Large Interconnected Systems Research Articles

Combining monthly wind and inflow uncertainties in the stochastic dual dynamic programming

AbstractFollowing a global trend, intermittent sources, especially wind, have been experiencing accelerated growth in Brazil—in the last decade, wind power grew 13 times and became the second largest source in the electricity mix (12%), just behind hydropower (60%). Currently, although following regulatory guidelines, the representation of wind power in the long-term operation planning model is done in a simplified way, based on the monthly average of the last five years of aggregated generation, thus demanding improvements. The objective of this work is to describe an approach to be used by the Brazilian power industry to represent the uncertainties of monthly wind power production in the SDDP algorithm applied in the long-term operation planning model, keeping the large-scale stochastic problem still computationally viable, when applied to large interconnected systems, especially with hydroelectric predominance. The proposed methodology comprises statistical clustering of wind regimes and definition of equivalent wind farms; evaluation of monthly transfer functions between wind speed and power production; integrated generation of monthly multivariate synthetic scenarios of inflows and winds, considering associated cross-correlations; and representing monthly wind power in the SDDP algorithm. The application to real configurations of the Brazilian interconnected system, including case studies related to the monthly operation program and the calculation of the maximum amount of energy that can be traded in long-term power purchase agreements, points to its effectiveness and the relevance of modeling the wind uncertainties in the long-term operation planning of large hydro-dominated systems.

Compositional Approximately Bisimilar Abstractions of Interconnected Systems

This paper formulates and studies the concepts of approximate (alternating) bisimulation relations characterizing equivalence relations between interconnected systems and their abstractions. These equivalence relations guarantee that the abstraction preserves the dynamics of the original model. We develop a compositional approach to abstraction-based controller synthesis based on the notions of approximate composition and incremental input-to-state stability. In particular, given a large system consisting of interconnected components, we provide conditions under which the notion of approximate (alternating) simulation relation is preserved when moving from the subsystems to the large interconnected system. The effectiveness of the proposed results has been evaluated through traffic congestion control.

Sparsistent filtering of comovement networks from high-dimensional data

Network filtering is a technique to isolate core subnetworks of large and complex interconnected systems, which has recently found many applications in financial, biological, physical and technological networks among others. We introduce a new technique to filter large dimensional networks arising out of dynamical behavior of the constituent nodes, exploiting their spectral properties. As opposed to the well known network filters that rely on preserving key topological properties of the realized network, our method treats the spectrum as the fundamental object and preserves spectral properties. Applying asymptotic theory of high-dimensional covariance matrix estimation, we show that the proposed filter can be tuned to interpolate between zero filtering to maximal filtering that induces sparsity via thresholding, while having the least spectral distance from a consistent (non-)linear shrinkage estimator. We demonstrate the application of our proposed filter by applying it to covariance networks constructed from financial data, to extract core subnetworks embedded in full networks.

Evaluation of Numerical Methods for TSCOPF in a Large Interconnected System

Transient stability-constrained optimal power flow (TSCOPF) models comprehensively analyze the security and economic operation of power systems. However, they require a high computational effort and can suffer from convergence problems when applied to large systems. This study analyzes the performance of eleven numerical integration algorithms applied to ordinary differential equations that represent power system dynamics in a TSCOPF model. The analyzed algorithms cover a range of explicit and implicit methods, including the recently published semi-explicit and semi-implicit Adams-Bashforth-Moulton formulas, together with several initialization techniques. The integration methods are applied to a model of the Iberian Peninsula power system, and their performance is discussed in terms of convergence, accuracy, and computational effort. The results show that most implicit methods converge to the solution, even for large time steps. In particular, the Adams-Moulton method of order two and Simpson’s rule, both initialized with RK4, outperform the trapezoidal rule, which is the default method in TSCOPF models.

Compositional stability criteria based on cyclically neutral supply conditions

In this paper we consider stability of large scale interconnected nonlinear systems that satisfy a strict dissipativity property in terms of local storage and supply functions. Existing compositional stability criteria certify global stability by constructing a global Lyapunov function as the (weighted) sum of local storage functions. We generalize these results by unifying spatial composition, i.e., (weighted) sum of local supply functions is neutral, with temporal composition, i.e., (weighted) sum of supply functions over a time cycle is neutral. Two benchmark examples illustrate the benefits of the developed compositional stability criteria in terms of reducing conservatism and constrained distributed stabilization.

