Power System Model Research Articles

An Open-Source Julia Package for RMS Time-Domain Simulations of Power Systems

This paper presents RMSPowerSims.jl, an open-source Julia package for the time-domain simulation of power systems. The package is designed to be used in conjunction with PowerModels.jl, a widely used Julia package for power system optimization. RMSPowerSims.jl provides a framework for the simulation of power systems in the time domain, allowing for the study of transient stability, frequency stability, and other dynamic phenomena. The package is designed to be intuitive and flexible, allowing users to easily define custom models for network components and disturbances, while also providing a range of pre-constructed models for common power system components. RMSPowerSims.jl simplifies the process of performing RMS simulations on power system models developed using the PowerModels.jl ecosystem, and provides an easy-to-use modeling that reduces the barrier to entry for new users wishing to perform RMS simulations. The accuracy of the package is verified against DIgSILENT PowerFactory for short-circuit and load-increase disturbances, using the New England 39-bus system. The active power generation delivered by several generators in the network, and the voltage magnitudes of selected busbars are analyzed and noted to be in close agreement with those obtained using PowerFactory. The computational performance of the package is compared to that of PowerFactory and is found to be comparable for load-step simulations; however, PowerFactory is found to be considerably faster for short-circuit simulations. As computational performance is not a priority at this stage of development, this is expected, and speed optimization is planned for future work. RMSPowerSims.jl is available under an open-source license and can be downloaded from GitHub.

Frequency-Voltage-var Function for Active Front-end VFD on Oil and Gas Platforms with Offshore Wind Generation

Renewable energy resources emerge as a sustainable alternative to augmenting the energy supply of floating production storage and offloading (FPSO) platforms. However, the increased generation at FPSO based on converter-interfaced energy decreases the system-equivalent inertia constant, which becomes more susceptible to frequency deviations. This paper proposes and evaluates the combined frequency-voltage-var control performance to mitigate frequency variation in a typical FPSO unit with penetration of floating wind energy generation. The control functions are communication-free and embedded in the active front-end variable frequency drives (AFE-VFDs), which are installed on the FPSO and have the primary function of controlling the speed of water injection pumps. The FPSO electrical power system model is developed in MATLAB/Simulink®. Comparative results obtained from the AFE-VFD equipped with volt-var, freq-var, and combined freq-volt-var functions are shown to highlight the proposed solution merits. The results have shown a conflicting behavior with the frequency and voltage deviation improvement associated with absorption and injection of reactive power, respectively. Accordingly, the frequency-volt-var prioritizes frequency deviations during heavy transient events and voltage deviations during regular operation.

RlaNet: A Residual Convolution Nested Long-Short-Term Memory Model with an Attention Mechanism for Wind Turbine Fault Diagnosis

This paper proposes a new fault diagnosis model for wind power systems called residual convolution nested long short-term memory network with an attention mechanism (rlaNet). The method first preprocesses the SCADA data through feature engineering, uses the Hermite interpolation method to handle missing data, and uses the mutual information-based dimensionality reduction technique to improve data quality and eliminate redundant information. rlaNet combines residual networks and nested long short-term memory networks to replace traditional convolutional neural networks and standard long short-term memory architectures, thereby improving feature extraction and ensuring the abstractness and depth of the extracted features. In addition, the model emphasizes the weighted learning of spatiotemporal features in the input data, enhances the focus on key features, and improves training efficiency. Experimental results show that rlaNet achieves an accuracy of more than 90% in wind turbine fault diagnosis, showing good robustness. Furthermore, noise simulation experiments verify the model’s resistance to interference, providing a reliable solution for wind turbine fault diagnosis under complex operating conditions.

The effects of fair allocation principles on energy system model designs

Abstract What constitutes socially just or unjust energy systems or transitions can be derived from the philosophy and theories of justice. Assessments of distributive justice and utilising them in modelling lead to great differences based on which justice principles are applied. From the limited research so far published in the intersection between energy systems modelling and justice, we find that comparisons between the two principles of utilitarianism and egalitarianism dominate in assessments of distributive justice, with the latter most often considered representing a 'just energy system'. The lack of recognition of alternative and equally valid principles of justice, resting on e.g. capabilities, responsibilities and/or opportunities, leads to a narrow understanding of justice that fails to align with the views of different individuals, stakeholders and societies. More importantly, it can lead to the unjust design of future energy systems and energy systems analysis. 
 
