Quasi-static Time-series Research Articles

Engineering Performance and Spatial Models Highlight Key Considerations for Supporting Broadscale Replacement of Environmentally Sensitive (ES) Vessel Moorings

Chain moorings are widely used for securing vessels in coastal zones worldwide but can cause environmental damage to the seabed. Although Environmentally Sensitive (ES) mooring alternatives are available, wide-scale adoption and replacement of existing chain moorings have been limited. Adoption may have been hindered by a lack of information relating to the performance and movement characteristics of ES moorings in contrast to chain moorings. The engineering performance of both chain and ES moorings, including tension loading and horizontal movement, was explored using a quasi-static time series model. The performance of chain moorings depended on weather conditions; in simulated extreme weather conditions, chain moorings experienced a surprisingly high tensile load, more than double (118%) the working load limit. However, in mild weather conditions, chain moorings had the lowest tension loads compared to all tested designs. ES moorings experienced lower peak loads compared to chain moorings (47%–61%) in extreme weather but had higher base loads in mild conditions. The lighter, neutrally buoyant mooring line of ES moorings resulted in an increased movement range of the moored vessels under both weather scenarios. Additionally, this study modeled the clearance between ES moorings and neighboring chain moorings, which can be critical knowledge for planning the replacement of only some chain moorings within existing mooring fields. Using an existing mooring field as a case study, only 18% of the moorings have sufficient clearance with their neighboring moorings to be replaced with ES moorings. This study identified better load handling performance of ES than chain moorings under extreme weather conditions, suggesting when designed properly, ES moorings can function as intended to moor vessels. Yet the difference in clearance requirement between mooring designs indicates that careful planning is needed when replacing individual moorings with ES mooring in dense mooring fields. Replacement of chain moorings will need to incorporate a wider spatial perspective, considering differences in movement and spacing required between moorings to minimize the risk of contact between moored vessels. ES moorings could be effective both in their ability to conserve benthic habitats and at securing vessels in extreme conditions, however, the replacement process will require an adaptive management approach and careful consideration of mooring engineering requirements and mooring field spacing.

Accelerating quasi-static time series simulations with foundation models

Accelerating quasi-static time series simulations with foundation models

Enhancing PV Hosting Capacity of Electricity Distribution Networks Using Deep Reinforcement Learning-Based Coordinated Voltage Control

Coordinated voltage control enables the active management of voltage levels throughout electricity distribution networks by leveraging the voltage support capabilities of existing grid-connected PV inverters. The efficient management of power flows and precise voltage regulation through coordinated voltage control schemes facilitate the increased adoption of rooftop PV systems and enhance the hosting capacity of electricity distribution networks. The research work presented in this paper proposes a coordinated voltage control scheme and evaluates the enhanced hosting capacity utilizing a deep reinforcement learning-based approach. A comparative analysis of the proposed algorithm is presented, and the performance is benchmarked against existing local voltage control schemes. The proposed coordinated voltage control scheme in this paper is evaluated using simulations on a real-world low-voltage electricity distribution network. The evaluation involves quasi-static time series power flow simulations for assessing performance. Furthermore, a discussion is presented that reflects on the strengths and limitations of the proposed scheme based on the results observed from the case study.

Reactive compensation in distribution systems and volt/var control analysis: Mutual performance of inverters and curve slope effects

The high penetration of photovoltaic distributed generation is causing overvoltage in distribution networks due to the reverse active power flow. Proposals to mitigate this problem through Volt/Var control (VVC) by photovoltaic inverters are being discussed. However, the configuration of the appropriate Volt/Var curve depends on the topological factors of each system. In this context, this paper presents a practical methodology for calculating the reactive compensation of the local VVC. In addition, the impact of the slope of the curve on power quality and the problems of mutual actuation of inverters in the VVC are analyzed. The studies were conducted in quasistatic time series (QSTS) mode on the IEEE 33 bus system. The slope of the curve affects grid losses and the substation power factor, and can mitigate the negative effects of the mutual actuation of the inverters in the VVC. Based on this, guidelines were established to adapt the definition of the slope to the characteristics of each system.

