in solving load distribution add to the complexity of related issues. To solve the challenges raised in the distribution microgrid, this paper proposes an optimal load distribution model that models the uncertainties in the distribution microgrids using the Monte Carlo method. Using meta-heuristic algorithms, the optimal Generation function by modeling grid security constraints such as voltage deviation, losses, and a load limit of the system should be in economic operation mode, and then the power distribution equations should be solved. The battery can supply 1 kW of active power to the system at a cost of 1 unit/kW during the high cost period if it absorbs 1 kW of active power at a cost of 0.92 units/kW during the low cost period. Additionally, the active and reactive power losses have been decreased to 0.3kW and 0.2kW, respectively, by utilizing the suggested methodology. The simulation results show that the proposed method performs satisfactorily and that the modeling is simulated in MATLAB software.

FEATURES OF CREATION OF THE SMART MONITORING SYSTEMS FOR MICROGRIDS

In this paper, an analysis of the main requirements for control systems in Microgrid is conducted. The main objectives of the implementation of Microgrid systems were determined and, based on the performed analysis, the requirements for Smart-monitoring systems were systematized. The components of Smart-monitoring systems, which include: communication software platform, hardware communication platform and types of equipment of DG sources for Microgrid systems were analyzed. It is proposed to build Smart-monitoring systems for Microgrid systems on the basis of the SGAM model, taking into account various models of aggregation of different types of DG sources within the framework of Microgrid systems. The proposed structure of the Smart-monitoring system for Microgrid systems with various DG sources makes it possible to effectively aggregate DG sources and prosumers and to carry out effective dispatching of generating capacities based on market mechanisms of their interaction with consumers and among themselves.

ПОБУДОВА МОДЕЛЕЙ ОПТИМАЛЬНОЇ ВЗАЄМОДІЇ ДЖЕРЕЛ РОЗОСЕРЕДЖЕНОЇ ГЕНЕРАЦІЇ ТА СИСТЕМ АКУМУЛЮВАННЯ ЕНЕРГІЇ У МЕЖАХ MICROGRID СИСТЕМ

The Problems of integration of DG and RES, as well as energy storage systems (ESS) in the Microgrid systems are investigated in this paper. It is proposed to consider Microgrid models of systems with different types of DG and RES (DER) within the framework of the SGAM architecture, and to distinguish three types of DG and ESS: " Non controllable DER (T1)", "Controllable DER (T2)" and "DER with storage systems (T3)" with further division into subtypes. This method makes it possible to display the multifaceted interaction of systems with DER and ESS within the framework of Microgrid systems. On the basis of the proposed mechanism, the formulation of the problem of optimal interaction of DG sources and ESS within the boundaries of Microgrid systems within the framework of game theory is formalized. An optimization procedure is proposed within the framework of a formalized game, which is based on mechanisms of dynamic pricing and allows to find the most optimal solutions for the game task. References 13, figures 8, table 1.

Using Arithmetic Optimization Algorithm to Allocate and Size Wind Energy Systems in RDSs

Recent years have seen a marked increase in the world’s energy needs. Numerous studies have been conducted to examine distributed generation (D.G.) utilizing renewable energy sources (R.E.S.s) in order to address this need. The number of environmental problems that are resolved by the usage of traditional power plants is also decreased by these renewable sources. The ideal position and size of the RESs-DG significantly influence the bus voltage profile, power quality, and efficiency of Radial Distribution Systems (RDS) because of power losses. In this study, the use of wind energy systems as a DG source in RDS is investigated. One of the most common RESs used as DG sources, the ideal location and size for wind system, was chosen to demonstrate this enquiry. The goal of this optimization work, which used the Arithmetic Optimization Algorithm (AOA), was to increase system efficiency by minimizing power losses and improving the voltage profile and power quality. Three widely used RDS, including the IEEE 31 and 69 bus systems, have been used to evaluate how well the recommended technique has been implemented. Genetic Algorithm (GA) is offered to examine the efficacy of the recommended AOA. The findings show that the used AOA approach can pinpoint the appropriate size and positioning of a wind farm in order to reduce power loss, enhance voltage profile, and outperform other existing tactics with superiority over GA.