In this work, we contribute to the growing amount of research on distributive justice in energy systems modelling by assessing the implications of different philosophical views on justice on modelling results. Through a modelling exercise with a power system model for Europe (highRES), we explore different designs of a future (2050) net-zero European electricity system, and its distributional implications based on the application of different justice principles. In addition to the utilitarian and egalitarian approach, we include, among others, principles of 'polluters pay' and 'ability-to-pay', which take historical contributions of greenhouse gas emissions and the socio-economic conditions of a region into account. 
 
We find that fair distributions of electricity generating infrastructure look significantly different depending on the justice principles applied. The results may stimulate a greater discussion among researchers and policymakers on the implications of different constructions of justice in modelling, expansion of approaches, and demonstrate the importance of transparency and assumptions when communicating such results.

A two-stage bi-level electricity-carbon coordinated optimization model for China's coal-fired power system considering variable renewable energy bidding

With China's grid-connected large-scale variable renewable energy, coal-fired power system is progressively changing from being the main supplier of electric energy to providing flexibility services. The coal-fired power system must increase operating efficiency during this transition process by considering the technical characteristics of various coal-fired power units. Additionally, the trading strategies of coal-fired power units in the electricity-carbon market are impacted differently depending on the extent of VRE penetration. This paper innovatively considers these two factors and proposes a two-stage bi-level clearing model in electricity-carbon joint market to coordinate the synergistic development of variable renewable energy and coal-fired power. The upper level of the model aims to maximize the total profits of the coal-fired power system and variable renewable energy units, while the lower level of the model minimizes the total purchasing costs. Coal-fired power units and variable renewable energy units compete to sell electric energy, with the latter buying peaking regulation from the former. The research results indicate that the proposed model can significantly reduce 66.79 % carbon emissions, increase 33.96 % non-fossil variable renewable energy integration and optimize the generation structure of coal-fired power system.

Hybrid solar and hydrogen energy system 0-D model for off-grid sustainable power system: A case in Italy

Off-grid solar systems are one of the most promising solutions for achieving complete grid independence. However, the storage of large amounts of energy produced in the summer through solar panels becomes crucial to reach this goal and hydrogen, as a zero-CO2 energy carrier, could play a pivotal role. This paper presents a case study on the integration and simulation of solar energy and hydrogen technologies in an off-grid energy plant for a teaching buildings complex in Italy. A 0-D virtual energy plant model has been developed aimed at estimating the net energy production and hydrogen consumption/production rates using different inputs of irradiance (monthly average, daily) and energy demand (constant and variable daily consumption levels) in the buildings. The outcome of the analysis identifies the most convenient configuration of the plant in terms of sizing and device interactions for achieving complete grid independence, and the impact of different inputs on the plant performance.

Investments in green hydrogen as a flexibility source for the European power system by 2050: Does it pay off?

The European Union aims to deploy a high share of renewable energy sources in Europe’s power system by 2050. Large-scale intermittent wind and solar power production requires flexibility to ensure an adequate supply–demand balance. Green hydrogen (GH) can increase power systems’ flexibility and decrease renewable energy production’s curtailment. However, investing in GH is costly and dependent on electricity prices, which are important for operational costs in electrolysis. Moreover, the use of GH for power system flexibility might not be economically viable if there is no hydrogen demand from the hydrogen market. If so, questions would arise as to, what would be the incentives to introduce GH as a source of flexibility in the power system, and how would electrolyzer costs, hydrogen demand, and other factors affect the economic viability of GH usage for power system flexibility. The paper implements a European power system model formulated as a stochastic program to address these questions. The authors use the model to compare various instances with hydrogen in the power system to a no-hydrogen instance. The results indicate that by 2050 deployment of approximately 140 GW of GH will pay off investments and make the technology economically viable. We find that the price of hydrogen is estimated to be around €30/MWh.

