Mathematical Modeling and Control Algorithm Development for Bidirectional Power Flow in CCS-CNT System

Electricity is indispensable worldwide, but conventional distribution networks struggle in sparsely populated areas. Capacitor Coupled Substations (CCS) and Controllable Network Transformers (CNT) are promising solutions for supplying electricity to such regions. CCS efficiently delivers power to remote areas, while CNT enables bidirectional power flow, crucial for integrating micro-grids and managing energy fluctuations. Combining CCS and CNT facilitates both power tapping and injection into the transmission network. A study using MATLAB/Simulink models the impact of CCS-CNT integration on transmission networks. Results indicate negligible voltage level disturbance, suggesting its seamless integration. Moreover, incorporating CNT within CCS systems might obviate the need for external ferroresonance suppression circuits (FSC). Thus, CCS-CNT systems offer dual functionality, effectively supplying and injecting electricity into the grid while potentially serving as FSCs. The research purpose is to assess the results that can be achieved when utilizing a CCS-CNT system for supplying electricity to a dedicated load. The results showed that a typical CCS-CNT results in normally acceptable output voltage when the system is connected to a transmission network. Furthermore, it also shows that there is no impact on the transmission network it is connected to. This research underscores the importance of innovative solutions like CCS-CNT in extending reliable electricity access to underserved areas and enhancing grid resilience. Further analysis is warranted to explore additional benefits and optimize system performance.

Increases in load, increases in penetration of renewable energy, and limited investment in transmission infrastructure are fostering the need for a smarter, more dynamically controllable grid. Flexible ac transmission systems (FACTs) devices such as the UPFC and BTB are difficult to implement at transmission-level voltages due to complexity and cost. A direct-ac/ac-converter-based controllable network transformer (CNT), because of its fractional converter rating and lack of dc storage requirement, is a simpler and less expensive alternative for applications involving dynamic power flow control. Scaling of the CNT, however, is still a challenge. This paper proposes an approach for scaling the CNT to utility-level voltages and currents utilizing multilevel topologies as well as direct-ac/ac power electronic building blocks (AC-PEBBs). A comparison of various PEBB-based CNT topologies is presented via simulation and experimental results for a 13 kV, 1 MVA application.

Synthetically analyze the power distribution communication network technology in the smart power grid link. It mainly includes the summary of the smart distribution network, electric power communication backbone network and then layer communication requirements, the network mode and the application mode of WLAN technology in the distribution network, EPON network technology, micropower wireless technology, PTN technology and power broadband wireless systems. State the demand of the smart power distribution business and put forward technical guidance for the smart power distribution communication network scheme. In view of the complex distribution network architecture, more nodes and scattered, complex business types data business needs, put forward the integrated solutions of optical fiber communication as the backbone access, wireless bandwidth, passive optical communication as the coverage, the short distance wireless communication as the main terminal access. It provides a reference for the communication plan of distribution side.

Multi-faceted sustainability improvement in low voltage power distribution network employing DG and capacitor bank

A new method of power flow control in a meshed network has been presented earlier, to enable power dispatch along a defined path without impacting flows on branches adjacent to the path. This paper explores the type of power converter topology that could optimally provide the desired control function. This includes well known FACTS devices such as back-to-back converters (BTB) and unified power flow controllers (UPFC), as well as newer devices such as controllable network transformers (CNT), and distributed series impedance (DSI) devices. Equipment ratings are calculated for the BTB, UPFC, CNT and CNT-DSI hybrid solutions. Scalability to grid voltages and power levels is also discussed. Power flow capability, implementing the proposed solution with ideal voltage sources, is shown via simulation for the IEEE 39 bus system. Finally, functionality is simulated in a meshed, four-bus system using switching devices. Proposed functionality would allow more efficient market operation, incentivize transmission investment and ensure physical delivery of contracted energy, thus enabling real-time markets for low carbon (green) sources.

Active Distribution Networks (ADNs) are modern and intelligent power distribution systems that integrate renewable energy sources and advanced control technologies to provide reliable, secure, and efficient electricity supply. The traditional power distribution networks are designed to deliver electricity in a one-way flow from the transmission system to the customers. In contrast, ADN enables two-way power flow between the distribution network and customers, allowing them to become active participants in the electricity system. The key technology behind ADN includes advanced metering infrastructure (AMI), Distribution Automation (DA), and energy storage systems (ESS). AMI provides real-time data on electricity consumption, generation, and distribution, enabling efficient load management and demand response. Other key technologies of ADN include renewable energy sources such as solar photovoltaic (PV), Wind turbines and small-scale hydroelectricity. These sources are connected to the distribution network through power electronic interfaces that convert the DC output of the renewable sources into AC for distribution. Smart grid technologies such as microgrids, virtual power plants, and energy management systems are also integrated into ADN to improve grid stability and resilience. ADNs have the potential to transform the electricity system by enabling more efficient, sustainable, and reliable energy systems that can better serve the needs of consumers and society. Thus, ADN is expected to become a critical technology in achieving a cleaner and more sustainable energy future.

