Improving Accuracy and Computational Efficiency of the Load Flow Computation of an Active/Passive Distribution Network

Over the last couple of decades, there has been a growing trend to make a paradigm shift from the passive distribution network to the active distribution network. With the rapid enlargement of network and installation of distributed generation (DG) units into distribution network, new technical challenges have arisen for load flow computation. The available techniques for the active distribution load flow calculation have limited scope of application and, sometimes, suffer from computational complexity. The complexity level of the distribution system power flow calculation is higher because of the issues of phase imbalance and high R/X ratios of feeder lines. The phase-imbalance increases computational complexity, whereas, the high R/X ratio makes time-consuming derivative based solver such as Newton-Raphson inviable for such large system. The motivation behind this work is to propose distinct mathematical approach for accurate modeling of network components, and loads to reduce computational time with improve accuracy. The applicability of an existing technique remains limited either by DG control modes, or by transformer configurations. The objective of this work is basically to develop an active distribution load flow (ADLF) algorithm with the following features. • Improved computational efficiency. • Applicability to any feeder network. • Accurate modeling of loads. • Applicability to different mode of operations of distributed generators (DGs). Typically, distributed generators are power-electronically interfaced sources that can be operated either in the current-balanced or in the voltage-balanced mode. The integration of DGs to the feeder network enables the distribution system to have bidirectional power exchange with the transmission grid. Which, also improve the voltage profile of the distribution network by providing additional sources of reactive power compensation. The contribution of the first work is to carry out the load flow analysis of a distribution network in the case of the dominant presence of induction motor loads. For a given operating condition, the load representation of an induction motor on the distribution network is made by analyzing its exact equivalent circuit. Thus, the induction motor is precisely represented as a voltage and frequency dependent load. The necessity of representing an induction motor by means of its precise load model is verified through a detailed case study. The convergence of the load flow solution with the precise modeling of induction motor loads is ensured by carrying out the load flow analysis over a complex distribution network containing several loops and distributed generations. The specific contribution of the second work is to improve the accuracy of the results obtained from the load flow analysis of a distribution network via forwardbackward sweeps. Specific attention is paid to the two-port modeling of a transformer with precise consideration for the zero sequence components of its port voltages. The zero sequence voltages at transformer ports are often ignored in the conventional load flow analyses. A new two-port network model is derived, which is generalized enough for the accurate representation of a transformer in the cascaded connection. Based upon the novel two-port representation made, a new set of iteration rules is established to carry out the forward-backward sweeps for solving the load flow results. All possible transformer configurations are taken into account. It is shown that the load flow analysis technique proposed is suitable for both active and passive distribution networks. The accuracy analysis of the load flow results is also carried out. For a given load flow result, by assessing the nodal current imbalances are evaluated based upon the admittance matrix representation of the network. Extensive case studies are performed to demonstrate the utility of the proposed load flow analysis technique. The contribution of the third work is to develop a computationally efficient and generalised algorithm for the load flow calculation in an active distribution network. The available techniques for the active distribution load flow calculation have limited scope of application and, sometimes, suffer from computational complexity. The applicability of an existing technique remains limited either by DG control modes or by transformer configurations. In this chapter, the load flow calculation is carried out by using the concept of Gauss-Zbus iterations, wherein the DG buses are modeled via the technique of power/current compensation. The specific distinctness of the proposed Gauss-Zbus formulation lies in overcoming the limitations imposed by DG control modes for the chosen DG bus modeling as well as in having optimized computational performance. The entire load flow calculation is carried out in the symmetrical component domain by decoupling all the sequence networks. Furthermore, a generalised network modeling is carried out to define decoupled and tap-invariant sequence networks along with maintaining the integrity of the zero sequence network under any transformer configurations.The computational efficiency and accuracy of the methodology proposed are verified through extensive case studies. The contribution of the fourth work is to identify and eliminate unnecessary itvii eration loops in the load flow analysis of an active distribution network so as to improve its overall computational efficiency. The number of iteration loops is minimized through the integrated modeling of a distributed generator (DG) and the associated coupling transformer. The DG bus is not preserved in the load flow calculation and the aforementioned DG-transformer assembly is represented in the form of a voltage dependent negative load at the point of connection to the main distribution network. Thus, the iteration stage that is involved in indirectly preserving the DG in the form of a voltage source or negative constant power load can be got rid of. This, in turn, eliminates the need for multiple rounds of forward-backward sweep iterations to determine the bus voltages. The power characteristics of the DG-transformer assembly are thoroughly investigated through a carefully performed case study so as to assess the potential convergence performance of the proposed