Transient behavior of pumped storage-wind hybrid power system under grid-connected operation condition

The large-scale grid connection of renewable energy represented by wind power threatens the safe and stable operation of electric system. The vigorous development pumped storage power station (PSPS) is a global consensus to support the grid-connected of renewable energy. This paper investigates the transient behavior of pumped storage-wind (PSW) hybrid power system under grid-connected operation condition (GCOC). Firstly, a model of PSW hybrid power system under GCOC is constructed. The stable domain is determined according to Hopf bifurcation theory. The influence of system parameters on the stability of PSW hybrid power system under GCOC is analyzed. A synergetic control strategy is designed to improve the dynamic performance of the system. Then, the mechanism of multi-time-scale dynamic response is revealed. Finally, the transient behavior of PSPS under different application scenarios and the interaction between PSPS and wind power station (WPS) are studied. The results show that the stability of PSW hybrid power system under GCOC can be judged by stable domain. The designed synergetic control strategy can improve the dynamic performance of the system. The dynamic response is composed of three oscillations with different frequencies, namely, mass oscillation at low frequency, water hammer oscillation at medium frequency, and electrical oscillation at high frequency. The principal oscillation is caused by water hammer. The interaction between PSPS and WPS has a significant effect on the transient behavior. By adjusting the interaction between PSPS and WPS, the system can absorb more wind power while ensuring safe and stable operation, which can increase profits and avoid unnecessary operation oscillations. The analytical methods and results presented in this paper are of great significance for improving the ability of power grid to accept renewable energy.

Dynamic Modeling of Distribution Power Systems with Renewable Generation for Stability Analysis

This paper presents a comprehensive study on the dynamic modeling of distribution power systems with a focus on the integration of renewable energy sources (RESs) for stability analysis. Our research delves into the static and dynamic behavior of distribution systems, emphasizing the need for enhanced load modeling to mitigate planning and operational uncertainties. Using MATLAB/Simulink®, we simulate four distinct study cases characterized by varying load types and levels of distributed generation (DG), particularly solar PV, under both balanced and unbalanced conditions. Our findings highlight the critical role of DG in influencing voltage stability, revealing that deviations in voltage and current during grid imbalances remain within acceptable limits. The study underscores the importance of DG-based inverters in maintaining grid stability through reactive power support and sets the stage for future research on microgrid simulations and battery storage integration to further enhance system stability and performance.

Complementary Analysis and Performance Improvement of a Hydro-Wind Hybrid Power System

Hydropower as a flexible regulation resource is a rare choice to suppress the ever-increasing penetration of wind power in electrical power systems. The complementary characteristics and performance improvement of a hydro–wind hybrid power system based on a mathematical model of the hybrid power system is studied in this paper. This established model takes into account the stochastic variation in wind speeds in the wind power subsystem and the hydraulic–mechanical–electrical coupling characteristics of the hydropower subsystem. The complementary analysis is conducted based on the evaluation variables outputted by the established model, such as the wind power, hydro-regulation power, hydraulic power, and frequency. To make full use of the regulation capability of the hydropower system, the optimization of parameter settings is also carried out to improve complementary performances of the hybrid power system. The results from the complementary analysis show the detailed characteristics of hydro–wind coordinated operation under different types of real wind speeds. Here, 95% of installed hydro-capacity is used to complement the power shortage of the intermittent wind energy under the low wind speed. Alternatively, only around 66% of the installed hydro-capacity can be utilized to cope with the fluctuation in wind power under the medium and high wind speeds before the optimization of parameter settings. The recommended values and change rules of the control, hydraulic, and electrical parameters for the hydropower system are subsequently revealed from the analysis of parameter settings to contribute to a stable and safe hybrid power system. The results show that the optimized parameter can increase the maximal regulating capacity of the hydropower system by nearly 9 MW, approximately a sixth of the total installed hydropower capacity. The method and results obtained in this paper provide theoretical and technical guidance for the safe and economical operation of power stations.