Parameter and topology identification of delayed hypernetworks with stochastic perturbation

In the past two decades, large interconnected systems have been modeled as single-layer networks. In fact, various networks may interact and influence with each other to form the hypernetworks. As one of the most important problems in network science, topology identification of complex network has been widely studied in single-layer networks. On the contrary, topology identification of hypernetwork has received little attention. For a hypernetwork, different layers may have different delay, and noise is usually unavoidable. Therefore, the delayed hypernetwork with stochastic perturbation is put forward in this manuscript. By using synchronization-based identification method, the schemes to identify the unknown topology and system parameters are proposed. It is found that the unknown topology and system parameters of the drive network can be correctly identified, regardless of whether the topology of the response network is the same as that of the drive network. Numerical examples are illustrated to verify the effectiveness of the proposed algorithm. In addition, it is found that the identification time increases with the varying interval of coupling strengths, and the interval of the time delays and stochastic perturbations have opposite effects on the identification time.

Stability analysis for interconnected system with quantized sampled-data control

In this paper, we investigate the stability analysis for interconnected system, which is composed of multiple subsystems with sampled-data control and state quantization. The controlled interconnected system is modeled as a time-delay system with time-varying delays. By employing the information of sampling instants, a discontinuous Lyapunov functional is constructed. Using this functional, we derive tractable sufficient conditions to ensure the well-posedness and asymptotic stability of the considered system by taking the interconnected structure into consideration. These conditions depend only on the sampling interval, quantizer parameters and matrices parameters of individual subsystem, making them attractive in computation verification for large scale interconnected system. Furthermore, a grid search based optimization algorithm is proposed to reduce the total number of sampled data for the whole system. The effectiveness and applicability of the main results are shown by two examples.

Spatial variation in provenance signal: identifying complex sand sourcing within a Carboniferous basin using multiproxy provenance analysis

Multiple factors (e.g. source rock composition, climate, nature/scale of sedimentary system) influence the volume and composition of sediment delivered to basins. Fluctuations in these parameters produce cryptic source signals which can vary within the same sedimentary system. Bespoke multi-proxy provenance approaches, targeted at minerals of variable stability, allow for an assessment of natural biasing (recycling) and intra-basinal spatial variations. Provenance of fluvial/deltaic sandstones (Mullaghmore Sandstone Formation) in the NW Carboniferous Basin, Ireland, has been constrained using zircon and apatite U–Pb geochronology, trace elements in apatite and Pb-in-K-feldspar analysis. Zircon U–Pb grain populations are consistent with feldspar data, suggesting Proterozoic basement highs offshore Ireland and Scotland were the main contributor with minor supply from Archean–Paleoproterozoic rocks of Greenland/NW Scotland and Caledonian-aged rocks. However, apatite data show a much larger proportion of Caledonian-aged grains of metamorphic origin, suggesting significant sediment was recycled from Neopropterozoic metasedimentary rocks. The spatial variation in provenance indicates that, at onset of clastic input, sediment was being routed to the basin through a complex drainage system, comprising several discrete hinterland catchments, rather than supply from a single, large interconnected sedimentary system. Such complexities can only be identified with the careful application of a bespoke multi-proxy provenance approach. Supplementary material: Tables 1-5 and individual Pb-in-K feldspar plots are available at https://doi.org/10.6084/m9.figshare.c.5536691

Citywide quality of health information system through text mining of electronic health records

A system of hospitals in large cities can be considered a large and diverse but interconnected system. Widely applied in hospitals, electronic health records (EHR) are crucially different from each other because of the use of different health information systems, internal hospital rules, and individual behavior of physicians. The unstructured (textual) data of EHR is rarely used to assess the citywide quality of healthcare. Within the study, we analyze EHR data, particularly textual unstructured data, as a reflection of the complex multi-agent system of healthcare in the city of Saint Petersburg, Russia. Through analyzing the data collected by the Medical Information and Analytical Center, a method was proposed and evaluated for identifying a common structure, understanding the diversity, and assessing information quality in EHR data through the application of natural language processing techniques.

Risk-averse optimization for resilience enhancement of complex engineering systems under uncertainties

With the growth of complexity and extent, large scale interconnected network systems, e.g., transportation networks or infrastructure networks, become more vulnerable to external disturbances. Hence, managing potential disruptive events during the design, operating, and recovery phase of an engineered system and therefore improving the system’s resilience is an important yet challenging task. To ensure system resilience after the occurrence of failure events, this study proposes a mixed-integer linear programming (MILP) based restoration framework using heterogeneous dispatchable agents. The scenario-based stochastic optimization (SO) technique is adopted to deal with the inherent uncertainties imposed on the recovery process from nature. Moreover, different from conventional SO using deterministic equivalent formulations, the CVaR risk measure is implemented for this study because of the temporal sparsity of the decision making in applications such as the recovery from extreme events. The resulting restoration framework involves a large-scale MILP problem and thus an adequate decomposition technique i.e. modified Lagrangian dual decomposition, is also employed to achieve tractable computational complexity. Case study results based on the IEEE 37-bus test feeder demonstrate the benefits of using the proposed framework for resilience improvement as well as the advantages of adopting SO formulations.