A quasi-static time-series approach to assess the impact of high distributed energy resources penetration on transmission system expansion planning

Due to advancements in solar cell fabrication and inverter-based technology, as well as decreasing acquisition costs, solar distributed generation systems have emerged as a promising renewable source. Furthermore, electrification of the transportation system is an alternative promoted by many governments to mitigate the dependency on fossil fuels and achieve the goals of decarbonizing the economy. However, interconnecting a large quantity of distributed energy resources (DERs) to the power system reveals technical problems affecting the entire system. Planning coordinators and grid operators need to understand the full-spectrum impact of DERs on the power system to ensure secure and reliable grid planning and operations. The operation of a Hydro-Québec transmission system planned for 2030 is simulated in quasi-static time series mode with a massive integration of 1 million of electric vehicles and 1000 – 3000 MW of distributed photovoltaics. This paper provided findings on assessment of high DER penetrations impacts on the transmission system in terms of voltage control, mitigation means used, MVAR availability and consumption margin, generating unit optimal operation, and switching actions of several equipment.

Revenue-Based Allocation of Electricity Network Charges for Future Distribution Networks

This paper investigates the economic implications that high penetrations of distributed energy resources (DER) have in future distribution networks, and proposes a novel scalable scheme for the assignment of use of network charges based on individual participant nodes’ revenue. For validation purposes, a techno-economic simulation is proposed to understand how power and revenue flows will change. A year-long high-resolution quasi-static time series (QSTS) simulation, two price schemes, four trading environments, and four DER allocation methods from the literature are used to study economic benefits for individual participants and the supplier. Testing is performed using the IEEE 33-bus and 123-bus networks, and an Irish urban medium voltage feeder. Revenue flow is presented as an indicator of which participant nodes are profiting more from grid usage, and therefore should be responsible for greater network charges, this is validated against traditional and alternative schemes. Important reductions in use of network charges are seen especially by participant nodes with a higher PV generation-to-load and self-consumption rates. The proposed method is only relevant when dynamic tariffs are in place and/or local trading is enabled. Ultimately, results suggest that the income from network charges received by the supplier is increased when dynamic tariffs are used.

Temporally-adaptive Robust Data-driven Sparse Voltage Sensitivity Estimation for Large-scale Realistic Distribution Systems with PVs

This letter proposes a new robust data-driven sparse voltage sensitivity estimation approach for large-scale distribution systems with PVs. It has a high statistical efficiency to mitigate the impacts of PV stochasticity and unknown measurement noise under various system operating conditions. A new adaptively-weighted <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">l</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> sparsity-promoting regularization is developed, exploiting the temporal characteristic of time-varying sensitivities for better accuracy. The <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">l</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> regularization is used to mitigate collinearity impacts. The Huber loss function and a concomitant scale estimate are adopted to mitigate the impacts of unknown and non-Gaussian noise. These techniques are implemented in a fast recursive parallel computing framework. The proposed estimator is tested by quasi-static time series simulations of a large three-phase unbalanced system with PVs and various discrete time-delayed control devices. Results validate the superior robustness and efficiency of the proposed estimator over existing alternatives.

A Framework to Predict Variability Characteristics in Building Load Profiles

The expansion of Advanced Metering Infrastructure (AMI) has provided building operators and researchers detailed information on building energy consumption. The majority of AMI systems, however, record data at relatively low resolutions of 15, 30, or 60 minutes, due to cost, storage and bandwidth limitations. Emerging applications in power flow analysis, Quasi-Static Time-Series Simulation (QSTS), smart grid integration and load matching, however, require data at higher resolutions. Short-term energy demand can deviate significantly from long-term averages, with an unknown magnitude and frequency when only low-resolution load profile data is available. This paper presents a novel data-driven approach to predict characteristics of the missing high-resolution information in a low-resolution signal, applicable to both measured and modeled building load profile data, utilizing machine learning regression algorithms. In the proposed framework, the relationship between characteristics of high-resolution and low-resolution signals is learned from the decomposition and characterization of a subset of high-resolution building data. This paper validates the underlying hypotheses and methodology of this approach through a single-building case study, training a variety of machine learning models on one year of data, and using the resulting models to predict high-resolution characteristics in a different year. An Ensemble Tree regression model demonstrates a high predictive accuracy (R2 of 0.79-0.92) for several statistical metrics of the high-resolution load profile. These results support the broader potential for leveraging low-resolution information to accurately constrain predictions of missing high-resolution information in building load profiles, which may greatly increase the utility of both measured and modeled data in many practical and research applications. Generalizing such models will require analysis of high-resolution data from a diverse set of building types.

