Power Grid Model Research Articles

On the conditions for safe connection to hub-cluster power grids

Purpose of this work is studying of the dynamics of a power grid model that results from the expansion of a highly centralized grid, i.e. a hub-cluster, by adding a small subgrid. The main attention is paid to the study of possible power grid operation regimes and their characteristics. Methods. Numerical simulation of power grid operation, the dynamics of which is described by the Kuramoto equations with inertia, is used. Results. Various power grid operation regimes and the boundaries of their existence in the parameter space are given. The main characteristics of these regimes, such as the probability of realization and the magnitude of oscillations of regime variables, are considered. The conditions for safe connection to hub-cluster power grids are obtained. Conclusion. The dynamics of power grid consisting of two subgrids and its operation regimes are considered. Based on the characteristics of these regimes, their safety for subgrids is determined. The results obtained made it possible to formulate conditions for a safe connection to hub-cluster power grids.

Evaluating power grid model hydropower feasibility with a river operations model

Production cost models (PCMs) simulate dispatch of generators across a large power grid and are used widely by planners to study the reliability of electricity supply. As energy systems transition away from the thermoelectric technologies that have traditionally balanced electricity supply and demand, hydropower and its representation in PCMs is of increasing importance. A limitation of PCMs applied to continental power grids with diverse generation portfolios is that hydropower generation is simulated without full consideration of complex river dynamics, leading to possible misrepresentation of grid flexibility and performance. In addition, data used in PCMs may reflect outdated operating policies. In this paper we propose a hydropower generation feasibility test for PCMs. The approach uses a detailed hydropower model to determine whether the hourly hydropower schedule from a PCM with simplified monthly parameterization can be attained after accounting for realistic river dynamics and operating policies, such as spill requirements and general water movement and balance through a cascade reservoir system. We perform this hydropower generation test for the ‘Big 10’ hydropower system on the Columbia River (part of the Western Interconnect of the United States), revealing 9% overestimation of available hydropower generation in a PCM solution in an average hydrologic year. Our evaluation provides insight on the cost and opportunities for better representing hydropower in PCMs.

Construction of Power Grid Stability Analysis System Based on Stochastic Process Theory

In recent years, the proportion of new energy power generation in the power supply has increased yearly. However, the random volatility generated by new energy generation poses a new challenge to the stability of the power system. In terms of stability analysis, the traditional methods based on the deterministic system can not fully describe the influence of random fluctuation. In this case, this paper introduces the power grid stability analysis method considering random influence. Based on the original model, this paper introduces the random fluctuation simulated by the Gaussian process, establishes the power grid model described by nonlinear stochastic differential equations, and gives the numerical solution format of the model with the help of the Euler method. Secondly, compared with the traditional method of quantifying the size of the escaping state of the system, this method considers the influence of the random variable on the stability of the system at the same time. Therefore, this paper establishes the stability analysis system of the power grid and further considers the influence of power grid topology and system parameters on system stability. By analyzing the Brass paradox, it is found that it is more reasonable to quantify the stability of the system with exit time. Finally, this paper uses the stability analysis system to study the stability of the high voltage power grid in Shandong Province and gives suggestions to improve the stability.

Multi-area parameter error identification for large power systems

Power grid model parameters may contain errors due to various reasons. Detecting and correcting parameter errors typically requires significant computational effort due to the size and complexity of the parameter database. While the normalized Lagrange multiplier (NLM) method can effectively detect, identify and correct parameter errors, its computational burden could rapidly grow with increasing system size. This paper addresses this issue by proposing a multi-area parameter error identification method. Each area has its own outlier detection tool for detecting the incorrect parameters and measurements within the area. On the other hand, due to the reduced redundancy at area boundaries, parameter errors on branches incident to boundary buses may not be detected. Such errors are subsequently detected by a coordination level estimator completing the system-wide parameter detection procedure. Performance of the developed method is demonstrated using the IEEE 118-bus and 2000-bus Texas synthetic systems.

