Bulk Power System Research Articles

A secure system integrated with DC-side energy storage for renewable generation applications

Massive energy storage capability is tending to be included into bulk power systems especially in renewable generation applications, in order to balance active power and maintain system security. This paper proposes a secure system configuration integrated with the battery energy storage system (BESS) in the dc side to minimize output power fluctuation, gain high operation efficiency, and facilitate fault ride through, which is suitable for unidirectional renewable power generation systems (power transfer from renewable sources to the grid). The system utilizes robust diode units (DUs) to protect receiving-end devices against dc faults. Also, the BESS and half-bridge modular multilevel converter (MMC) at the receiving end can operate safely and flexibly to achieve stable and high-quality power transfer, in both source power intermittency and dc-link fault cases. Depending on BESS sizing, the source system power fluctuation can be reduced (absorbed by the receiving-end BESS) when a receiving-end grid fault occurs. Topological configuration and control design of the proposed system are presented. Simulation results show the effectiveness of the proposed system in both dc and ac fault cases, with power fluctuation elimination functionality highlighted. The receiving-end operation losses are investigated, showing a high-efficiency system. In addition, key system implementation considerations regarding the proposed system are elaborated.

A new approach to retrofit plans for distributed energy resources to mitigate adverse impacts on bulk power systems stability

This work presents a new methodology to assess the need of a retrofit plan to readjust anti-islanding protection of distributed energy resources (DERs) with focus on bulk power systems stability. The proposed approach aims to reduce DERs cascade disconnection during major disturbances in transmission networks, a phenomenon that can amplify or result in major blackouts in power systems with high or moderate DERs penetration. The proposed methodology is based on the assessment of Dynamic Security Regions with the incorporation of a simplified modeling to represent DERs cascade disconnection. As a result, recommendations for executing a retrofit plan with a low cost, preserving an adequate level of security, are provided. Initially, the impact of DERs disconnection on the Brazilian Interconnected Power Systems (BIPS) is demonstrated, highlighting the importance of modeling such effect in stability studies. Then, the proposed methodology is applied to the BIPS, evidencing its benefits by specifying the minimum amount of DERs that needs to be submitted to a retrofit plan to guarantee an adequate level of security.

Week‐ahead daily peak load forecasting using genetic algorithm‐based hybrid convolutional neural network

Daily peak load forecasting is crucial for the operation of bulk power systems, including economic dispatch and unit commitment. It is also essential for peak load shaving and load management in distribution systems. In power markets, peak load forecasting helps participants develop bidding strategies. This paper proposes a new method, using a hybrid convolutional neural network (CNN) that is cascaded with a fully-connected network, for making week-ahead daily peak load forecasts. The proposed method uses three loops to obtain the optimal CNN: The outer loop performs crossover/mutation operations and tournament selection to produce chromosomes to optimize the network topology and hyperparameters (such as kernel size) of the hybrid CNN by genetic algorithms; the middle loop deals with the order of chromosomes; the inner loop optimizes the synaptic weights and parameters (e.g. values of a kernel) using Adam optimizer. Daily peak load data and corresponding meteorological data for Taiwan are explored. Simulation results show that the proposed method outperforms the traditional CNN, multi-layer neural network, recurrent neural network, support vector regression and vector autoregressive moving average model.

Resurgence of Grid-Forming Inverter Technology [About This Issue

The emergence of grid-forming inverters dates to the early 2000s, following the advent of inverter-based microgrids and distributed energy resources. The “grid-forming” concept was introduced, mainly as a control paradigm for inverter-based resources, to assure the stability of microgrids. Since then, a wide variety of control strategies have been developed for grid-forming inverters, yet their applications are primarily in microgrids or small islands. In recent years, with the rapid growth of inverter-based resources in bulk power systems, there has been a resurgence of interest in grid-forming inverters from power system operators. However, a wide-scale adoption of grid-forming technology is still not ready since it requires updates to codes, standards, and guidelines, along with further developments of models and tools for system planning and operations. This issue of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">IEEE Electrification Magazine</i> delivers five feature articles and two columns that share the prospects and challenges of grid-forming inverter technology. In addition, an article about e-bikes is included.

