Modeling of Electrical Power System with Distributed Generation Source

This paper presents an approach for the optimal integration of multiple distributed generation (DG) sources in a radial distribution system. The integration of DG sources poses various challenges such as can lead to higher power losses caused by reverse power flow, voltage exceeding secure limits, voltage stability, power quality, and economic operation. To address these challenges, a hybrid algorithm is proposed which combines the benefits of both Evolutionary Programming and Firefly Algorithm. The proposed hybrid Evolutionary - Firefly Algorithm is employed for the determination of the optimal size of the DG sources. The objective of the proposed algorithm is to minimize the total system power losses and improve the voltage profile. The algorithm considers various constraints including the DG capacity limits and voltage limits. A comprehensive case study is conducted on a radial distribution system to demonstrate the effectiveness of the proposed approach. The simulation results show that the hybrid algorithm can find the optimal size and location of DG sources while achieving the desired system performance. The integration of multiple DG sources leads to a significant reduction in power losses and improved voltage profile. Furthermore, the proposed approach provides a flexible framework for the optimal integration of DG sources in radial distribution systems, allowing for the accommodation of different types and capacities of DG sources. The proposed technique is tested on the IEEE Reliability Test systems, specifically the IEEE 69-bus. The combination of DG at bus 61 and bus 27 yields a loss reduction index of 94%.

In this paper, a long short-term memory (LSTM)-based method with a multi-input tensor approach is used for the classification of events that affect the power quality (PQ) in power systems with distributed generation sources. The considered events are line faults (one line, two lines, and three lines faulted), islanding events, sudden load variations, and generation tripping. The proposed LSTM-based method was trained and tested using the signals produced by the events simulated in a study system with distributed generation sources via PSCAD®. Then, noise with different levels was added to the testing set for a thorough assessment, and the results were compared with other well-known methods such as convolutional and simple recurrent neuronal networks. The LSTM-based method with multi-input proved to be effective for event classification, achieving remarkable classification performance even in noisy conditions.

This paper proposes a comprehensive simulation model for the Electrical Power System (EPS) of More Electrical Aircrafts (MEA). Taking the presently typical MEA model of Boeing 787 as an example, the integrated structure of EPS is firstly illustrated and the operating principles are theorized. The key components of the MEA EPS including generators, rectifiers, loads, breakers, control devices, cables and other supplementary elements are then simulated to build a comprehensive EPS model on the platform of MATLAB/Simulink. Although the model's scale is large, its simulation time is guaranteed thanks to using the built-in blocks provided by Simulink. Finally, the stability analysis in terms of normal operation and different faults are carried out in case studies and power source switching strategies in different situations are summarized. The results showed that the comprehensive model proposed by the paper can be used to simulate MEA EPS and analyze its operational stability effectively and efficiently.

The modern electric power system is foreseen to have increased penetration of controllable loads under demand response programs and renewable energy resources coupled with energy storage systems which can provide virtual inertia. In this paper, the conventional model of an electric power system is appended by considering, individually and collaboratively, the role of demand response and virtual inertia for the purpose of frequency analysis and control. Most existing literature on this topic either considers one of these two roles or lacks in providing a general model of power system with demand response and virtual inertia. The proposed model is presented in general form and can include/exclude demand response and/or virtual inertia. Further, power system operator can opt the power shares from conventional, demand response, and virtual inertia loops for frequency regulation and can also evaluate the impact of other parameters such as time delays and frequency deadbands on system frequency response. The mathematical formulation of steady-state values of frequency deviation and power contribution from all resources is provided and validated by simulation results under various scenarios including a case of wind intermittency.

This paper describes the optimization of a power system with distributed generation (DG) sources. The optimization aims to minimize the electricity production costs ensuring that the load is served reliably and is conducted using the fmincon function in Matlab. The optimization is performed considering the power demand and the availability of the system's generating units, and equality restrictions. The optimization is performed first for steady-state condition, and second for the entire day. The optimization for the entire day is performed for two cases: when the DG sources are connected to the system and when the DG sources are not connected to the system. The test system comprises four generators and one load.

