Distributed Generation Plants Research Articles

Features of planning and managing power flows in distribution grids of megalopolises

The study examines the root causes of disruptions of normal operation of power distribution grids in large cities and metropolitan areas. The existing principles of scheduling and maintaining power flows in power distribution grids as well as ways of ensuring the reliability of their operation are analyzed. The integration of fuel-fired distributed generation facilities and renewable generation plants into distribution networks is shown to affect the ability to ensure transient stability during emergency disturbances. We establish evaluation criteria and provide upward margin values to determine the feasibility of the planned power flows. The study reveals general patterns in the calculation of the upward margin for power distribution grids of large cities and metropolitan areas. Test power flow analysis is performed for a real-world segment of a metropolitan area power distribution grid to identify possible overloads of power grid equipment and develop and implement a list of measures for the power flow to achieve the feasible region. The developed approach makes it possible to minimize load shedding or rule out load shedding altogether, ensuring reliable power supply to consumers in large cities and metropolitan areas in the event of an unexpected load growth.

Использование прогностических регуляторов для улучшения качества процессов управления асинхронизированными гидрогенераторами

The introduction of distributed generation (DG) plants into electric power systems (EPS) requires solving problems related to the development of control systems in normal, emergency and post-emergency modes in order to increase their reliability and stability. Asynchronous generators (ASG), which have advantages over synchronous machines can be used in DG plants. However, their application requires the development of modern automatic control systems (ACS). The article discusses a distribution electric network with DG plants based on ASG. At the same time, special attention is paid to the development of ACS ASG models. The aim of the research was to determine the effects of the use of predictive regulators (PR) for ASG management. For this purpose, modeling of the normal, emergency and post-emergency modes of the electric network was performed, which included two ASGs driven by hydraulic turbines. The third and fifth harmonics were generated in the connection node of the power plant. A three-phase short circuit in a 35 kV network with a duration of one second was considered as a disturbance. The results obtained allowed us to draw the following conclusions: the use of PR improves the quality of electricity. The harmonic coefficients of the voltage are reduced by 7.35 %, and the voltage asymmetry coefficients in the reverse sequence are reduced by 50 %. Predictive frequency regulators of ASG with a fixed forecast time calculated according to the proposed methodology improve the control processes. For example, the duration of the transition process for the first ASG is reduced by a third, and the maximum frequency deviation is reduced by 20 %. The degree of its attenuation increases by 33 %.

Research on Data-Driven Fault Scenario Simulation Model of Distributed Network

Distribution lines are critical components of today's power system, and can directly impact on power supply security and stability. An effective power system protection system should detect any faults as soon as they occur. There are two steps in fault diagnosis. One is defect classification, which has already achieved excellent accuracy rates. As a result, this study concentrates on the opposite objective, which is fault location. This research introduces a War Strategy Water Wave Optimization (WSWWO) based Deep Q Network for radial distribution networks using synchronous generators for Distributed Generation (DG). The algorithm estimates the fault site by analyzing voltage and current samples at the main feeder head, and scheduled active and reactive power injections by network synchronous generators. A full-order synchronous machine model was utilized to analyze the dynamic behavior of DG plants during fault transients. Here, the Deep Q Network is trained by WSWWO, and hybridized by two optimization algorithms, War Strategy Optimization (WSO) and Water Wave Optimization (WWO). Furthermore, the experimental results revealed that the WSWWO-Deep Q Network outperformed state-of-the-art models in terms of Accuracy and Error, with values of 0.997 and 0.141, respectively.

Coordinated management of electricity storages and distributed generation plant with predictive controllers in a power supply system with reduced electricity quality

THE PURPOSE. A study of the influence of coordinated control of electricity storage devices and distributed generation installations on the operating modes of a network cluster, which is an electrical distribution network connected to the AC railway power supply system through a direct current insert (DCI).METHODS. The studies were carried out using a simulation model implemented in the MATLAB system.RESULTS. The following disturbing influences were considered: turning off the main power supply of the network cluster from the DCI side for 0.5 seconds; three-phase short circuit with a duration of 0.5 s at the end of a 6 kV cable line with a length of two kilometers. The simulation results showed the effectiveness of coordinated control of electricity storage devices and a turbogenerator with self-adjusting predictive controllers. On this basis, the values of overshoot of the rotor speed are reduced and the transient process time is reduced for all parameters in various modes. For example, the transient time for the generator rotor speed in the mode of connecting an additional load is reduced by three times, and for voltage - by two times.CONCLUSION. Based on computer modeling, it is shown that coordinated control of electricity storage devices and a turbogenerator with predictive regulators reduces the amount of rotor speed overshoot to almost zero and reduces the transient process time by almost 90%. It is advisable to conduct further research on the application of the method of coordinated control of active elements used in the power supply system to regulate the mode parameters.