Flexibility Management in Economic Dispatch With Dynamic Automatic Generation Control

As the installation of electronically interconnected renewable energy resources grows rapidly in power systems, system frequency maintenance and control become challenging problems to maintain the system reliability in bulk power systems. As two of the most important frequency control actions in the control centers of independent system operators (ISOs) and utilities, the interaction between Economic Dispatch (ED) and Automatic Generation Control (AGC) attracts more and more attention. In this paper, we propose a robust optimization based framework to measure the system flexibility by considering the interaction between two hierarchical processes (i.e., ED and AGC). We propose a cutting plane algorithm with the reformulation technique to obtain seven different indices of the system. In addition, we study the impacts of several system factors (i.e., the budget of operational cost, ramping capability, and transmission line capacity) and show numerically how these factors can influence the system flexibility.

Sensitivity Analysis Based Identification of Key Parameters in the Dynamic Model of a Utility-Scale Solar PV Plant

Grid modernization and innovations in clean energy are leading to a rapid increase in the penetration of inverter-based resources (IBRs) like wind power and solar photovoltaic (PV) plants in the bulk power system (BPS). To study the implications on BPS dynamics and mitigate potential risks to grid reliability, the second-generation generic renewable energy system model has been developed earlier. However, this model has three modules with 86 user-defined parameters and eight control flags to facilitate the utility-scale solar PV plant operation in different control modes. It presents a major challenge to the transmission system planning engineers. There is a critical need to identify the key parameters of the dynamic model that are highly sensitive to grid events causing large-scale voltage and frequency disturbances. In this work, a sensitivity analysis based on modified Sobol’ method is proposed for identification of the key parameters in the utility-scale solar PV plant model. The total Sobol’ sensitivity index captures even the higher-order effects of the variations in the parameters. Validation of the identified key parameters was carried out on a modified IEEE 9-bus system and 200-bus synthetic grid using PSS®E for plant-level control and local coordinated control operation of the solar PV plant. The reduced set of parameters identified in this work offer help to utility grid planning teams while conducting dynamic studies to meet the interconnection requirements.

Advanced extended-term simulation approach with flexible quasisteady-state and dynamic semi-analytical simulation engines

Power system simulations that extend over a time period of minutes, hours, or even longer are called extended-term simulations. As power systems evolve into complex systems with increasing interdependencies and richer dynamic behaviors across a wide range of timescales, extended-term simulation is needed for many power system analysis tasks (e.g., resilience analysis, renewable energy integration, cascading failures), and there is an urgent need for efficient and robust extended-term simulation approaches. The conventional approaches are insufficient for dealing with the extended-term simulation of multi-timescale processes. This paper proposes an extended-term simulation approach based on the semi-analytical simulation (SAS) methodology. Its accuracy and computational efficiency are backed by SAS&#x0027;s high accuracy in event-driven simulation, larger and adaptive time steps, and flexible switching between full-dynamic and quasi-steady-state (QSS) models. We used this proposed extended-term simulation approach to evaluate bulk power system restoration plans, and it demonstrates satisfactory accuracy and efficiency in this complex simulation task.

Frequency Regulation Model of Bulk Power Systems With Energy Storage

This paper presents a Frequency Regulation (FR) model of a large interconnected power system including Energy Storage Systems (ESSs) such as Battery Energy Storage Systems (BESSs) and Flywheel Energy Storage Systems (FESSs), considering all relevant stages in the frequency control process. Communication delays are considered in the transmission of the signals in the FR control loop and ESSs, and their State of Charge (SoC) management model is considered. The system, ESSs and SoC components are modelled in detail from a FR perspective. The model is validated using real system and ESSs data, based on a practical transient stability model of the North American Eastern Interconnection (NAEI), and the results show that the proposed model accurately represents the FR process of a large interconnected power network including ESS, and can be used for long-term FR studies. The impact of communication delays and SoC management of ESS facilities in the Area Control Error (ACE) is also studied and discussed, as well as the computational efficiency of the proposed FR model.

Co-Simulation of Transmission and Distribution Systems—From Modeling to Software Development

As the penetration of Distributed Energy Resources (DERs) increases, it becomes critical to model these resources adequately in bulk power system (BPS) operation and planning studies. Adequate in this context refers to capturing the characteristics of the distribution system to the required degree such that reasonable estimates about BPS stability can be ascertained. Historically, performing such studies have been limited due to the unavailability of software capable of executing high fidelity simulation at the required scale on personal workstations i.e. not having to resort to high performance computing resources. In this paper, we present TDcoSim, an open source software that allows user to perform large scale high fidelity simulation for BPS planning and operation studies and (a) outline the necessary details required to build such software, (b) present the practical challenges faced during the development of TDcoSim.