Software time-domain simulation models are useful to the naval engineering community both for the system design of future vessels and for the in-service support of existing vessels. For future platforms, the existence of a model of the vessel's electrical power system provides a means of assessing the performance of the system against defined requirements. This could be at the stage of requirements definition, bid assessment or any subsequent stage in the design process. For in-service support of existing platforms, the existence of a model of the vessel's electrical power system provides a means of assessing the possible cause and effect of operational defects reported by ship's staff, or of assessing the possible future implications of some change in the equipment line-up or operating conditions for the vessel. Detailed high fidelity time-domain simulation of systems, however, can be problematic due to extended execution time. This arises from the model's mathematically stiff nature: models of Integrated Electric Propulsion systems can also require significant computational resource. A conventional time-domain software simulation model is only able to utilize a single computer processor at any one time. The duration of time required to obtain results from a software model could be significantly reduced if more computer processors were utilized simultaneously. This paper details the development of a distributed simulation environment. This environment provides a mechanism for partitioning a time-domain software simulation model and running it on a cluster of computer processors. The number of processors utilized in the cluster ranges between four and sixteen nodes. The benefit of this approach is that reductions in simulation duration are achievable by an appropriate choice of model partitioning. From an engineering perspective, any net timing reduction translates to an increase in the availability of data, from which more efficient analysis and design follows.

Analysis of a bilinear model of an electric power system using spectral decompositions of Lyapunov functions

Integrated transmission-and-distribution (T&D) modeling is a new and developing method for simulating power systems. Interest in integrated T&D modeling is driven by the changes taking place in power systems worldwide that are resulting in more decentralized power systems with increasingly high levels of distributed energy resources. Additionally, the increasing role of the hitherto passive energy consumer in the management and operation of power systems requires more capable and detailed integrated T&D modeling to understand the interactions between T&D systems. Although integrated T&D modeling has not yet found widespread commercial application, its potential for changing the decades-old power system modeling approaches has led to several research efforts in the last few years that tried to (i) develop algorithms and software for steady-state and dynamic modeling of power systems and (ii) demonstrate the advantages of this modeling approach compared with traditional, separated T&D system modeling. In this paper, we provide a review of integrated T&D modeling research efforts and the methods employed for steady-state and dynamic modeling of power systems. We also discuss our current research in integrated T&D modeling and the potential directions for future research. This paper should be useful for power systems researchers and industry members because it will provide them with a critical summary of current research efforts and the potential topics where research efforts are needed to further advance and demonstrate the utility of integrated T&D modeling.

Review for "Artificial neural network and synchrosqueezing wavelet transform based control of power quality events in distributed system integrated with distributed generation sources"

The article presents a comparative review and analysis of modern methods of functioning of relay protection systems of medium-voltage distribution networks with distributed generation sources (DGR). The analysis touched upon the main technical challenges associated with the active introduction of DGR, primarily renewable sources, into regional networks, which leads to a change in the directions of flows and currents in the network, violation of the conditions for ensuring selectivity, sensitivity and technically perfect coordination between protective devices. Special attention is paid to the features of relay protection of micro-power systems during the transition from network to island mode.The purpose of the study is to review and analyze modern methods and systems of relay protection of distribution regional networks with DRG, taking into account the features of their operation.The article studies traditional and innovative (adaptive, combined, based on sequential components, using phasor measuring devices and artificial intelligence) protection methods, their efficiency and ability to operate in characteristic modes. The comparative analysis was carried out taking into account known modern platforms, their advantages, complexity of implementation, requirements for communication channels, settings and tests, possible risks due to the complexity of relay protection systems. The key advantages and limitations of modern approaches to implementing relay protection, as well as current trends in the development of protection systems for active networks with a high share of DRG, are identified.It is shown that to ensure the reliability and safety of power supply in modern conditions, it is necessary to implement adaptive, intelligent and hybrid protection systems with the possibility of operating regional microgrids in island mode.As a rule, in distribution regional networks, protection systems based on current measurement are used, less often - based on voltage measurement or combined protection systems (based on current and voltage measurement). However, the change in the structure of power supply from centralized (with one-way current flow) to decentralized (with different DRGs) creates a serious threat to network protection systems in terms of reliability of operation, sensitivity and coordination of various protection elements.It is established that innovative methods demonstrate higher flexibility, accuracy and ability to self-organize. At the same time, they require more complex technical and software implementation, communication setup and relevant implementation experience. The reliability of protection in the future will be determined by the system's ability to adapt to rapid changes in operating mode, dynamic connection and change of DRG parameters, requirements for power supply of critical consumers even in the event of a transition to islanding modes when disconnected from the main grid.

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The article is devoted to solving the issues of managing power flows to implement the Energy Internet concept. A new approach to the regulation of power flows in an electrical network with distributed generation sources is proposed. A feature of the approach is the possibility to change the amplitude and phase shift of the voltage vector regardless of the current mode of the electrical network. Vector control is implemented with the help of a new device - the mode vector regulator (MVR). The principle of operation and design of the MVR are described. The range of active power regulation in the line with MVR is determined based on LabVIEW model. It depends on the given phase angle of the current of the line choke and the phase shift between the voltages of the nodes. Mode parameters calculation for a network with the MVR is based on the nodal analysis adjusted for the features of the representation of the MVR in the equivalent circuit. An example of using the MVR in an electrical network with distributed generation sources is shown.