Joint Optimal Scheduling of Renewable Energy Regional Power Grid With Energy Storage System and Concentrated Solar Power Plant

Under the path of global low-carbon development, increasing the proportion of renewable energy in the power grid will become the main goal in the future. But, it will also aggravate the problem of wind and solar curtailment. A joint optimal scheduling model of a renewable energy regional power grid with an energy storage system and concentrated solar power plant is proposed in this study. The proposed model takes the lowest comprehensive operation cost of the power grid as the optimization goal and considers various constraints of concentrated solar power plants, energy storage systems, thermal power units, wind power, and photovoltaic power generation. Finally, a modified IEEE 9-bus system is used to verify the validity. The results show that the model can effectively improve the system node voltage, promote the accommodation of wind and solar power, and alleviate the peak shaving of thermal power units under the premise of optimal economy pressure.

Reconstruction of cascading failures in dynamical models of power grids

Abstract In this article, we propose a method to reconstruct the active links of a power network described by a second-order Kuramoto model and subject to dynamically induced cascading failures. Starting from the assumption (realistic for power grids) that the structure of the network is known, our method reconstructs the active links from the evolution of the relevant dynamical quantities of the nodes of the system, that is, the node phases and angular velocities. We find that, to reconstruct the temporal sequence of the faults, it is crucial to use time series with a small number of samples, as the observation window should be smaller than the temporal distance between subsequent events. This requirement is in contrast with the need of using larger sets of data in the presence of noise, such that the number of samples to feed in the algorithm has to be selected as a trade-off between the prediction error and temporal resolution of the active link reconstruction.

Mechanisms Regulating Energy Homeostasis in Plant Cells and Their Potential to Inspire Electrical Microgrids Models.

In this paper, the main features of systems that are required to flexibly modulate energy states of plant cells in response to environmental fluctuations are surveyed and summarized. Plant cells possess multiple sources (chloroplasts and mitochondria) to produce energy that is consumed to drive many processes, as well as mechanisms that adequately provide energy to the processes with high priority depending on the conditions. Such energy-providing systems are tightly linked to sensors that monitor the status of the environment and inside the cell. In addition, plants possess the ability to efficiently store and transport energy both at the cell level and at a higher level. Furthermore, these systems can finely tune the various mechanisms of energy homeostasis in plant cells in response to the changes in environment, also assuring the plant survival under adverse environmental conditions. Electrical power systems are prone to the effects of environmental changes as well; furthermore, they are required to be increasingly resilient to the threats of extreme natural events caused, for example, by climate changes, outages, and/or external deliberate attacks. Starting from this consideration, similarities between energy-related processes in plant cells and electrical power grids are identified, and the potential of mechanisms regulating energy homeostasis in plant cells to inspire the definition of new models of flexible and resilient electrical power grids, particularly microgrids, is delineated. The main contribution of this review is surveying energy regulatory mechanisms in detail as a reference and helping readers to find useful information for their work in this research field.

Load-Frequency Control of Three-Area Interconnected Power Systems with Renewable Energy Sources Using Novel PSO~PID-Like Fuzzy Logic Controllers

Modern era power systems may include not only traditional primary energy sources like hydro or thermal energy, but also a variety of Renewable Energy (RE) sources such as solar and/or wind power. This leads to the complexity of the electrical networks related to their design and construction as well as system stability and control issues. Considered to be one of the most crucial control issues, Load Frequency Control (LFC), must be continuously improved in order to ensure the control goals. For an interconnected power system, the control purposes are to maintain the net frequency at nominal value, e.g. 50 or 60Hz as well as to ensure that tie-line power flows are stable at scheduled values. This work proposes a novel LFC strategy applying Particle Swarm Optimization (PSO) ~ PID – like fuzzy logic–based controllers. PSO is one of the most effective optimization techniques. It is used to optimally determine four scaling factors for each LFC proposed in this study. A three-area power network consisting of a hydraulic station, a non-reheat plant, and a reheat unit along with RE sources such as wind and solar power are taken into consideration. The control performance of the proposed control strategy is compared to those of existing controllers, i.e. Genetic Algorithm (GA), Bacteria Foraging Optimization Algorithm (BFOA), Fractional Order-PID (FPID), and fuzzy logic-based PI controllers for the same interconnected power grid model with various case studies of load changes along with nonlinearities and different RE source conditions. Simulation results implemented in MATLAB/Simulink demonstrate the feasibility and applicability of the proposed control strategy.