A Review of Current-Limiting Control of Grid-Forming Inverters Under Symmetrical Disturbances

Grid-forming (GFM) inverters are recognized as a viable solution to increase the penetration of renewable energy in bulk power systems. However, they are physically different from synchronous generators in terms of overcurrent capability. To protect the power semiconductor devices and support the power grid under severe symmetrical disturbances, the GFM control systems should be able to achieve the following requirements: current magnitude limitation, fault current contribution, and fault recovery capability. Various current-limiting control methods are reported in the literature to fulfill these goals, including current limiters, virtual impedance, and voltage limiters. This paper presents an overview of those methods. Emerging challenges that need to be addressed, including temporary overcurrent, unspecified output current vector angle, undesired current saturation, and transient overvoltage, are pointed out. Comparative simulations are conducted to demonstrate the performance of different methods under grid voltage drops and phase jumps. Finally, open issues of current-limiting control methods for GFM inverters, including transient stability assessment, voltage source behavior under overcurrent conditions, and windup of voltage controllers, are shared.

Promising Grid-Forming VSC Control Schemes Toward Sustainable Power Systems: Comprehensive Review and Perspectives

Driven by environmental and economic aspects, the proliferation of renewable energy sources (RES) has been expanded in power systems worldwide. In this regard, the intermittent generation of such RESs (e.g., photovoltaic and wind farms) can cause several operational and stability problems in such low-inertia power systems. To handle these issues, great interest in the literature has been directed to develop feasible grid-forming voltage source converters (VSC) control schemes that have voltage/frequency regulatory functions. Accordingly, an inclusive review is presented in this paper for these promising grid-forming VSC control schemes which will be the backbone of sustainable converter-dominated power systems. Specifically, control structures, smart grid-support functionalities, stability issues, and fault current mitigations are compared considering the existing grid-forming VSC control schemes. Besides, the applications of grid-forming VSC along with their benefits and drawbacks are investigated for both isolated and bulk power systems. The evaluation aspects are also explored for assessing the performance of the existing VSC control schemes in the grid. Finally, the current challenges that face VSC in forthcoming applications and existing gaps are highlighted while corresponding perspectives for future research studies are defined for stable sustainable low-inertia power systems.

Cost-based Risk Approach for Spinning Reserve Assessment in Bulk Power Systems

Spinning reserve (SR) is one of the most prevalent methods for balancing grid uncertainties, such as generator faults, to maintain grid reliability. Literature review shows that several deterministic as well as probabilistic methos have been proposed for determining SR. It is always a challenge for a system operator to decide which approach better from security and reliability point of view. This is important because the allocated SR may provide in some cases a misleading sense of confidence with respect to safe, secure, reliable and economic operation of power systems. This paper presents a cost-based risk index approach for assessing the spinning reserve requirements in a power system. To that end, the performance of spinning reserve is classified in three types, namely, not-effective, partially-effective, and not-meeting-load. Then probability of each type and its consequences are subsequently computed and finally that the risk associated with any spinning reserve value is determined. It is shown that one might consider various spinning reserve values for an operating condition (randomly or using approaches proposed in literature), then calculate risks associated with each value, and finally use the calculated risk indices to determining the optimal level of spinning reserve. As an example, we have shown that in the studied network with 6600MW load, maintaining 240MW SR will increase cost of 1MW hour energy by $0.154 while the optimal value of 200MW SR will increase cost of 1MWhour energy by just $0.126. This paper initially focuses on providing a measure of the quality of an ex-ante specified spinning reserve, latter on the flowchart of using the proposed approach for determining optimal level of spinning reserve is presented. The proposed risk index can also be used for comparing different deterministic as well as probabilistic approaches presented in literature for spinning reserve requirements.

Latched Limit Strategy for Single-phase Synchronous Inverter for Realization of Designed Grid Forming Performance

Single-phase synchronous inverters (SSIs) with synthetic inertia connect to single-phase circuits and stabilize the grid. They also improve grid resilience by forming and operating an islanded single-phase microgrid when disasters disconnect the single-phase circuits from the bulk power system. Generally, voltage and current feedback controllers are implemented in grid-connected converters to track the output voltage to the voltage reference and protect themselves from overcurrent when the fault occurs. However, controllers with multiple feedback control loops in SSIs impair the grid stabilization performance depending on grid frequency variations. Without optimal parameter tuning according to grid conditions, they also cause instability of the controller during the islanding operation of a single-phase microgrid. This paper proposes a controller to realize the designed grid forming performance and avoid the above problems inherent in SSIs. The SSI with the proposed controller works as a grid forming inverter in a normal condition without the multiple feedback loops, stabilizing the grid and operating a single-phase microgrid stably. When an overcurrent is detected, the SSI shifts from a grid forming mode to a current control mode using a latched limit strategy to protect semiconductor devices from the overcurrent. Since the appropriate switching between the two modes is essential for realizing the designed performance of the SSI, the proposed controller employs a modified current-trip voltage-reset limit. Numerical simulations and experiments demonstrate that the proposed controller provides the designed performance in both normal and faulted conditions.