Combinatorial optimization algorithm with coordínate search method to lócate and size distributed generation plants in a radial distribution electrical system

Combinatorial optimization algorithm with coordínate search method to lócate and size distributed generation plants in a radial distribution electrical system

False Data Injection Impact on High RES Power Systems with Centralized Voltage Regulation Architecture

The increasing penetration of distributed generation (DG) across power distribution networks (DNs) is forcing distribution system operators (DSOs) to improve the voltage regulation capabilities of the system. The increase in power flows due to the installation of renewable plants in unexpected zones of the distribution grid can affect the voltage profile, even causing interruptions at the secondary substations (SSs) with the voltage limit violation. At the same time, widespread cyberattacks across critical infrastructure raise new challenges in security and reliability for DSOs. This paper analyzes the impact of false data injection related to residential and non-residential customers on a centralized voltage regulation system, in which the DG is required to adapt the reactive power exchange with the grid according to the voltage profile. The centralized system estimates the distribution grid state according to the field data and provides the DG plants with a reactive power request to avoid voltage violations. A preliminary false data analysis in the context of the energy sector is carried out to build up a false data generator algorithm. Afterward, a configurable false data generator is developed and exploited. The false data injection is tested in the IEEE 118-bus system with an increasing DG penetration. The false data injection impact analysis highlights the need to increase the security framework of DSOs to avoid facing a relevant number of electricity interruptions.

Energy and stochastic economic assessment for distributed power generation from Manipueira biogas

ABSTRACT Cassava is a staple food in many countries, and this food source differs from other crops in that its processing generates a highly polluting and toxic residue (manipueira) that requires further treatment. The present study analyzed the economic feasibility of anaerobic digestion of manipueira for producing clean electricity through distributed generation (DG) while simultaneously eliminating toxic compounds. This eliminates the toxic residues. For this, an approach for the sizing of DG plants from manipueira biogas was presented, a non-trivial task which is not widespread in the literature. For two plants with different capacities, a deterministic economic analysis was carried out based on the criteria of Net Present Value, Internal Rate of Return, and Discounted Payback. Finally, the project risk was assessed through a sensitivity and stochastic analysis using Monte Carlo Simulation. The empirical verification was done on Brazilian data. When considering the NPV criterion, the results indicate a feasibility probability of 9.25% and 81.21% for scenarios 01 and 02, respectively. The results show that scale gains were important in reducing the impact of the investment and, at the same time, the larger scale of the project makes the cost of capital more relevant to the result. These findings show the need for subsidies for the investment, in addition to the promotion of specific credit lines that enable small-scale generation, or that can improve results in greater capacity.

Digital Twin Formation Method for Distributed Generation Plants of Cyber–Physical Power Supply Systems

The purpose of the study presented in the article was to develop a method for the formation of digital twins for distributed generation plants operating as part of cyber–physical power supply systems. A method of forming a digital twin for a system for automatic regulation of the voltage and rotor speed of a synchronous generator is considered. The structure of a digital twin is presented in the form of a multiply connected model using experimental data. The possibility of using a fuzzy inference system, artificial neural networks, and a genetic algorithm for solving the problem is shown. As a result of the research, neuro-fuzzy models of the elements of the distributed generation plant were obtained, which are an integral part of the digital twin. Based on the simulation results, the following conclusions were drawn: the proposed method for constructing an optimized fuzzy model gives acceptable results when compared with experimental data and shows practical applicability in constructing a digital twin. In the future, in order to simplify the model, it is necessary to solve the problem of optimizing the number of rules in the fuzzy inference system. It is also advisable to direct further research to the formation of a complete hierarchical fuzzy system that connects all elements of the digital twin.