Fast Quasi-Static Time-Series Simulation for Accurate PV Inverter Semiconductor Fatigue Analysis with a Long-Term Solar Profile

Power system simulations with long-term data typically have large time steps, varying from one second to a few minutes. However, for PV inverter semiconductors in grid-connected applications, the minimum thermal stress cycle occurs over the fundamental grid frequency (50 or 60 Hz). This requires the time step of the fatigue simulation to be approximately 100 μs. This small time step requires long computation times to process yearly power production profiles. In this paper, we propose a fast fatigue simulation for inverter semiconductors using the quasi-static time-series simulation concept. The proposed simulation calculates the steady state of the semiconductor junction temperature using a fast Fourier transform. The small thermal cycling during a switching period and even over the fundamental waveform is disregarded to further accelerate the simulation speed. The resulting time step of the fatigue simulation is 15 min, which is consistent with the solar dataset. The error of the proposed simulation is 0.16% compared to the fatigue simulation results using the complete thermal stress profile. The error of the proposed method is significantly less than the conventional averaged thermal profile. A PV inverter that responds to a transactive energy system is simulated to demonstrate the use of the proposed fatigue simulation. The proposed simulation has the potential to cosimulate with system-level simulation tools that also adopt the quasi-static time-series concept.

Non-Bias Allocation of Export Capacity for Distribution Network Planning With High Distributed Energy Resource Integration

A novel distributed energy resources (DER) allocation method focused on grid constraints that avoids topological bias is proposed for distribution networks. A technology-agnostic approach is used, where a non-bias allocation of export capacity (NAEC) not specific to generation type is calculated. Moreover, the proposed NAEC is extended from an export capacity into a hosting capacity (HC) using a statistical approach. The methods are tested using the IEEE 33-bus distribution system, and two typical Irish distribution feeders -one urban, one rural- as case studies. Using a high-resolution year-long quasi-static time series simulation (QSTS) and three different generation profiles, the proposed NAEC method is validated against current practices and state of the art allocation methods in terms of active balancing, security of supply, interactions between users, operational concerns, and fairness. Results show that an equivalent or higher level of DER penetration is achieved using the proposed methodology. There are no additional constraint violations using the NAEC methodology, moreover, time slots with violations are reduced, improving security of supply. Furthermore, results suggest that avoiding topological bias makes the network accessible for more users, and prioritises self-consumption.

Simplified A-Diakoptics for Accelerating QSTS Simulations

The spread of distributed energy resources (DERs) across the distribution power system demands complex planning studies based on quasi-static-time-series (QSTS) simulations, requiring a significant amount of computing time to complete, leading planners to look for alternatives to QSTS. Diakoptics based on actors (A-Diakoptics) is a technique for accelerating simulations combining two computing techniques from different engineering fields: diakoptics and the actor model. Diakoptics is a mathematical method for tearing networks, reducing their complexity by using smaller subcircuits that can be solved independently. The actor model is used to coordinate the interaction between these subcircuits and their control actions, given the pervasive inconsistency that can be found when dealing with large-scale models. A-Diakoptics is a technique that simplifies the power flow problem for improving the simulation time performance, leading to faster QSTS simulations. This paper presents a simplified algorithm version of A-Diakoptics for modernizing sequential power simulation tools to use parallel processing. This simplification eliminates critical points found in previous versions of A-Diakoptics, improving the performance of the algorithm and facilitating its implementation to perform QSTS simulations. The performance of the new version of A-Diakoptics is evaluated by its integration into EPRI’s open-source simulator OpenDSS, which uses standard computing architectures and is publicly available.