Optimal Power Control in Distributed Generation Units in an Islanded Microgrid

This article studies the effect of new optimization techniques with the aim of finding the best solution using a fuzzy approach for operating an independent microgrid. The power flow technique is used to model and solve the problem of optimal active and reactive power control of distributed generation units (DGs) in an island microgrid (MG), while taking into account the improvement of the voltage profile and the voltage stability index by regulating the droop characteristics of DG sources. The suggested algorithms, Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Harmony Search (HS), Hybrid HS-GA, and Teaching-Learning Based Optimization, solve the optimization issue (TLBO). The numerical results of optimization algorithms are compared in terms of best solution, number of iterations, and convergence rate. Regarding multi-objective nature of the problem, the non-dominated sorting method is used to obtain the Pareto front for all algorithms. Finally, the best solution is selected from Pareto solutions using proposed fuzzy approach. Simulation results on the standard IEEE 33-bus network in MATLAB show that the TLBO algorithm has higher efficiency, and faster convergence rate compared to other methods in this study.

Protection Challenges on Integration of Distributed Sources to Power system network: A Review

— Electricity generation has to be increased to meet various type of future load demand like LED lightning, Electrical 
 Vehicles, mobiles, communication network, non linear load etc. Automation is essential requirement now a days in each sector. 
 To provide automation at residential, commercial and industrial sectors electrical energy is required. To meet energy 
 requirement of various sector utility grid is integrated with DG Sources, which mainly include renewable energy sources like 
 solar, wind and other environment friendly sources either in large scale or small scale depends on the location and availability. 
 This type of technology leads power system to era of smart grid. Smart grid technology provides features like digitization, two 
 way communication, distributed generation, adaptive islanding, self monitoring and self mitigating, fully controllable compare to 
 conventional Grid. Though smart grid technology is advantageous but due to integration of distributed generation at 
 transmission and distribution system will increase protection challenges in the power network. This paper gives an insight of 
 different protection issues which occur at transmission, distribution and Micro grid network. The paper also focuses on the 
 techniques and solution of the various protection challenges.

Minimizing the Active Power Losses and Retaining the Voltage Profile of the Distribution System Using Soft Computing Techniques with DG Source

The motivation of this research is to curtail the active power losses in the radial distribution system. This paper proposes a novel voltage stability indicator to determine the optimum conductor sizes for various distribution lines and find the conductor stability limit. This work proposes a new BAT algorithm for finding the optimal switching configurations using reconfiguration, which is used to minimize the active power losses. The proposed BAT algorithm gives the optimal locations to place the required amount of DG sources to improve the stability and minimize the power losses and maintain the voltage profile of the systems. The proposed BAT algorithm has been executed with the MATLAB 2016 software and compared with the differential evolution technique for IEEE 33 bus, IEEE 69 bus, and Indian real time 62 bus systems. The test results are applied on different conductors, and the real power flow on the different conductors are mapped in the proposed method using the novel voltage stability indicator. The radial distribution system has lower power losses, best voltage profile, cost of saving the DG source, optimal placing of a suitable rating of the DG source, optimal location of the DG source, and cost of saving the DG source which were achieved in this work. In this research, the distributed load flow analysis is implemented to find the parameters by the forward-backward sweep algorithm. The minimum bus voltage 0.95 pu is virtual in all the conductors. The loss reduction in the DE for IEEE 33 bus has been reduced from 42.4% to 45.3% and the loss reduction in IEEE 69 bus from 36.2% to 38.8% and the real time 62 bus from 47.5% to 49.15%. The loss reduction in the BAT algorithm for IEEE 33 bus has been reduced from 38.46% to 45.3% and the loss reduction in IEEE 69 bus is from 32.2% to 38.8%. The Indian standard real time 62 bus has been reduced from 38.92% to 49.15%. The proposed results are compared with the DE and BAT algorithm. The proposed BAT algorithm is found to be more effectual in reducing voltage deviation (VD) and reducing the power losses in the system.