Transmission and Distribution Co-Simulation and Applications

As the penetration of flexible loads and distributed energy resources (DERs) increases in distribution networks, demand dispatch schemes need to consider the effects of large-scale load control on distribution grid reliability. Thus, we need demand dispatch schemes that actively ensure that distribution grid operational constraints are network-admissible and still deliver valuable market services. In this context, this work develops and evaluates the performance of a new network-admissible version of the device-driven demand dispatch scheme called Packetized Energy Management (PEM). Specifically, this work develops and investigates the live grid constraint-based coordinator and metrics for performance evaluation. The effects of grid measurements for a practical-sized, 2,522-bus, unbalanced distribution test feeder with a 3000 flexible kW-scale loads operating under the network-admissible PEM scheme is discussed. The results demonstrate the value of live grid measurements in managing distribution grid operational constraints while PEM can effectively deliver frequency regulation services. Increased penetration of flexible loads and DERs on distribution system (DS) will lead to increased interaction of transmission and distribution (T&D) system operators to ensure reliable operation of the interconnected power grids, as well as the control actions at LV/MV grid in aggregation will have significant impact on the transmission systems (TS). Thus, a need arises to study the coupling of the transmission and distribution (T&D) systems. Therefore, this work develops a co-simulation platform based on decoupled approach to study integrated T&D systems collectively. Additionally, the results of a decoupled method applied for solving T&D power flow co-simulation is benchmarked against the collaborator developed unified solution which proves the accuracy of the decoupled approach. The existing approaches in the literature to study steady-state interaction of TS-DS have several shortcomings including that the existing methods exhibit scalability, solve-time and computational memory usage concerns. In this regard, this work develops comprehensive mathematical models of T&D systems for integrated power flow analysis and brings advancements from the algorithmic perspective to efficiently solve large-scale T&D circuits. Further, the models are implemented in low-cost CPU-GPU hybrid computing platform to further speed up the computational performance. The efficacy of the proposed models, solution algorithms, and their hardware implementation are demonstrated with more than 13,000 nodes using an integrated system that consists of 2383-bus Polish TS and multiple instances of medium voltage part of the IEEE 8,500-node DS. Case studies demonstrate that the proposed approach is scalable and can provide more than tenfold speed up on the solve time of very large-scale integrated T&D systems. Overall, this work develops practically applicable and efficient demand dispatch coordinator able to integrate DERs into DS while ensuring the grid operational constraints are not violated. Additionally, the dynamics introduced in the DS with such integration that travels to TS is also studied collectively using integrated T&D co-simulation and in the final step, a mathematically comprehensive model tackles the scalability, solve-time and computational memory usage concerns for large scale integrated T&D co-simulation and applications

Planning and Operation of Low Voltage Distribution Networks: A Comprehensive Review

YesThe low voltage (LV) distribution network is the last stage of the power network, which is connected directly to the end user customers and supplies many dispersed small-scale loads. In order to achieve environmental targets and to address the energy shortage issue, governments worldwide increase the renewable energy sources (RES) into the electricity grid. In addition, different types of low carbon technologies (LCTs) such as electric vehicles (EVs) are becoming widely used. A significant portion of RES and LCTs is penetrated into the LV distribution network, which poses a wide range of challenges. In order to address these challenges, there is a persistent need to develop traditional planning and operation frameworks to cope with these new technologies. In this context, this paper provides a comprehensive review about planning, operation, and management of LV distribution networks. The characteristics, types, and topologies of LV distribution networks plus different aspects of operation and planning are investigated. An insightful investigation of the reasons impacts and mitigation of voltage and current unbalanced in LV networks is provided. Moreover, the main three-phase power flow techniques used to analyze the LV networks are analyzed

A review on economic and technical operation of active distribution systems

© 2019 Elsevier Ltd Along with the advent of restructuring in power systems, considerable integration of renewable energy resources has motivated the transition of traditional distribution networks (DNs) toward new active ones. In the meanwhile, rapid technology advances have provided great potentials for future bulk utilization of generation units as well as the energy storage (ES) systems in the distribution section. This paper aims to present a comprehensive review of recent advancements in the operation of active distribution systems (ADSs) from the viewpoint of operational time-hierarchy. To be more specific, this time-hierarchy consists of two stages, and at the first stage of this time-hierarchy, four major economic factors, by which the operation of traditional passive DNs is evolved to new active DNs, are described. Then the second stage of the time-hierarchy refers to technical management and power quality correction of ADSs in terms of static, dynamic and transient periods. In the end, some required modeling and control developments for the optimal operation of ADSs are discussed. As opposed to previous review papers, potential applications of devices in the ADS are investigated considering their operational time-intervals. Since some of the compensating devices, storage units and generating sources may have different applications regarding the time scale of their utilization, this paper considers real scenario system operations in which components of the network are firstly scheduled for the specified period ahead; then their deviations of operating status from reference points are modified during three time-intervals covering static, dynamic and transient periods