The stability of a hybrid AC-DC microgrid depends mainly upon the bidirectional interlinking converter (BIC), which is responsible for power transfer, power balance, voltage solidity, frequency and transients sanity. The varying generation from renewable resources, fluctuating loads, and bidirectional power flow from the utility grid, charging station, super-capacitor, and batteries produce various stability issues on hybrid microgrids, like net active-reactive power flow on the AC-bus, frequency oscillations, total harmonic distortion (THD), and voltage variations. Therefore, the control of BIC between AC and DC buses in grid-connected hybrid microgrid power systems is of great importance for the quality/smooth operation of power flow, power sharing and stability of the whole power system. In literature, various control schemes are suggested, like conventional droop control, communication-based control, model predictive control, etc., each addressing different stability issues of hybrid AC-DC microgrids. However, model dependence, single-point-failure (SPF), communication vulnerability, complex computations, and complicated multilayer structures motivated the authors to develop online adaptive neural network (NN) Q-learning-based full recurrent adaptive neurofuzzy nonlinear control paradigms for BIC in a grid-connected hybrid AC-DC microgrid. The proposed strategies successfully ensure the following: (i) frequency stabilization, (ii) THD reduction, (iii) voltage normalization and (iv) negligible net active-reactive power flow on the AC-bus. Three novel adaptive NN Q-learning-based full recurrent adaptive neurofuzzy nonlinear control paradigms are proposed for PQ-control of BIC in a grid-connected hybrid AC-DC microgrid. The control schemes are based on NN Q-learning and full recurrent adaptive neurofuzzy identifiers. Hybrid adaptive full recurrent Legendre wavelet-based Neural Network Q-learning-based full recurrent adaptive NeuroFuzzy control, Hybrid adaptive full recurrent Mexican hat wavelet-based Neural Network Q-learning-based full recurrent adaptive NeuroFuzzy control, and Hybrid adaptive full recurrent Morlet wavelet-based Neural Network Q-learning-based full recurrent adaptive NeuroFuzzy control are modeled and tested for the control of BIC. The controllers differ from each other, based on variants used in the antecedent part (Gaussian membership function and B-Spline membership function), and consequent part (Legendre wavelet, Mexican hat wavelet, and Morlet wavelet) of the full recurrent adaptive neurofuzzy identifiers. The performance of the proposed control schemes was validated for various quality and stability parameters, using a simulation testbench in MATLAB/Simulink. The simulation results were bench-marked against an aPID controller, and each proposed control scheme, for a simulation time of a complete solar day.

Various new energy, energy storage, and adjustable loads are incorporated into the distribution network to participate in the adjustment of the distribution network side, making the operation of the distribution network side more flexible. As an important part of the distribution network, the power lines of the distribution network are directly affected by this change. Therefore, the online detection of distribution network parameters in the distribution network becomes more and more important. Currently, smart devices can perfor15wm parameter estimation and topology recognition in a data-driven manner. However, many current methods require the use of phasor measurement units to measure the phase angle of the node voltage, which is not feasible for current relatively traditional power distribution networks. Based on the more accurate power detection of the current distribution network, this paper proposes a method for estimation of the line parameters of the distribution network without considering the voltage phase angle information. Based on the limited measurement data of the distribution network, the measured electricity is all amplitude. By modeling the transmission line of the distribution network, the problem of solving the transmission line parameters is transformed into a binary nonlinear regression problem. The binary nonlinear least-squares regression method is used to identify the transmission line parameters, and the residual analysis is used to eliminate anomalies data. After that, the reliability and accuracy of the method are analyzed for the identification results under different data volumes and different error levels. Finally, the line parameters within a day were identified under the condition of line temperature changes. By comparing the results of electrothermal coupling, the changes of line parameters in a day can be more accurately identified.