ANFIS based double integral sliding mode control for a grid-integrated hybrid power system

Hybrid Power System (HPS), an promising power generation strategy, has gained much popularity in recent years, thanks to its fundamental mechanism that taps the abundantly-available renewable energy sources. HPS comprises of a photovoltaic (PV) panel, a Battery Storage System (BSS) and a Solid Oxide Fuel Cell (SOFC). Here, PV is the chief power source whereas SOFC and BSS are used as backup generators to supply the required power in case when PV energy is deficient. All these sources, with distinct DC-DC converters, are integrated parallel to a same DC bus. A 3-phase Voltage Source Inverter (VSI) is used in this setup to convert DC voltage into AC. Different modes of operations have been demonstrated with conventional Sliding Mode Controller (SMC). The proposed Double Integral Sliding Mode Controller (DI-SMC)-trained Adaptive Neural Fuzzy Inference System (ANFIS) is utilized to enhance the performance and anti-interference ability of the hybrid system. Further, the HPS is also verified and validated in terms of achieving the preferred power supervision between DG sources, grid, and the load. Both modeling and control strategies of the hybrid scheme were simulated in MATLAB/Simulink. The aim of the proposed management scheme is to supply maximum-quality power to the grid under varying loading conditions and solar irradiance with FC state under consideration. Further, the management algorithm was also implemented to stabilize DC bus voltage under load variations.

СИНТЕЗ МОДЕЛЕЙ ЛОКАЛЬНИХ ЕЛЕКТРОЕНЕРГЕТИЧНИХ СИСТЕМ З ДЖЕРЕЛАМИ РОЗОСЕРЕДЖЕНОЇ ГЕНЕРАЦІЇ

The problems of integration of Microgrids which include DG sources and RES with centralized electric power systems are investigated in this paper. The main stages and tasks of synthesis of models of these systems are analyzed. Authors propose to create models of the synthesized systems based on game-theoretic approach which allows to take into account the interests (objective functions) of the models of both Microgrids and centralized systems. Such method allows to reflect the diverse interaction of the systems with DG sources and RES and centralized power systems. Based on the proposed method, the problem of multi-criterion optimization for models of such systems in the framework of game theory is formulated by authors. The procedure of optimization of the synthesized system model in a formalized game is proposed/ This procedure is based on the mechanisms of dynamic pricing and allows to find the most optimal solutions for the game task. References 10, figures 5.

Investigation of the Effects of Fuel Cells on V-Q & V-P Characteristics

In this paper, the use of a FC system connected to the network is proposed as a source of DG with high reliability, and for this purpose, the dynamic model of the fuel cell has been simulated. A hybrid system of fuel cell distributed generation (FCDG) is presented to provide electrical energy for a small isolated area. Boost converter (DC/DC), in order to increase the voltage level of the system and stabilize the DC link voltage has been used, which provides the possibility of connecting several different scattered production sources in parallel. Voltage stability is concerned with the ability of a power system to maintain acceptable bus voltages under normal conditions and after being subjected to a disturbance. The use of DG sources has many advantages, including meeting peak load needs, reducing network losses, providing reactive power locally, and regulating network voltage. Among all sources of distributed production, fuel cells are of special importance due to their high efficiency, high energy density, the ability to simultaneously produce heat and electric power, and low emission of pollutants. Using fuel cells (FCs) have several advantages and in this paper we investigate the effects of FCs on power systems via simulation a single machine (DG as small gas turbine coupled with a FC) in the Dig Silent area for different PF of FC. Different PF for FC obtained with control the DC to AC inverter. We found that by control the PF of FCs, we can increase the limitation of reactive generation of overall system and improve the V-P V-Q characteristics of overall system. With the grid-connected inverter's switching control, the active and reactive power injected into the grid is controlled independently.