Transactive Energy System for Distribution Network Management: Procuring Residential Flexibility Services Under Dynamic Pricing

The formulation of dynamic pricing is one of the emerging solutions to guide residential demand for the benefits of the bulk power system. However, the schedule of residential demand in response to time-differentiated energy prices could cause congestions in distribution networks at both the lowest-price and highest-price time intervals. To enable the adoption of dynamic pricing, this work presents a novel framework to manage the constraints of distribution networks based on the concept of Transactive Energy System (TES). The TES-based framework produces incentives during network issues to unlock customers’ flexibility services to reschedule controllable assets (e.g., batteries). By running Home Energy Management Systems (HEMS), the flexibility of customers to modify schedules are quantified against predefined set of incentives. For each incentive, the amounts of net-demand change per customer are aggregated and submitted through aggregators to the Distribution System Operator (DSO) in the forms of both generation offers (reducing demand) and demand offers (increasing demand). The latter are crucial to cater for generation-driven network issues. The resulting aggregators’ staircase bidding curves are embedded to an advanced Optimal Power Flow (OPF) model to identify the successful offers to manage network constraints whilst minimizing incentives paid to aggregators. This allows defining incentives and quantities directly without extensive iterations between DSO and aggregators. The application of the framework to an urban 11kV feeder shows its effectiveness to manage congestions. However, the highly variations in dynamic prices increase the amounts of incentives particularly when flexibility services are requested at evening and night time intervals.

A Dynamic Behavior-Based Bulk Power System Event Signature Library With Empirical Clustering

The grid reinforcement, advanced grid stabilizing systems, and inverter-interfaced loads have varied power system dynamics. The changing trends of various dynamic phenomena need to be scrutinized to ensure future grid reliability. A dynamic behavior-based event signature library of phasor measurement unit (PMU) data has great potential to discover new and unprecedented event signatures. This paper presents an event signature library design that further defines more granular event categories within the major event categories (e.g., frequency, voltage, and oscillation events) provided by electric utilities and regional transmission organizations. The proposed library design embraces a supervised machine learning approach with a deep neural network (DNN) model and manually-generated labels. The input of the model uses representative PMUs that evidently express dominant event signatures. The performance of the event categorization module was evaluated, via information entropy, against labels generated automatically from clustering analyses. We applied the event signature library design to two years of over 1000 actual events in the bulk U.S. power system. The module obtains remarkable event discrimination capability.

Cascading Failure Mitigation Via Transmission Switching

After decades of research, cascading blackouts remain one of the unresolved challenges in the bulk power system operations. A new perspective for measuring the susceptibility of the system to cascading failures is clearly needed. The newly developed concept of system stress metrics may be able to provide new insights into this problem. The method measures stress as susceptibility to cascading failures by analyzing the network structure and electrical properties. This paper investigates the effectiveness of transmission switching in reducing the risk of cascading failures, measured in system stress metrics. Based on line-outage distribution factors, an algorithm is developed to identify and test the switching candidates quickly. A case study analyzing different stress metrics on the IEEE 118-bus test system is presented. The results show that transmission switching identified by our proposed algorithm could be used in preventive as well as corrective mechanisms to reduce the system's susceptibility to cascading failures. Contrary to the conventional operation wisdom that switching lines out of service jeopardizes reliability, our results suggest the opposite; system operators can often use transmission switching, when the system is under stress, as a tool to reduce the risk of cascading failures.

SMTD Co-Simulation Framework With HELICS for Future-Grid Analysis and Synthetic Measurement-Data Generation