Rolling planning model for high proportion renewable energy generation power system considering frequency security constraints

In this paper, a rolling planning model for high proportion renewable energy generation power systems is proposed, considering frequency security constraints, to address the frequency stability challenges posed by increased integration of wind and solar energy into the power grid under the “double carbon” goal. First, this study establishes a frequency response model for a thermal generation unit (TGU) and analyzes the impact of the high proportion of renewable energy on system frequency stability. Subsequently, a dynamic frequency security constraint is formulated, which can be used in generation planning to address the frequency issues. Second, a bi-level rolling planning model for high proportion renewable energy generation power systems considering dynamic frequency security constraints is established. The upper level focuses on investment decisions. The lower level incorporates frequency security constraints into the operational simulation to guarantee the frequency stability of the power system when making decisions on the size of newly built TGUs annually. Finally, case studies are conducted to demonstrate the validity and effectiveness of the proposed rolling planning model.

Stability Studies of Grid-Forming and Grid-Following Inverter Penetrated Systems With Different External Power System Models

Stability Studies of Grid-Forming and Grid-Following Inverter Penetrated Systems With Different External Power System Models

A Bi-Level Peak Regulation Optimization Model for Power Systems Considering Ramping Capability and Demand Response

In the context of constructing new power systems, the intermittency and volatility of high-penetration renewable generation pose new challenges to the stability and secure operation of power systems. Enhancing the ramping capability of power systems has become a crucial measure for addressing these challenges. Therefore, this paper proposes a bi-level peak regulation optimization model for power systems considering ramping capability and demand response, aiming to mitigate the challenges that the uncertainty and volatility of renewable energy generation impose on power system operations. Firstly, the upper-level model focuses on minimizing the ramping demand caused by the uncertainty, taking into account concerned constraints such as the constraint of price-guided demand response, the constraint of satisfaction with electricity usage patterns, and the constraint of cost satisfaction. By solving the upper-level model, the ramping demand of the power system can be reduced. Secondly, the lower-level model aims to minimize the overall cost of the power system, considering constraints such as power balance constraints, power flow constraints, ramping capability constraints of thermal power units, stepwise ramp rate calculation constraints, and constraints of carbon capture units. Based on the ramping demand obtained by solving the upper-level model, the outputs of the generation units are optimized to reduce operation cost of power systems. Finally, the proposed peak regulation optimization model is verified through simulation based on the IEEE 39-bus system. The results indicate that the proposed model, which incorporates ramping capability and demand response, effectively reduces the comprehensive operational cost of the power system.

China's provincial power decarbonization transition in a carbon neutral vision

The power sector plays a crucial role in achieving the China's carbon neutrality target. However, there remain knowledge gaps regarding provincial emission reduction efforts toward carbon neutrality and the impact of carbon flows embodied in electricity transmissions. This study built a modeling framework, linking a bottom-up multi-regional power system model and Quasi-Input-Output approach, to investigate the provincial-level power system transition. Multiple combined scenarios based on shared socio-economic developments and different carbon mitigation policies were designed for a comprehensive assessment. Results indicates that the transition of the power system by 2060, under various scenarios, necessitates 7–7.8 TW of wind and solar photovoltaic power, 4810–6309 TWh of electricity transmissions, and 140–262 GW of coal power retrofits. Notably, carbon emission flows will accumulatively reach 12.7–18.7 Gt from 2020 to 2060. Inner Mongolia will bear a cumulative of more than 5 Gt of carbon flows from North China. When considering the indirect emissions, load centers such as Shandong will have higher peak emissions, and Shandong will replace Inner Mongolia as the largest emitter province. In addition, provincial emission factors under the influence of complex electricity transmissions and carbon flows are estimated.

Minimum Risk Quantification Method for Error Threshold of Wind Farm Equivalent Model Based on Bayes Discriminant Criterion

The error threshold is the cornerstone to balance the mathematical complexity and simulation speed of wind farm (WF) equivalent models, and can promote the standardization process of equivalent methodology. Due to differences in power system conditions and model evaluation standards in different countries, the form and indexes of error thresholds of WF equivalent models have not been unified yet. This paper proposes a theoretical method for quantifying the minimum risk of error threshold of WF equivalent models based on the Bayes discriminant criterion. Firstly, the Euclidean errors of WF equivalent models in different periods are quantified, and the probability density distributions of the errors are fitted by kernel density estimation. Secondly, the real-time weighted prior probability algorithm is used to obtain the prior probability of a valid WF equivalent model, and the different losses caused by the missed judgment and misjudgment of the model validity to power systems are taken into account. Thirdly, the minimum risk quantification model of error threshold is established based on the Bayes discriminant criterion, and the feasibility of the proposed method is verified by an actual WF with numerical examples. Compared with the existing error thresholds, the proposed error threshold can more quickly and accurately determine the validity of WF equivalent models.