Optimal Load Distribution in DG Sources Using Model Predictive Control and the State Feedback Controller for Switching Control

The distributed energy management of interconnected microgrids, which is based on model predictive control (MPC), relies on the cooperation of all the agents (i.e., microgrids). Model predictive control or MPC is widely used in industrial applications as an effective tool for dealing with multivariable limited control problems. MPC uses an explicit system model to predict the future horizon of the system and its outputs. This predictability allows calculating the optimal order of inputs to minimize output errors over a limited horizon, which is effected by the limitations of the system. This study presents a distributed economic model predictive control method using the new state feedback controller to control the switching of interface converters and compensate for the unbalanced and nonlinear loads. In this model, the islanding mode and the reconnection of the grid are considered to improve the transient behavior of the system to achieve steady-state power distribution. It has been proposed that it could obtain better results in predictive control, utilizing similarity transform in the state matrix and its modification. First, this model is simulated on distributed generation sources with power-sharing and local loads using the state feedback controller in MATLAB Simpower. Then, the performance of the proposed method is evaluated, confirming that it is more reliable than the FS-MPC and DSVM-MPC methods.

Genetic Algorithms and Satin Bowerbird Optimization for optimal allocation of distributed generators in radial system

In this document, the topic of discussion is the combination of two existing algorithms to generate a new hybrid technique. The two algorithms that are subjected to said amalgamation are Genetic Algorithms (GA) and Stain Bowerbird Optimization algorithms (SBO). These two methodologies have profound utility themselves and are used in a multitude of scenarios. The easy application and the constructive outcomes manifested by these two algorithms birthed the idea of their combined usage. Following up on this, the hybrid GASBO was created. GASBO was an optimization approach used to detect and categorize the allotted renewable energy assets in a specific energy generation complex. This was done to regulate the energy dispensing systems otherwise known as ‘distributing’ systems. These renewable resources are reflected by environmental factors and the energy they create is also dependent on their surroundings. Factors like sunlight, rain, waves, and tides etcetera play major roles in determining the outcome of the created energy.Contrary to what it may appear like, the position of the DG sources in the structure affects the outcome a lot. These sources contain fuel cells and photovoltaic cells: in short, devices that can harness energy from a seemingly infinite supply like sunlight. As mentioned before, the GASBO assisted in providing the best location for the system and it also categorized the sources according to their abilities. The potential and position of the sources in the grid are of vast importance. The main purpose of GASBO is to optimize the overall system by improving its efficiency and reducing collateral harm. This shows that GASBO is quite a fundamental tool. It has also been tested on several systems like IEEE 33-bus. The facts in this paper are based on published projects.

Genetic-Moth Swarm Algorithm for Optimal Placement and Capacity of Renewable DG Sources in Distribution Systems

Genetic-Moth Swarm Algorithm for Optimal Placement and Capacity of Renewable DG Sources in Distribution Systems

Islanding Detection Techniques for Grid Integrated DG –A Review

This paper focuses on the review of various islanding detection methods for integrated DG system. Due to the advantages of renewable power generation, the grid integration of DG sources is increasing day to day life. One of the major problems with these integrated DG systems is an unintentional islanding. The islanding is caused in the power system, if DG supplies power to local load connected after disconnecting from the main grid. As per various DG interconnection standards, the islanding should be detected within 2 seconds after islanding. The islanding detection methods are classified as remote techniques which work on utility side and local techniques which work on DG side. This paper discusses the survey of various islanding detection methods with their performance indices. The advantages, disadvantages, power quality issues, NDZ, balanced islanding detection possibility and standards of each method are presented in detail. This paper is very useful to the researchers for selecting the better method for future islanding detection.

A Real-time Operation Scheme of Microgrids with Distributed Generation in Electricity Markets

This paper addresses the operation problem of microgrids under market environments. Considering the flexibility of DG sources in operation as well as the availability of market prices, microgrid operators can improve the profit in electricity markets by properly adjusting DG units in real-time corresponding to the price signal which is updated few-hour ahead. Starting with the basic formulation of unit commitments, the paper derives the optimality condition of DG units, i.e., generation levels for maximizing the profit assuming all units are being On (committed). If the capacity constraint results in an excess of the marginal cost to the locational market price, the unit will be considered to be Off. Taken into account the cost associated with switching On/Off the unit, an economic comparison will determine the optimal decision of whether to turn the unit On/Off or remain its current state. The proposed operation scheme is examined in a case study to illustrate its effectiveness with different scenarios of the market price.