Flicker elimination in grids with distributed generation using group predictive voltage and frequency regulators

In this work, we determine the control efficiency of grids with distributed generation and the possibility of eliminating flicker therein using group predictive voltage and frequency regulators. A small-size thermal power plant with the transformer connection to a power grid and consisting of three turbogenerators with a capacity of 2.5 MV·A each and a voltage of 6 kV was considered as a distributed generation plant. An isolated power supply system with three 2.5 MV·A gas turbine units each operating on static and motor loads was also considered. Automation control methods were used. Studies were conducted in the MatLab environment using the Simulink and SimPowerSystems simulation packages. The obtained results demonstrate that, upon temporarily activating the power load in the point of connecting a distributed generation unit and using inconsistent regulators, fluctuations occurring in the rotor speed and turbogenerator voltage indicate the presence of flicker effects. A similar situation can be caused by a sudden change in the forecast time for individual predictive speed controllers. Following the disconnection of a 0.4 s short circuit, a voltage flicker was found to occur in the vicinity of the gas turbine plant. However, local or group predictive regulators allow the problem of flicker emergence to be solved. The use of group predictive regulators allows flicker to be eliminated more effectively: the transient time is reduced by 1.7 and 2.7 times for the generator rotor speed and voltage, respectively. Moreover, for voltage, over-regulation is practically eliminated. The conducted computer simulation confirmed that flicker can be eliminated by applying group control of turbine generators using predictive speed controllers. Similarly, for a grid with gas turbine units, the use of predictive control algorithms made it possible to eliminate flicker without solving the problem of adjusting regulators. At the same time, group predictive regulators eliminate flicker more effectively, thereby improving the quality indicators of the control process.

Optimal Number and Locations of Smart RMUs for Self-Healing Distribution Networks

Smart grids with self-healing (SH) capability provide an important intelligent feature to help in fast correction actions in case of network faults. SH architecture consists of modern communication systems, smart equipment, and intelligent sensors. With the high cost of SH components (especially smart ring main unit (SRMU)), optimization is required to achieve optimum performance with minimum cost. This study presents a proposed methodology to determine the optimum number and locations of SRMUs in electricity distribution networks considering various cost issues. The disconnection cost of on-grid photovoltaic (PV) plants is taken into consideration as an important factor in determining the locations of the SRMUs. The nonlinear programming (NLP) optimization technique is used to determine the required number of SRMUs, considering the cost/benefit analysis (cost of upgrading MRMUs to SRMUs/benefit due to interruption time reduction), which is the most important factor from DISCOs’ perspective. The mixed integer linear programming (MILP) optimization technique is employed for selecting the optimal locations of the SRMUs considering the cost of losses, energy not supplied (ENS), and PV disconnection, which improves network operation cost. The methodology takes into consideration the cable failure rate and the interest rate. Moreover, the study introduces the Egyptian electrical distribution network and a pilot project for control centre development using SRMUs. The methodology is applied to a modified IEEE 37-node test feeder and a part of a specific district network in South Cairo consisting of 158 nodes; both systems include a number of PV distributed generation plants. Simulation results are presented to show the effectiveness of the proposed method.

A Stochastic Model for Determining Static Stability Margins in Electric Power Systems

This paper aims to develop a method for determining margins of static aperiodic stability for electric power systems equipped with distributed generation plants. To this end, we used generalized equations of limiting modes in a stochastic formulation. Computer simulation showed that the developed methodology can be used in solving problems of operational control of the modes of electric power systems. On the basis of the results obtained, we arrived at the following conclusions: the modified equations do not allow the iterative process to converge to a trivial solution and, therefore, they ensure high reliability of results when determining stability margins in a stochastic statement; a technique based on the introduction of an additional variable can be used to improve the convergence of computational processes when determining the stability margins in a deterministic statement; the parameters of the limiting modes obtained in the deterministic and stochastic formulations may significantly differ; with an increase in the variance of the load graphs, the risk of stability violation significantly increases; at the same time, the amount of the margin determined on the basis of the Euclidean norm remains overly optimistic; in the illustrative example, a significant increase in the risk of stability violation takes place during planned and emergency shutdowns of the EPS elements.

A New Short Term Electrical Load Forecasting by Type-2 Fuzzy Neural Networks

In this study, we present a new approach for load forecasting (LF) using a recurrent fuzzy neural network (RFNN) for Kermanshah City. Imagine if there is a need for electricity in a region in the coming years, we will have to build a power plant or reinforce transmission lines, so this will be resolved if accurate forecasts are made at the right time. Furthermore, suppose that by building distributed generation plants, and predicting future consumption, we can conclude that production will be more than consumption, so we will seek to export energy to other countries and make decisions on this. In this paper, a novel combination of neural networks (NNs) and type-2 fuzzy systems (T2FSs) is used for load forecasting. Adding feedback to the fuzzy neural network can also benefit from past moments. This feedback structure is called a recurrent fuzzy neural network. In this paper, Kermanshah urban electrical load data is used. The simulation results prove the efficiency of this method for forecasting the electrical load. We found that we can accurately predict the electrical load of the city for the next day with 98% accuracy. The accuracy index is the evaluation of mean absolute percentage error (MAPE). The main contributions are: (1) Introducing a new fuzzy neural network. (2) Improving and increasing the accuracy of forecasting using the proposed fuzzy neural network. (3) Taking data from a specific area (Kermanshah City) and forecasting the electrical load for that area. (4) The ability to enter new data without calculations from the beginning.