Design and field implementation of smart grid-integrated control of PV inverters for autonomous voltage regulation and VAR ancillary services

Ancillary services from Photovoltaic (PV) inverters can increase distribution system flexibility and alleviate the voltage regulation challenges associated with high PV penetration levels. However, the required communication infrastructure and smart grid integration challenges limit the broad deployment of PV ancillary services. This paper presents a cost-effective volt/var control (VVC) of multi-string PV inverters for active voltage regulation and reactive power dispatch using the existing smart distribution infrastructure to avoid the upfront costs of providing PV ancillary services. The proposed VVC model is developed in MATLAB/Simulink to adapt PV reactive power compensation according to the X/R characteristics of the distribution feeder. An IEC 61131-3 compliant prototype is designed based on Simulink PLC code and deployed to a commercially available remote terminal unit (RTU) using CODESYS standardization tool to address smart grid integration challenges. The proposed VVC scheme is tested in a real-world grid-connected PV system with multi-string inverters for experimental validation. Quasi-static time-series simulation and experimental results demonstrate the validated effectiveness of the proposed control scheme in controlling fast PV fluctuations, resolving voltage violations, voltage flickers, and enabling higher PV penetration.

Impacts of EV residential charging and charging stations on quasi-static time-series PV hosting capacity

Impacts of EV residential charging and charging stations on quasi-static time-series PV hosting capacity

Fast parallel quasi-static time series simulator for active distribution grid operation with pandapower

The increasing penetration from intermittent renewable distributed energy resources in distribution grid brings along challenges in grid operation and planning. To evaluate the impact on the grid voltage profile, grid losses, and discrete actions from assets (e.g. transformer tap changes), quasi-static simulation is an appropriate method. Quasi-static time series and Monte-Carlo simulation requires a tremendous number of power flow calculations (PFCs), which can be significantly accelerated with a parallel High-Performance Computing (HPC)-PFC solver. In this paper, we propose a HPC-PFC-solver-based grid simulation (parallel simulation) approach for a multi-core CPU platform as well as a greedy method, which can prevent the errors caused by simultaneous parallel simulation. The performance of the proposed approach and the comparison is demonstrated with two use cases.

Techno-Economic Value of DERMS for Flexible Interconnection of Solar Photovoltaics

As an alternative to conventional distribution upgrades, distribution system operators (DSOs) are increasingly exploring flexible interconnection capacity solutions (FICSs), where distributed energy resources (DER) output is actively managed and curtailed to avoid infrequent violations. While a FICS has the potential to allow more DER to be interconnected at a reduced cost, increased grid utilization, and more rapid interconnection processes, there is limited understanding of the technical and economic value of FICSs. This paper assesses the trade-offs between the lost solar PV productivity and interconnection cost savings enabled by a distributed energy resources management system (DERMS) under a flexible interconnection approach. Further, it presents select results of a detailed techno-economic study analysing over 900 scenarios and sensitivities using three New York distribution circuits and detailed quasi-static time-series (QSTS) load flow simulations to determine how the value of FICS is influenced by PV deployments and other key aspects. For each scenario and sensitivity, conventional distribution upgrade measures were identified, PV curtailment under FICSs was estimated, and an economic analysis was performed to quantify the value of FICS. The findings help identify what circumstances make a FICS most valuable and how key factors affect the value.

Distributed Energy Resource Benchmark Models for Distribution Impact Assessment - Update of Activities by CIGRE Working Group C6.36

With growing levels of distributed energy resources (DER), effective assessment and design of active distribution systems increasingly depend upon access to models that accurately represent the various DER and their controls. However, as DER technologies continue to rapidly evolve, along with the analysis needed to capture their impacts on the system, there is an increasing need for benchmark models that can serve as a common reference by distribution engineers, vendors, academia, and other industry stakeholders. This paper provides an update on the work by CIGRE Working Group C6.36: “Distributed Energy Resource Models for Impact Assessment” to identify a set of benchmark DER models for quasi-static time-series load flow (QSTS) simulations, increasingly used to evaluate active distribution system impacts and performance. These benchmark models can be used by the industry to understand and verify the performance of existing models as well as serve as a reference for further modifications and enhancements. This paper discusses the working groups proposed DER benchmark model framework, which specifies the DER benchmark model hierarchy and requirements. Additionally, initial efforts in developing benchmark models for PV systems, energy storage systems, and smart inverters are presented along with the lessons learned and future work.