Adaptive Mho Distance Protection for Interconnected Transmission Lines Compensated with Thyristor Controlled Series Capacitor

This paper proposes an adaptive dynamic Mho distance relay based on a phase comparator scheme for protecting interconnected transmission networks compensated with a Thyristor Controlled Series Capacitor (TCSC). The proposed relay uses an impedance index factor to initiate the fault detection subroutine. The RMS of the positive sequence current of the faulted loop and the TCSC terminal current are compared for TCSC zone identification. A phase comparator for ground and phase distance elements is proposed, relying on the positive sequence voltage as a polarized memory quantity, while the operating and polarizing quantities are developed using estimated TCSC impedance to mitigate its negative impact. The proposed scheme is easy in implementation and independent on synchronized data transfer, as minimum communication requirements are needed. To evaluate the performance of the proposed scheme, extensive simulation studies were carried out on an IEEE9 bus system compensated with TCSC for different firing angles covering four modes of TCSC operations, different fault types, and fault locations. In addition, an IEEE-39 bus network, as a large interconnected system, is tested for validation purposes. The achieved results designate the precision of the proposed scheme. Moreover, the results indicate its effectiveness for fault resistance tolerance, close-in three phase faults, and stable power swing phenomenon compared with conventional relays.

On identity-aware replication in stochastic modeling for simulation-based dependability analysis of large interconnected systems

This paper focuses on the generation of stochastic models for dependability and performability analysis, through mechanisms for the automatic replication of template models when identity of replicas cannot be anonymous. The major objective of this work is to support the modeler in selecting the most appropriate replication mechanism, given the characteristics of the system under analysis. To this purpose, three most used solutions to identity-aware replication are considered and a formal framework to allow representing them in a consistent way is first defined. Then, a comparison of their behavior is extensively carried out, with focus on efficiency, both from a theoretical perspective and from a quantitative viewpoint. For the latter, a specific implementation of the considered replication mechanisms in the Möbius modeling environment and a case study representative of realistic interconnected infrastructures are developed.

Review of Methods to Accelerate Electromagnetic Transient Simulation of Power Systems

Converter-based generators are increasingly replacing classical synchronous generation, resulting in significant challenges to the operation and planning of modern power systems. Power electronics (PE)-based equipment, along with non-linear PE-driven loads, introduce time-varying characteristics and fast switching behavior that increases the complexity of the power system model. Faster control actions are needed to overcome the fast switching dynamics to ensure the reliability and stability of future power systems. Thus, this requires advanced and detailed simulation methods and tools with highly accurate equivalent models to embody the relatively slower electromechanical to faster electromagnetic transient (EMT) phenomena. Conventional transient stability analysis using positive-sequence simulators has become inadequate for representing converter-dominated power systems, while EMT simulators suffer from the high computational burden. This review paper presents accelerated EMT simulation methods and tools that are categorized and discussed in three topics: system equivalents, simulation methods, and accelerating tools. Dynamic system equivalent techniques are discussed to model small to large interconnected external systems of the grid network. Moreover, a systematic review is made for existing EMT simulation methods, along with advanced co-simulation methods, for addressing simulation speed and accuracy issues in large power system networks. Emerging hardware-based simulation tools are reviewed that reduce the computational burden and increase the simulation efficiency of the power system model. Challenges and trends in EMT simulation are also presented and concluded by providing perspectives on this research topic.

Novel Data-Driven Distributed Learning Framework for Solving AC Power Flow for Large Interconnected Systems

Recent advancement in power systems induces complexity in large-scale interconnected systems and poses challenges in performing security assessment studies at various operating conditions. Traditional model-based methods are computationally intensive and may not meet the requirements for real-time applications. This paper presents a novel data-driven framework for accelerating the process of obtaining multiple AC power flow (ACPF) solutions for large systems using deep convolutional neural networks (DCNN). DCNN models are designed and trained using various representative power flow cases from a system, whose outputs can be used to perform steady-state security assessment studies. Distributed training with multiple Graphical processing units (GPU)s is implemented using TensorFlow to reduce computation time. The proposed framework is implemented to identify critical buses and recognize the ACPF cases expected to cause steady-state bus voltage violations. The efficacy and feasibility of the proposed framework are evaluated on the Western Electricity Coordinating Council (WECC) 2028 system. Results demonstrate that the proposed framework is highly accurate and possess good interpretability in performing various transmission planning and operation assessment studies for large scale power networks.