Intelligent control strategy in the islanded network of a solar PV microgrid

In the islanded mode of MG network, due to the lack of inertia and under performance of PI based inverter control, variation in power and frequency level can be expected more during the transient conditions as compared to the grid connected mode. Thus, in this study, a Particle Swarm Optimization (PSO) algorithm with the proposed cost function was implemented in the Grid-support grid-forming (GsGfm) type Voltage Source Inverter (VSI) of the DG sources (solar PV and battery unit) for the islanded photovoltaic (PV) based MG model (built in Matlab-Simulink software environment) to reduce the variation in power and frequency level. The islanded MG model was also implemented with a reverse droop based on virtual impedance control strategy for the VSI and power management control strategy to ensure better power sharing among DG sources with regulation of frequency level and power balance with co-ordinated control operation of DG sources. Implementation of PSO based intelligent control strategy for the inverters of DG units, showed substantial improvement in the performance of controller in terms of reduced settling time and overshoot in power level along with the significant reduction of the power variation and frequency variation during the transient conditions (change in load and change in solar irradiance of PV units). Also proposed PSO control strategy ensured the frequency level to be within the acceptable operating range (Australian network standard) in the islanded MG network.

Assessment of Operating Condition Dependent Reliability Indices in Microgrids

Reliability results are important for proper planning and operation of utility companies. At the base of this method of analysis is the failure rate of the system components. In the traditional method, this probability of failure is determined by the components’ manufacturer and is considered to be constant. This study proposes a dynamic modeling of failure rate, taking the system operating conditions into consideration. With this new consideration, an IEEE test system has seven of its reliability indices quantified for comparison. The inclusion of the newly modeled failure rate leads to a worsening of 11.07% in the indices, on average. A second analysis is performed considering the presence of DG sources within the microgrid, namely PV and wind based. An improvement of 0.71% on the indices is noticed, once the DG sources are introduced. Finally, the effects of storage systems in the microgrid are investigated through a third scenario, in which two 2 MWh battery systems are introduced, and an improvement of 3.05% is noticed in the reliability indices.

Intelligent Control Frequency Microgrid in Islanded Mode by Central Protection Unit

The appearance of microgrids created challenges such as microgrid protection and due to the presence distributed generation in microgrid network fault currents basically are variable.protection projects based on constant current must be upgraded.one of the major challenges, changes of microgrid frequency in islanded mode.in this paper a new protection system have provided to monitor microgrids and update current errors use extensive communication network. This system has been designed to respond to the dynamic changes in the system like connection/disconnection DG sources and changing microgrid user condition from connected network mode to islanded mode. the protection system Provided takes over control frequency microgrid in islanded mode and prevents microgrid instability. To control frequency central protection unit changes one of the distributed generators to busbar slack. Studies for the provided network sample have been done and show how the proposed protection system can run these models.

Employing Multi-Phase DG Sources as Active Power Filters, Using Fuzzy Logic Controller

By placing distributed generation power sources beside a big nonlinear load, these sources can be used as a power quality enhancer, while injecting some active power to the network. In this paper, a new scheme to use the distributed generation power source in both operation modes is presented. In this scheme, a fuzzy controller is added to adjust the optimal set point of inverter between compensating mode and maximum active power injection mode, which works based on the harmonic content of the nonlinear load. As the high order current harmonics can be easily rejected using passive filters, the DG is used to compensate the low order harmonics of the load current. Multilevel transformerless cascade inverters are preferred in such utilization, as they have more flexibility in current/voltage waveform. The proposed scheme is simulated in MATLAB/SIMULINK to evaluate the circuit performance. Then, a 1kw single phase prototype of the circuit is used for experimental evaluation of the paper. Both simulative and experimental results prove that such a circuit can inject a well-controlled current with desired harmonics and THD, while having a smaller switching frequency and better efficiency, related to previous 3-phase inverter schemes in the literature.