Proactive Monitoring, Anomaly Detection, and Forecasting of Solar Photovoltaic Systems Using Artificial Neural Networks

The world of energy sustainability landscape is witnessing high proliferation of smartgrids and microgrids, it has become significant to use intelligent tools to design, operate and maintain such crucial systems in our lives. Solar energy is an intermittent source and purely Photovoltaic (PV) based, or PV and storage based smartgrids require characterization and modelling of PV resources for an effective planning and effective operations. This dissertation familiarizes briefly the existing tools for design, monitoring, forecasting and operation of a solar system in smart electric grids infrastructure and proposes a unique application-based infrastructure to monitor, operate, forecast and troubleshoot a working PV of a smartgrid. A resilient smartgrid communication is proposed which enables monitoring and control of different elements in any PV system. This communication architecture is used to facilitate a feedback-oriented monitoring of different elements in a microgrid ecosystem and investigated thoroughly. This integrated architecture which is a combination of sensors, network elements, database and computation elements is designed specifically for solar photovoltaic (PV) powered grids on modular basis. Apart from this, the network resilience and redundancy for smooth and loss less communication is another characteristic factor in this research work. Subsequently, a deep neural network algorithm is developed to diagnose the underperformance in the generation of a PV system connected to a smartgrid. As PV generation is predominantly dependent on climatic parameters, it is necessary to have a mechanism for understanding and diagnosing performance of the system at any given instance. To address this challenge, this deep neural network architecture is presented for instantaneous performance diagnosis. The proposed architecture enabled modeling and diagnose of soiling and partial shade conditions prevalent with an accuracy of 90+%. Features of monitoring and regulating the generation and demand side of the grid were integrated through network along with feedback-based measures for effective performance in the PV system of a smartgrid or microgrid using the same network. The novelty in this work lies in real-time calculation of ideal performance and comparison for diagnosing critical performance issues of solar power generation like soiling and partial shading. Furthermore, long-short term memory (LSTM), which is a recurrent neural network model, is created for forecasting the PV solar resources, in which can assist in quantifying PV generation in various time intervals (hourly, daily, weekly). PV based smartgrids often experience expensive or inaccurate resources planning due to the lack of accurate forecasting tools where the projected methodology would eliminate such losses. This research work in its whole provides a different proposition of vertical integration which can transform into a new concept called Internet of Microgrid (IoMG). Planning, monitoring and operation form the core of smartgrids administration and if intelligent tools intertwined with network are being used as integral part in each of these aspects, then it forms a holistic view of smartgrids

Research on Three-phase Optimal Power Flow for Distribution Networks Based on Constant Hessian Matrix

The optimal power flow (OPF) problem for active distribution networks with distributed generation (DG) and a variety of discretely adjustable devices (e.g., on-load tap-changers, OLTCs) is essentially a non-convex, nonlinear, mixedinteger optimization problem. In this paper, the quadratic model of three-phase OLTCs is proposed by adding branch currents as unknown variables, which guarantee a constant Hessian matrix throughout iterations. This paper proposes a three-phase OPF model for active distribution networks, considering a three-phase DG model. The OPF model is solved by an interior point method incorporating a quadratic penalty function as opposed to a Gaussian penalty function. Furthermore, a voltage regulator is also incorporated into the OPF model to form an integrated regulation strategy. The methodology is tested and validated on the IEEE 13-bus three-phase unbalanced test system.<br/

Emerging Technologies for the Energy Systems of the Future

Energy systems are transiting from conventional energy systems to modernized and smart energy systems. This Special Issue covers new advances in the emerging technologies for modern energy systems from both technical and management perspectives. In modern energy systems, an integrated and systematic view of different energy systems, from local energy systems and islands to national and multi-national energy hubs, is important. From the customer perspective, a modern energy system is required to have more intelligent appliances and smart customer services. In addition, customers require the provision of more useful information and control options. Another challenge for the energy systems of the future is the increased penetration of renewable energy sources. Hence, new operation and planning tools are required for hosting renewable energy sources as much as possible