ВИКОРИСТАННЯ ПРОГРАМНОГО ЗАБЕЗПЕЧЕННЯ ДЛЯ ПІДВИЩЕННЯ ЕФЕКТИВНОСТІ МОДЕЛЮВАННЯ ЕНЕРГЕТИЧНИХ МЕРЕЖ

The article is devoted to the topical issue of power grid modeling. The article discusses positive and negative features of simulation programs. Particular attention is paid to the principles of the programs. Such programs as PSS®SINCAL from Siemens; ETAP from Operation Technology and PowerFactory from DIgSILENT GmbH are considered in the article. The PSS®SINCAL software specializes in designing networks from low to ultra-high voltage classes, in symmetrical and non-symmetrical modes of operation, takes into account the installation possibilities of compensating devices and gives recommendations for their installation locations. Basic models enabling mode calculations and shortcircuit calculations as well as simulation of electromagnetic transients are used as the basis of the PSS®SINCAL software. The basic modules include steady state calculations, calculations of short circuit currents, harmonics, system stability and electromagnetic transients. Particular attention is paid to the optimization and planning module, namely reactive power optimization. The module of reactive power optimization in PSS®SINCAL offers methods of optimizing existing equipment by finding the best switching points for reactive power compensation. ETAP software specializes in electrical network and power transmission design. ETAP Grid™ connects network design with detailed substation models, SCADA systems, and real-time transmission network management. This paper covers only 2 modules of ETAP software, namely transmission and distribution modules. PowerFactory captures the full range of functionality from standard features to highly sophisticated and advanced applications, including wind power, distributed generation, real-time modeling, and performance monitoring for testing of surveillance systems. This article reviews only 2 modules of the PowerFactory software, namely the electrical power transmission and distribution modules. The paper reviews the programs and concludes that Siemens' PSS®SINCAL software would be the most successful solution for modeling electric grids and accounting for the effects of compensating devices on voltage levels in electric grids.

Power Balance Partition Control Based on Topology Characteristics of Multi-Source Energy Storage Nodes

Aiming at the power balance control of multi-source energy storage grid in the case of a high proportion of new energy grid connection. In this article, a power grid dynamic partition method based on the Markov energy field principle and a priori knowledge model is proposed. Combined with the coordinated dispatching of power grid source-load, a two-layer power balance partition control model based on the topological characteristics of multi-source energy storage nodes is established. First, in the upper-layer model, the energy homogenization method of multi-source energy storage nodes is studied, and the Markov energy field model of power grid node partition based on energy interaction constraints between nodes is established to partition the power grid initially. Combined with the prior model of node dynamic partition, the initial partition is dynamically optimized to realize the dynamic partition of the multi-source energy storage grid. Then, in the lower-layer model, the source-load coordinated dispatching model in the power grid partition area is established to realize the dynamic partition control of the power grid. Finally, based on the real operation data of a northeast power grid and IEEE39 node system, a dynamic partition power control simulation model of a multi-source energy storage power grid is established. The simulation results and analysis show that the dynamic partition power control strategy proposed in this article can effectively improve the regulation ability and economy of the power grid.

Integration of water electrolysis facilities in power grids: A case study in northern Germany

• Power grid and alkaline water electrolysis models have been coupled through data exchange. • Average power line utilization as indicator of grid impacts. • Daily-constrained hydrogen production yields low production costs and minimum grid congestion. This work presents a study of the effects that integration of electrolysis facilities for Power-to-X processes have on the power grid. The novel simulation setup combines a high-resolution grid optimization model and a detailed scheduling model for alkaline water electrolysis. The utilization and congestion of power lines in northern Germany is investigated by setting different installed capacities and production strategies of the electrolysis facility. For electrolysis capacities up to 300 MW (∼50 ktH 2 /a), local impacts on the grid are observed, while higher capacities cause supra-regional impacts. Thereby, impacts are defined as deviations from the average line utilization greater than 5%. In addition, the minimum line congestion is determined to coincide with the daily-constrained production strategy of the electrolysis facility. Our result show a good compromise for the integrated grid-facility operation with minimum production cost and reduced impact on the grid.

A network-based structure-preserving dynamical model for the study of cascading failures in power grids

In this work we show that simple classic models of power grids, albeit frequently utilized in many applications, may not be reliable for investigating cascading failures problems. For this purpose, we develop a novel model, based on a structure-preserving approach, to obtain a network-based description of a power grid, where nodes correspond to generators and buses, while the links correspond to the physical lines connecting them. In addition, we also consider classic voltage and frequency protection mechanisms for lines and buses. Considering the Italian power grid as a case study of interest, we then investigate the propagation of an initial failure of any line of the power system, and compare the predicted impact of the failure according to different assumptions in the model such as the presence or absence of protection mechanisms and a simplified description of the system dynamics. In particular, it can be observed that more realistic models are crucial to determine the size of the cascading failure, as well as the sequence of links that may be involved in the cascade.