Using Group Predictive Voltage and Frequency Regulators of Distributed Generation Plants in Cyber-Physical Power Supply Systems

The widespread use of distributed generation (DG) plants in cyber-physical power supply systems (CPPSS) requires solving the complex problem of setting their regulators. The presented study aimed to determine the performance of the group predictive voltage and frequency regulators of DG plants in CPPSS. These studies were conducted in the MatLab environment on the CPPSS models with gas turbine units and with a small-scale hydroelectric power plant. The proposed method for tuning group predictive regulators makes it possible to improve the quality control indices. The research has established that with an additional load connected, the maximum voltage dip is reduced by a factor of 3.5 compared to conventional control regulators. In addition, the time of a transient process for the generator rotor speed is decreased by a factor of 3. In the case of a short-term short circuit, predictive regulators can reduce the time of the transient process by a factor of 1.5 and the overshoot by more than 2 times. The simulation results have confirmed the efficiency of group predictive regulators when used in DG plants, i.e., improvement of the quality of control processes in various operating modes.

The study of the isolated power supply system operation with controlled distributed generation plants, energy storage units and drive load

THE PURPOSE. Investigation of the operating modes of an isolated power supply system with controlled distributed generation plants, energy storage units and a drive load. Determination of the influence of the proposed prognostic controller of a distributed generation plant on the control parameters and quality indicators of the control process under various operating modes of an isolated power supply system.METHODS. The studies were carried out on a computer model of an isolated power supply system of an industrial enterprise with a turbine generator plant, a wind generator plant and a high-power electric storage unit, for which a fuzzy control system and a prognostic controller were used. The simulation was performed in MATLAB using Simulink and SimPowerSystems packages.RESULTS. The article describes a computer model of an isolated power supply system, as well as a structural diagram of the proposed autoprognostic speed controller. The simulation results showed that the combined use of an energy storage unit and an auto-prognostic generator rotor speed controller makes it possible to ensure the stability and survivability of an isolated power supply system, increasing its damping properties. The use of a fuzzy control system of a wind-generating plant made it possible to ensure its stable operation in all considered modes.CONCLUSION. The auto-prognostic speed controller, which does not require special settings, and the energy storage unit provide high quality control indicators in normal and emergency modes. It is advisable to conduct further studies to coordinate the actions of the control system of the electric energy storage unit and the auto-prognostic speed controller of the distributed generation plant.

The Study of Synchronous Generators' Voltage and Frequency Group Prognostic Controllers of a Small-scale HPP

The application of a large number of distributed generation plants, built on the basis of synchronous generators in Electric Energy System (EES), requires solving the problem of their centralized control, adjustment of voltage and frequency local controllers, which entails taking into account a large number of interrelated system parameters. These problems can be solved using prognostic control algorithms. The purpose of the study was to determine the effect of the proposed group prognostic voltage and frequency controllers for small-scale Hydroelectric Power Plant (HPP) on various operating modes of the EES. The studies were conducted in the MATLAB environment using the Simulink and SimPowerSystems simulation packages. The results of computer simulation indicate that the use of group prognostic controllers significantly reduces overshoot, oscillability index, transient time and voltage dips, and frequency in the normal and emergency conditions. The proposed methods of the group prognostic controller formation and tuning allow to improve quality indices of small-scale HPP voltage and frequency control, while retaining the former settings of synchronous generators controllers.

Cyber-physical security of predictive algorithms in group controllers of distributed generation plants

Cyber-physical security of predictive algorithms in group controllers of distributed generation plants

Joint voltage and frequency predictive controllers for distributed generation plants