Automated Tool to Create Chronological AC Power Flow Cases for Large Interconnected Systems

Power system planning engineers currently perform planning studies based on a few snapshots representing typical system operating points, also known as base power flow cases. However, that is not enough to fully understand and evaluate operational impacts of the current and future grid, especially in high uncertainty and extreme events. Time-series analysis must be considered. We developed a procedure for using production cost model (PCM) simulation data for wind, photovoltaic, and load levels to generate chronological, hourly power flow cases. Because the PCM uses a lossless, linear, DC power-flow solution for simulations, AC power flow must be converged to enable reliability planning studies. This paper describes a procedure to handle losses and reactive power planning for large, interconnected systems. The procedure is illustrated with an example using the Western Electricity Coordinating Council (WECC) 2028 Anchor Data Set (ADS) as a PCM and the WECC 2028 High Summer Power Flow case (22,000 bus system) as references. This procedure can be applied to systems with multiple AC and DC grids of any grid topology.

Inertia Emulation Uncorrelated With Electromechanical Dynamics to Improve Frequency Transients Using Center of Inertia (COI) Frequency Signal

This paper proposes an inertia emulation method that uses the frequency of the center of inertia (COI) as the feedback signal, aiming to slow the frequency change rate and raise the frequency nadir during frequency-dropping events. An approximated model depicting the COI frequency dynamics is first introduced, which shows the COI frequency signal has low observabilities of electromechanical modes. Thus, this feature enables the proposed inertia emulation to react quickly to steep frequency changes without suffering any adverse impacts caused by electromechanical dynamics, such as excessively saturating the controlled objects. Moreover, the electromechanical dynamics associated with small-signal stability properties will not be interrupted by the proposed inertia emulation. In addition, a simple yet effective computing procedure is proposed to configure the critical parameters, as the inertia emulation is implemented with multiple flywheel-based energy storage systems. Simulation results obtained based on two large interconnected systems verify the effectiveness of the proposed inertia emulation in terms of improving the frequency transients as well as its limited correlation with the electromechanical dynamics of the system. The signal transmission latency's impacts on the proposed inertia emulation are also investigated and discussed.

Impact of the configuration and condition of the power system on the damping of low-frequency oscillations

ABSTRACT The current stage of power system development is characterised by the transformation from local electric power systems to global interconnections. It provides economic benefits, improves the reliability of power system operation and increases the quality level. However, such large interconnected systems have some technical and economical limitations, for instance, long distance transmission, and almost have a weak tie between the electric power systems. One of the main problems of the reliability of such large interconnected systems is low-frequency oscillations, which significantly reduces network capacity and leads to dynamic instability. Therefore, the analysis of the influence of various topologies and regime modes of electric power system to the low-frequency oscillations for the development of control actions and recommendations for their effective damping and reduction is relevant. In this paper, simulation and analysis was done by using of two-area electric power systems and using «EUROSTAG» software. The factors, such as the previous steady-state condition and the structure of the electric power system, affecting the damping properties of electric power system and the impact of the Back-to-Back High-Voltage Direct Current link based on voltage source converters to the damping of low-frequency oscillations were considered.

A Grid of Microgrids: Is it the Right Answer? [Point of View

The rapid and worldwide rise in distributed generation capacity, especially photovoltaic, has raised the issue on whether the development and operation of large interconnected systems on a national or continental level will vanish. The usual question is: will the large electric energy systems of today, planned and operated in either a centralized or decentralized way, be replaced by various independent smart-city systems, all with self-healing and other eye-catching characteristics, forming “a grid of microgrids?”

Comprehensive Analysis of the Impact of the TCSC on Distance Relays in Interconnected Transmission Networks

This article extensively investigates the calculations of the compensation factor of the thyristor-controlled series compensator (TCSC), which are used to accurately evaluate the negative impacts of the TCSC on the performance of conventional distance relays. To broadly evaluate the distance protection performance, the TCSC was adapted to the IEEE 9-bus system as one of the interconnected transmission networks that are increasingly spreading to improve service reliability, reduce reserve capacity, and enhance system efficiency. In addition, IEEE 39-bus system, as a large interconnected system, is also examined to generalize the TCSC impact on different interconnected systems. To determine the precise impact, the impedance of the TCSC was calculated based on its practical design parameters. The impedance of the TCSC was examined as a function of transmission line impedance and firing angle. Both Mho and Quadrilateral distance relays were tested using the MATLAB/Simulink environment for different types of faults, fault locations, fault resistances, and firing angles for capacitive, inductive, and blocking modes of TCSC operation. In addition, distance relay performance was evaluated during power swing phenomenon in the presence of the TCSC. Simulation tests indicated the negative impacts of the TCSC on distance relay operation, which are not limited to over-reach and under-reach in faulty conditions but also to maloperation in dynamic disturbances that cause power swing phenomena on the protected line.

Functional reduced order H∞ decentralized observer based control for large scale interconnected nonlinear stochastic systems

In this work, the H∞ decentralized reduced order observer based control for a class of large scale nonlinear stochastic systems is concerned. In this context we consider subsystems which are interconnected by some nonlinear interconnections under quadratic boundedness and Lipschitz property of the system. The proposed control law is based on the resolution of some LMI.