Assessing green energy growth in Nepal with a hydropower-hydrogen integrated power grid model

The involvement of green hydrogen in energy transformation is getting global attention. This assessment examines the hydrogen production and its utilization potential in one of the hydropower-rich regions, Nepal under various demand growth and technology intervention scenarios by developing a power grid model of 52 nodes and 68 transmission lines operating at an hourly time-step. The model incorporates a grid-connected hydrogen storage system as well as charging stations for electric and hydrogen vehicles. The least-costly pathways for power grid expansion at the nodal and provincial levels are identified through optimization. The results show that 32 GW of installed capacity is required to meet domestic electricity demand and 14 GW more hydropower should be exploited to completely decarbonize the transport sector by 2050. For maintaining 50% shares of hydrogen vehicle in the transport sector and meet government electricity export targets, Nepal requires 5.7 GW, 12 GW and 23 GW of the additional electrolyzer, hydrogen storage tanks and storage-based hydropower capacities respectively. For a given electricity demand, introducing hydrogen systems can reduce the capacity requirements of hydro storage by storing surplus power generated from pondage run-of-the-river and run-of-the-river hydropower during the rainy season and using it in the dry season.

Method for Day-head Operations of a Large Hydropower Plant Considering Peak-shaving Demands of Multiple Provincial Power Grids

Large hydropower plants in China are usually required to transmit power to multiple provinces and meet their complex peak-shaving demands. How to model and solve this problem is challenging. Based on a Hydropower Project in southwest China, this study proposed a method for day-head operations of large hydropower plant considering peak-shaving demands of two provincial power grids. A short-term peak-shaving model for multiple power grids is constructed, which takes the minimum sum of the squares of the remaining loads of each power grid. This model considers complex constraints such as the operation of hydropower plants and the requirements of power transmission. The multi-objective optimization is transformed into a single-objective problem and solved by a group search algorithm based on the genetic algorithm. Two cases which respectively consider different loads and objective weights are presented to test the model. It is found that the large hydropower plant can simultaneously respond to different peak loads for multiple power grids. It should be also noted that different objective weights may have a significant effect on peak-shaving results.

Photovoltaic–electric vehicles participating in bidding model of power grid that considers carbon emissions

The synergy of clean energy and electric vehicles (EVs) is highly relevant in achieving low-carbon development. To promote the coordinated development of EVs and photovoltaics (PV) under the background of open power selling, a PV–EV bidding model that considers carbon emissions based on the distributed storage and smart contract technology of a blockchain is proposed in this study. This model aims to provide economic benefits to market players, ensure the safety and environmental protection of power grid operations, and integrate the ladder-type carbon emission trading mechanism. Then, it divides the electricity market into the electricity sales layer, i.e., active distribution networks (ADNs) and PV systems, and the electricity purchase layer, i.e., EVs. Smart contracts are signed with the agent layer, i.e., charging stations. The improved particle swarm optimization algorithm is used to solve the price and power of PV systems and EVs in the optimal contract, and the revenue of PV systems and EVs can be increased by over 35%. Moreover, the orderly charging and discharging of EVs is coordinated with the characteristics of the daily power generation and evening load peaks of PV systems. The proposed model can effectively provide an optimal scheduling scheme for peak load shifting and valley filling while reducing the carbon emissions of ADNs. It also promotes the local consumption of PV.

Partial Y-Bus Factorization Algorithm for Power System Dynamic Equivalents

This paper presents a partial Y-bus factorization algorithm to reduce the size of a power system model for transient stability analysis. In the proposed approach, steady-state operating conditions for dynamic equivalents are maintained using the traditional Ward admittance method. Fictitious generators are attached at boundary buses to preserve transient behavior following a disturbance. The equivalent dynamic effects from eliminated generators can be maintained by choosing appropriate dynamic parameters of fictitious generators, including machine inertia, transient reactance, and the damping coefficient. Parameters are determined using the idea that the contributions from external generators mostly depend on the network configuration and impedance characterized by the Y-bus matrix. The fictitious generators’ dynamic parameters are determined by conducting partial Y-bus factorization on dynamic parameter matrices. The proposed method’s performance is validated by conducting case studies with the IEEE 118-bus system and a 10,000 synthetic western U.S. power grid model and comparing simulation outcomes between the full system and reduced equivalent models. Simulation comparisons show that the equivalent model maintains high accuracy. The proposed method is promising alternative solution for power system dynamic equivalents.