The power grid is transforming with large amounts of distributed energy resource (DER) integration that is impacting the bulk power system planning and operations. Grid regulators have identified that traditional power system analysis techniques are challenged under the changing grid conditions. Transmission and distribution (T&amp;D) co-simulation is an effective methodology to accurately account for the changing power-grid. A scalable multitimescale T&amp;D (SMTD) co-simulation framework is developed with commercial transmission system solver that can handle large-scale system models, and distribution system solver that can model the distribution systems in detail with dynamic models of load and DER. In this article, PSS&#x002F;E and GridLAB-D are combined using a Python interface with Hierarchical Engine for Large-scale Infrastructure Co-Simulation software to enable T&amp;D co-simulation. This framework is scalable and parallel computing compatible that enables large-scale system simulation and adoption of T&amp;D co-simulation by the industry and utilities. The SMTD cosimulator is designed to integrate with existing system models and new ones. The article also highlights functional specifications for the T&amp;D co-simulation solvers and models along with providing the algorithms for the steady state, quasi-steady state, and dynamic T&amp;D co-simulation. In context of changing power grid, future power grid planning, validation of controls under critical contingencies and validation of various wide area monitoring and controls can effectively utilize the proposed framework that can capture the T&amp;D interactions accurately. The SMTD cosimulator can also be used to generate realistic synthetic measurement-data with noise and packet drop for uncommon grid events enabling development and validation of power system data analytics and controls.

A Framework for Coordinated Self-Assembly of Networked Microgrids Using Consensus Algorithms

With the rapidly increasing deployment of distributed energy resources (DERs), electric power systems across the world are moving towards more distributed designs and operations. While not every distributed device will be part of a microgrid, microgrids do offer solutions for scalability and interoperability, and for coordination with centralized utility control systems. The challenge is that the microgrids will be heterogenous with respect to ownership, operational objectives, resource mix, and control systems. Due to these variations within the population of microgrids, there will be significant challenges with coordinating their operations to achieve global objectives using existing centralized controls and optimizations. This paper presents a framework for the coordination of heterogeneous groups of microgrids using consensus algorithms. The framework enables the active engagement of utility and non-utility microgrids using a distributed architecture to support end-use loads during the loss of the bulk power system. Results from laboratory testing and preliminary implementations, as well as details of an ongoing operational deployment at the Electric Power Board of Chattanooga are presented in this paper.

Exploring the design space of PV-plus-battery system configurations under evolving grid conditions

In this study, we explore how the energy and capacity values of coupled systems comprising solar photovoltaic arrays and battery storage (PV-plus-battery systems) could evolve over time based on the evolution of the bulk power system. Using a price-taker model with simulated hourly energy and capacity prices projected from the present to 2050, we simulate the revenue-maximizing dispatch of a range of DC-coupled PV-plus-battery configurations in three locations in the United States. These configurations are defined by the inverter loading ratio (ILR, the ratio of the PV array capacity to the inverter capacity, which we vary from 1.4 to 2.6) and the battery-inverter ratio (BIR, the ratio of the battery power capacity to the inverter capacity, which we vary from 0.25 to 1.0). Based on each configuration’s total value, we estimate the breakeven costs needed to justify each incremental increase in ILR (holding BIR constant) or BIR (holding ILR constant). We find that, in a future with low-cost renewable energy technologies, PV-plus-battery system ILRs can be economically increased to around 2.0–2.4 at a BIR of 1.0, depending on solar resource. Our results indicate that a likely evolution of PV-plus-battery system design will be increasingly greater battery power capacity to mitigate the declining PV capacity value, which will, in turn, enable increasingly higher ILRs to further increase energy value. The extent to which PV-plus-systems will be deployed with increasingly higher ILRs depends primarily on whether PV cost declines outpace declining value and increasing curtailment over time.

The Effects of Climate Change on Interregional Electricity Market Dynamics on the U.S. West Coast

AbstractThe United States (U.S.) West Coast power system is strongly influenced by variability and extremes in air temperatures (which drive electricity demand) and streamflows (which control hydropower availability). As hydroclimate changes across the West Coast, a combination of forces may work in tandem to make its bulk power system more vulnerable to physical reliability issues and market price shocks. In particular, a warmer climate is expected to increase summer cooling (electricity) demands and shift the average timing of peak streamflow (hydropower production) away from summer to the spring and winter, depriving power systems of hydropower when it is needed the most. Here, we investigate how climate change could alter interregional electricity market dynamics on the West Coast, including the potential for hydroclimatic changes in one region (e.g., Pacific Northwest (PNW)) to “spill over” and cause price and reliability risks in another (e.g., California). We find that the most salient hydroclimatic risks for the PNW power system are changes in streamflow, while risks for the California system are driven primarily by changes in summer air temperatures, especially extreme heat events that increase peak system demand. Altered timing and amounts of hydropower production in the PNW do alter summer power deliveries into California but show relatively modest potential to impact prices and reliability there. Instead, our results suggest future extreme heat in California could exert a stronger influence on prices and reliability in the PNW, especially if California continues to rely on its northern neighbor for imported power to meet higher summer demands.