Dynamic control over real and reactive power flow is one of the key areas of concern for the modern grid. Traditional FACTS based devices have proven to be too costly and complex to achieve any significant market penetration. Modifying existing transmission assets to make them controllable may be a cost-effective method of increasing the grid controllability. Controllable Network Transformers (CNTs) have been shown theoretically to be an effective real and reactive power flow controller. The various options for filter design of a CNT are presented in this paper. The paper also discusses the design and testing of a medium voltage CNT prototype with an integrated hybrid active filter, rated at 200 kVA and 2.4 kV.

Study of power flow mechanism of capacitive power transfer system based on Poynting vector analysis

Multi terminal DC transmission system based on modular multilevel converter (MMC) is a promising and emerging development in HVDC applications. Here several converter stations, based on MMC topology is connected to the HVDC grid. Each of these stations can operate either in rectifier mode or in inverter mode allowing easy flexibility of bidirectional power flow. In this paper, a MMC based MTDC system is developed and its operation is analysed in details. A mathematical model of MTDC with two rectifier station and one inverter station has been developed. Control system for the MTDC system is proposed and explained. Several simulation results at steady state during load change and power flow reversal is illustrated. The proposed system shows easy integration of several converter stations in the MTDC grid and bidirectional power flow among the converters.

A new model of power system to identify critical elements for smart and bulk power transmission grid environment is presented in this paper. Proposed bidirectional power flow model under complex network framework can quantify the criticality of nodes whose removal would trigger cascading failure. The proposed model based centrality, which is an extension of nominal power flow based model, is able to find nodes whose removal exerts more stress on the system. Several measures of impact like path length increase, boosted connectivity loss, raised load loss and increase in number of overloaded lines justify the use of bidirectional power flow based model to evaluate the criticality in smart grid environment. Change in direction of power flow in various random lines of the test system has a very little effect on the rank of nodes in the critical list.

Flexible alternating current transmission systems are used since nearly four decades and present very good dynamic performances. The purpose of this work is to study the behaviour of a system where static compensator (STATCOM) is located at the midpoint of a long transmission line functioning in disturbed modes with various levels of load caused by tripping and then, reclosing of the incoming station breaker. The studied model and starting from the analysis of various alternatives will lead to the checking of the aptitude of the STATCOM to maintain the voltage plan and to improve the power flow in electroenergetic system which is the east region of Algerian 400 kV transmission network. The steady state performance of STATCOM’s controller is analysed through computer simulations with MATLAB/Simulink program. The simulation results have demonstrated that STATCOM can be effectively applied in power transmission systems to solve the problems of poor dynamic performance and voltage regulation. Keywords: STATCOM, reactive power, power flow, voltage plan, breaker automatic recloser

The focus of this study is the effectiveness of the controller’s Unified Power Flow Controller UPFC with the choice of a control strategy. This Unified Power Flow Controller (UPFC) is used to control the power flow in the transmission systems by controlling the impedance, voltage magnitude and phase angle. This controller offers advantages in terms of static and dynamic operation of the power system. It also brings in new challenges in power electronics and power system design. To evaluate the performance and robustness of the system, we proposed a hybrid control combining the concept of identification neural networks with conventional regulators and with the changes in characteristics of the transmission line in order to improve the stability of the electrical power network. With its unique capability to control simultaneously real and reactive power flows on a transmission line as well as to regulate voltage at the bus where it is connected, this device creates a tremendous quality impact on power system stability. The result which has been obtained from using MATLAB and SIMULINK software showed a good agreement with the simulation result.

As ac-to-ac power conversion becomes increasingly importantly in applications such as grid power flow control and motor control, the demand for a plug-and-play converter is increased. Traditional VSI-based ac-to-ac power converters such as the back-to-back converter require bulky dc-link capacitors that limit their reliability. Therefore, approaches that offer direct ac-to-ac power conversion are gaining popularity. This paper proposes a plug-and-play concept for achieving ac-to-ac power conversion via the ac/ac power electronic building block (AC-PEBB). The AC-PEBB is a compact, self-contained cell requiring no energy storage. It can be used in a variety of direct ac/ac converters including matrix converters, controllable network transformers (CNT), etc. This paper details the construction of a prototype AC-PEBB to be used in a 13 kV, 1 MVA application. The effectiveness of the AC-PEBB is demonstrated experimentally in an example application of controlling grid power flows via a 10 kVA CNT prototype built by augmenting a standard transformer with a single AC-PEBB cell. Series and parallel connection of multiple AC-PEBBs to increase maximum voltage and current handling capability is also demonstrated.