Synergistic use of intrusive and non-intrusive model order reduction techniques for dynamical power grids

This manuscript combines the recently developed nonlinear moment-matching (NLMM) technique with dynamic mode decomposition (DMD) to obtain a simulation-free reduction framework for power systems. Unlike the conventional model reduction methods for power systems, where the external area is linearized, we consider the nonlinear effective network (EN) and the synchronous motor (SM) power grid models. First, the reduced system is constructed from the solution of the underlying approximate Sylvester equation by exciting the system with user-defined inputs from a representative exogenous system. Then, a non-intrusive reduction is performed using DMD to approximate the nonlinear function via Koopman modes in an equation-free manner. The advantage is that a “simulation-free” nonlinear model order reduction framework is obtained to approximate the response of the large-scale power grid models. Finally, we substantiate our observations using numerical simulations of reduced EN and SM models of the IEEE 118 and IEEE 300 bus systems for realistic fault scenarios. Results show that the overall CPU times of the reduced-order models are lowered to half as compared to the original models while maintaining the fidelity. The results are also compared with POD-DEIM for reference.

Inferring Topology of Networks With Hidden Dynamic Variables

Inferring the network topology from the dynamics of interacting units constitutes a topical challenge that drives research on its theory and applications across physics, mathematics, biology, and engineering. Most current inference methods rely on time series data recorded from all dynamical variables in the system. In applications, often only some of these time series are accessible, while other units or variables of all units are hidden, i.e. inaccessible or unobserved. For instance, in AC power grids, frequency measurements often are easily available whereas determining the phase relations among the oscillatory units requires much more effort. Here, we propose a network inference method that allows to reconstruct the full network topology even if all units exhibit hidden variables.We illustrate the approach in terms of a basic AC power grid model with two variables per node, the local phase angle and the local instantaneous frequency. Based solely on frequency measurements, we infer the underlying network topology as well as the relative phases that are inaccessible to measurement. The presented method may be enhanced to include systems with more complex coupling functions and additional parameters such as losses in power grid models. These results may thus contribute towards developing and applying novel network inference approaches in engineering, biology and beyond.

Model reduction for a power grid model

<p style='text-indent:20px;'>We examine the complexity of constructing reduced order models for subsets of the variables needed to represent the state of the power grid. In particular, we apply model reduction techniques to the DeMarco-Zheng power grid model. We show that due to the oscillating nature of the solutions and the absence of timescale separation between resolved and unresolved variables, the construction of accurate reduced models becomes highly non-trivial because one has to account for long memory effects. In addition, we show that a reduced model that includes even a short memory is drastically better than a memoryless model.</p>

Economic Dispatch Methods for Smart Grid Based on Improved SPEA2 and Improved NSGA2

The severity of the ongoing environmental crisis has prompted the development of renewable energy generation and smart grids integration. The access of enewable energy makes the economic dispatching of smart grid complicated. Therefore, the economic dispatching model for smart grid is very necessary. This paper presents an economic dispatching model of smart power grid, which considers both economy and pollution emission. The smart grid model used for the simulation is construced of wind energy, solar energy, fuel cell, and thermal power, and the use of fuel cell enables the smart grid to achieve multi-energy complementar. To overcome the defect of the traditional centralized communication methods, which are prone to communication jams, this paper adopts a multi-agent inform ation exchange method to improve the stability and efficiency. In terms of the solution method for this model, this paper proposes Improved Strength Pareto Evolutionary Algorithm 2(ISPEA2) and Improved Non-dominated Sorting Genetic Algorithm 2(INSGA2) that solves the economic dispatch problem of a smart grid. The strength Pareto evolutionary algorithm 2(SPEA2),non-dominated sorting genetic algorithm 2(NSGA2) and the improved algorithms are simultaneously applied to the proposed smart grid model for economic dispatching simulation. The simulation results show that ISPEA2 and INSGA2 are effective. ISPEA2 and INSGA2 have shown improvements over SPEA2 and NSGA2 in accuracy or running times.