Improving the Performance of Integrated Power-Hardware-in-the-Loop and Quasi-Static Time-Series Simulations

This article introduces a novel multirate cosimulation architecture that overcomes previous challenges integrating faster real-time, microseconds-scale, power-hardware-in-the-loop (PHIL) with larger scale but slower, real-time, seconds-scale, quasi-static time-series (QSTS) simulation. Specifically, an intermediate reduced-equivalent electromagnetic transient (EMT) model duplicates the key power system topology to capture high-speed dynamics and converge hardware-power system interactions between QSTS updates. Exchanging multidimensional parameter vectors (loads, control status, etc.) between the QSTS and EMT models enables capturing the interactions of the rich, high-node-count (thousands of electrical nodes) QSTS model with the hardware. This architecture offers full spatial resolution from QSTS, including individual load dynamics, actual distribution management system controls, and nodal voltages. Simultaneously, the intermediate EMT model provides more detailed high-speed transients of key distributed energy resource hardware interactions. In addition, we use careful PHIL interface design and the exchange of complex power data, rather than current, to further improve performance. This cosimulation architecture is demonstrated by testing a simulated distribution system with an interconnected 500-kVA advanced photovoltaic (PV) inverter in PHIL. The architecture successfully captured PV local volt-volt ampere reactive (volt-VAR) control interactions with the larger network under time-varying electrical and weather conditions.

Aggregation of Radial Distribution System Bus with Volt-Var Control

The high penetration of the distributed energy resources (DERs) encourages themselves to implement grid-supporting functions, such as volt-var control. The quasi-static time-series (QSTS) simulation is an essential technique to evaluate the impact of active DERs on the grid. Meanwhile, the increase of complexity on the circuit model causes a heavy computational burden of QSTS simulation. Although circuit reduction methods have been proposed, there have been few methods that can appropriately handle the distribution system (DS) with multiple voltage control devices, such as DERs implementing volt-var control. To address the remaining issues, this paper proposes an offline bus aggregation method for DS with volt-var control. The method determines the volt-var curve for the aggregated bus on the basis of historical data to reduce error in the aggregated model, and its offline process solves the computational convergence issue concerned in the online one. The effectiveness of the proposed method is validated in the simulation using a Japanese low-voltage DS model. The simulation results show that the proposed method can reduce the voltage error and computational time. Furthermore, the versatility of the proposed method is verified to show the performance does not heavily depend on how to select historical data for model-building.

Electric Vehicles Charging Management for Real-Time Pricing Considering the Preferences of Individual Vehicles

The paper proposes a real-time model for electric vehicles (EVs) controlled load charging. The proposed demand-side management (DSM) of EVs is implemented based on queuing analysis with a nonhomogeneous arrival rate and charging service periods dataset. An electric vehicle model is used which is based on a statistical survey to represent the uncontrolled demand of the EVs. A probability distribution for the time at which EVs are plugged and the corresponding value of the state of charges (SOCs) are considered. The preferences of individual EVs have been fully exploited through a set of instructions to fulfill the needs of the vehicles’ owners. The designated preferences include the owner setting for both, charging price preferences (OPR), and the maximum estimated parking time duration (EPTD). The quasi-static time-series (QSTS) simulation is used to simulate real-time scenarios of the 24-h simulation period. The IEEE 123 nodes radial test feeder is analyzed with different daily load curves, EV charging scenarios, and wind power penetrations. The results show the effectiveness of the proposed DSM in avoiding excessive levels of charging with/without penetration of non-dispatchable wind power generation. The proposed DSM enables the EVs to charge with low tariff rates either at excessive renewable power generation or late evening hours with available committed bulk power plants and light loading conditions.

Multi-Area Aggregation of Multi-Grounded Unbalanced Distribution Systems

Currently, several methods applied in distribution systems need power flow solutions, such as evolutionary algorithms, exhaustive search, neural network training, continuation power flow, quasi-static time-series, among others. A properly modeled distribution system requires detailing and expects a three-phase network with neutrals and groundings, which help increase simulation times. For a thorough modeling, but with reduced simulation time, distribution system equivalency can be determined using a multi-area aggregation method in three-phase four-wire multi-grounded feeders, where even the modeling of neutral cables and groundings are allowed. The proposed method enables the user to represent complex network components as a reduced size subnet, achieving a considerable computational time reduction. The proposed method can be inserted into OpenDSS , or multiphase methods, using Newton - Raphson and Backward-Forward Sweep algorithms. Results show that the method is capable of mathematically finding the correct solution for all loading levels. The exactness of the proposition is evaluated using the simple NEV test feeder, IEEE 123, the IEEE 8500 Node Test Feeder, and a meshed network having unbalanced feeders with mutual coupling between different voltage levels.