The paper determines the effect of proposed joint voltage and frequency predictive controllers for distributed generation (DG) plants on quality indicators characterizing the control process in different operating modes of power supply systems. The studies are conducted in the MatLab environment (Simulink and SimPowerSystems simulation packages) employing control engineering methods. It is proposed to design and adjust joint predictive controllers by determining the resonant frequency of oscillations for the master generator rotor. This approach provides better quality indicators of voltage and frequency control in power supply systems while maintaining the same settings for the controllers of DG plants. With an additional load in an isolated power supply system, the maximum voltage sag is found to be 1.75 times lower than for local predictive control and 3.5 times lower as compared to the use of conventional controllers. For the specified mode, predictive controllers enable a threefold reduction in the transient time between rotor rotational speeds in a synchronous generator. In the start mode of a powerful electric motor, the predictive controllers of synchronous generators in the power supply system enable a 1.5 times reduction in voltage sag, with a 1.4 times reduction in overvoltage following its start. In the case of a short-term three phase short-circuit, joint predictive controllers allow a 1.5 times decrease in transient time and a 2.3 times decrease in the overshoot of power line frequency as compared to local control. In addition, frequency oscillation in the power system is also reduced. Similar effects are observed in other operating modes of the considered power supply systems equipped with DG plants. The performed dynamic simulation confirms the effectiveness of using joint voltage and frequency predictive controllers for DG plants, which consists in a positive impact on the quality of processes involved in controlling the parameters of power supply systems in various operating modes.

Flicker in the Networks with Distributed Generation Plants and Its Removal Using Group Prognostic Controller

The use of distributed generation (DG) plants in electrical energy system (EES) produces unambiguous effect on power quality. The presence of DG plants allows to reduce losses associated with power transmission and maintain the required voltage levels. In this case, the presence of DG can cause voltage fluctuation, leading to the appearance of flicker, which is understood as a feeling of instability of visual perception. Similar processes can occur at sharp disturbances close proximity to the DG. The situation can be aggravated by improperly configured DG generators controllers. Therefore, it is necessary to conduct an accurate assessment of the DG plants impact on the power grid, which is a rather time consuming task. The article presents results of the EES working modes simulation with a DG plant implemented on the basis of synchronous turbine generators. The results obtained indicated that during temporary connection of heavy load in the connection unit of DG plant and the use of non-concordantly tuned controllers, there are fluctuations in rotor speed and voltage of generators, the analysis of which indicates the presence of flicker. The same effect can obtained a sudden change in the forecast time for individual controllers of turbine generators speed. Flicker can be removed by applying group control of generators speed controllers.

Исследование кибербезопасности прогностических алгоритмов управления для установок распределенной генерации

The power industry is currently actively developing the field related to the use of distributed generation plants located near the power receiving devices of consumers. At the same time, the introduction of distributed generation plants causes a lot of engineering problems which need solutions. One of them is the optimization of the settings of automatic voltage regulators (AVR) and speed regulators (ASR) of synchronous generators in all possible operating modes. This requires the use of complex models of power supply systems, distributed generation plants and their regulators, as well as labor-intensive calculations that take into account a large number of interrelated parameters. However, there is another approach based on the use of predictive controllers. In this case only one parameter is needed for linear predictive models.The article describes a method for constructing and tuning the proposed predictive ASR synchronous generator, as well as computer models of distributed generation plants used in research. The purpose of the research was to determine cyber security of power supply systems equipped with various distributed generation plants with predictive speed controllers that can be implemented on the basis of the microprocessor technology. The studies were carried out in the MATLAB system using the Simulink and SymPowerSystems simulation packages on computer models of distributed generation plants with one turbine generator operating at a dedicated load, as well as a group of hydrogenerators connected to a high-power electric power system. The simulation results showed the effectiveness of the proposed predictive control algorithms, as well as the fact that their cyber security can be increased by introducing hardware restrictions on the range of changes in the time constant of the predictive link.

Research of Operation of Predictive Controllers of Distributed Generation Plant in Power Supply System with Energy Storage

The article discusses the power supply system of an industrial enterprise, which included a turbine generator plant operating on the basis of a synchronous generator equipped with predictive voltage and rotor speed controllers, as well as a high-power electric energy storage device. A description of the models of this plant, predictive controllers and energy storage, as well as the results of modeling when the system goes into an isolated mode of operation are given. Simulation was performed in MATLAB environment using Simulink and SimPowerSystems packages. The purpose of the work was to study the behavior of the proposed predictive controllers during the transition of the power supply system to the island (isolated) mode. Based on the results of computer simulation, it was concluded that the use of predictive controllers improves the damping properties of the system. The use of an energy storage device that is automatically connected to the network when the voltage drops, allows to reduce the overvoltage at the terminals of the generator during its unloading, as well as to reduce the required mechanical power on the turbine shaft in comparison with a permanently connected device. Predictive controllers can be recommended to increase the stability of distributed generation plants when switching to an isolated mode. It is advisable to conduct further research in the direction of creating algorithms for coordinated operation of controllers