This paper presents the results of an investigation regarding the electrical performance characteristics of a new, three-phase, 480 V (L-L), 30 kW, micro-turbine generator and its suitability as an electrical power source for applications at the electrical power distribution voltage level. This unit is fueled by natural gas and may be used as a dispersed generation source. The unit was purchased by the local utility company and given to the University of Nevada, Reno, USA, for the investigation. The Electrical Machine and the Power System Laboratory was used to perform the study. Testing was performed at several load set-point levels. The investigation includes the turbine behavior under a weak system that consists of the micro-turbine, a variable three-phase load, and a three-phase 15 kVA synchronous machine in the laboratory. The speed of this machine is controlled by a fuzzy logic algorithm. Conclusions are made regarding the suitability of the unit as a distributed generation source.

The article presents an adaptive genetic algorithm developed by the authors, which makes it possible to optimize the topology of a power network with distributed generation. The optimization was based on bioinspired methods. The objects of the study were a 15-node circuit of a power net-work with photovoltaic stations and a 14-node IEEE augmented circuit with distributed generation sources (three wind farms and two photovoltaic plants). The simulation of the modes of electric power systems was performed using the Pandapower library for the Python programming language, which is in the public domain. Three types of electric load of consumers were considered, reflecting the natures of electricity consumption in the nodes of real electric power systems, the results of numerical studies were presented. The proposed genetic algorithm used two different functions of interbreeding, the function of mutation, selection of the best individuals and mass mutation (complete population renewal). At the end of each iteration of the algorithm operation, statistical dependencies were de-rived that characterized its work: the best (minimal losses) and average adaptability in the population, a list of the best individuals throughout all iterations, etc. The verification was carried out in comparison with the results obtained by a complete search of possible radial configurations of the system, and it showed that the developed genetic algorithm had fast convergence, high accuracy and was able to work correctly with different configurations of electrical circuits, generation and load structures. The algorithm can be used in conjunction with renewable energy sources generation forecasting systems for the day ahead when planning the operating modes of power units in order to minimize the costs of covering electricity losses and improve the quality of electricity supplied.

Integrating non-dispatchable renewable energy sources (RES) such as wave farms into electric power systems presents inherent challenges. Specifically, the variability of the resource and its non-dispatchable) nature introduces power imbalances and power system stability problems in the system over both short and medium terms. This issue is particularly relevant for isolated power systems, such as those found on several European islands, where interconnection with the mainland is lacking. Therefore, although wave energy has significant potential for integration into island power systems due to resource availability, determining the maximum RES penetration that such systems can sustain while maintaining stability is not straightforward. Power system stability is closely tied to frequency. A well-established solution for improving the stability of isolated systems when integrating non-dispatchable RES is to install devices capable of responding to over- or under-frequency events, such as energy storage systems (ESS). The literature extensively discusses ESS control techniques for frequency regulation, with one of the most straightforward approaches being to operate the ESS according to a droop control strategy (similar to a statism). In this method, the power dispatched or stored by the ESS increases proportionally to the deviation from the frequency reference value. This paper presents a case study analyzing the frequency stability of an island power system equipped with an energy storage system (ESS) when integrating a wave farm. Frequency stability is evaluated based on two variables: wave energy penetration and the ESS droop control parameter. The case study is based on the island of El Hierro (Canary Islands, Spain), an isolated electrical system with a very high penetration of RES. The island’s electrical generation system consists of a wind farm, a pumped-storage hydroelectric power plant, and conventional generation from a diesel power plant. The analysis is conducted through simulations in MATLAB Simulink. A wave farm is modeled to evaluate the generated power and its associated oscillations, based on the wave energy resource at various locations along El Hierro’s coast. Additionally, an aggregated inertial dynamic model of the electrical power system is employed to assess the impact of the wave energy farm's generation on the system’s frequency and the aging that the frequency excursions introduce in the elements of the system. The Spanish Grid Code is considered to ensure compliance with frequency regulation mechanisms in isolated systems. Simulations are performed across different scenarios, varying both the nominal power of the wave farm and the ESS droop control parameter, in order to evaluate the ESS capacity. The results identify the optimal droop control parameter for each wave farm size to ensure frequency remains within acceptable thresholds. Furthermore, the minimum ESS capacity required for each wave farm size is determined from the simulations. These findings provide a basis for ESS and wave farm dimensioning, which could be translated into economic terms to maximize revenue (this aspect is beyond the scope of the present work).