Exploring a Dynamic Homotopy Technique to Enhance the Convergence of Classical Power Flow Iterative Solvers in Ill-Conditioned Power System Models

This paper presents a dynamic homotopy technique that can be used to calculate a preliminary result for a power flow problem (PFP). This result can then be used as an initial estimate to efficiently solve the PFP using either the classical Newton-Raphson (NR) method or its fast decoupled version (FDXB) while still maintaining high accuracy. The preliminary stage for the dynamic homotopy problem is formulated and solved by employing integration techniques, where implicit and explicit schemes are studied. The dynamic problem assumes an initial condition that coincides with the initial estimate for a traditional iterative method such as NR. In this sense, the initial guess for the FPF is adequately set as a flat start, which is a starting for the case when this initialization is of difficult assignment for convergence. The static homotopy method requires a complete solution of a PFP per homotopy pathway point, while the dynamic homotopy is based on numerical integration methods. This approach can require only one LU factorization at each point of the pathway. Allocating these points properly helps avoid several PFP resolutions to build the pathway. The hybrid technique was evaluated for large-scale systems with poor conditioning, such as a 109,272-bus model and other test systems under stressed conditions. A scheme based on the implicit backward Euler scheme demonstrated the best performance among other numerical solvers studied. It provided reliable partial results for the dynamic homotopy problem, which proved to be suitable for achieving fast and highly accurate solutions using both the NR and FDXB solvers.

Clustering of Electric Power Systems into Reliability Zones in Adequacy Assessment. Part 2

The article presents an analysis of clustering methods in relation to the problem of the formation of energy calculation models (ECM) of electric power systems (EPS). Classical clustering methods are considered, such as: the k-means method, the shortest path method, as well as methods for detecting communities in graphs according to given features, which are the most suitable for solving the problem. Based on the analysis, it was found that for graph clustering, the most adequate result can be obtained by applying the Leiden method. The experimental part of the article presents the results of applying the Leiden method for the formation of the ECM of the unified energy system of Siberia.

Inferring local social cost from renewable zoning decisions. Evidence from Lower Austria’s wind power zoning

Large infrastructures, such as wind turbines, may adversely affect their environment, so their deployment is often regulated. These regulations are frequently based on a dichotomy between areas considered feasible or infeasible areas for infrastructure deployment. To overcome the inability of such a binary distinction to adequately represent the involved economic trade-offs between, but also within feasible and infeasible areas, we establish a discrete choice framework to elicit social preferences implicit in Lower Austria’s wind power zoning and generate comprehensive estimates of local social costs in high spatial resolution. Our findings suggest that wind turbines were attributed significant local social costs in the political zoning process. These local social cost estimates can inform siting decisions, improve power system modelling and open a novel perspective on the assessment of potentials for renewable energies.

Load Frequency Optimal Active Disturbance Rejection Control of Hybrid Power System

The widespread adoption of the power grid has led to increased attention to load frequency control (LFC) in power systems. The LFC strategy of multi-source hybrid power systems, including hydroelectric generators, Wind Turbine Generators (WTGs), and Photovoltaic Generators (PVGs), with thermal generators is more challenging. Existing methods for LFC tasks pose challenges in achieving satisfactory outcomes in hybrid power systems. In this paper, a novel method for the multi-source hybrid power system LFC task by using an optimal active disturbance rejection control (ADRC) strategy is proposed, which is based on the combination of the improved linear quadratic regulator (LQR) and the ADRC controller. Firstly, an established model of a hybrid power system is presented, which incorporates multiple regions and multiple sources. Secondly, utilizing the state space representation, a novel control strategy is developed by integrating improved LQR and ARDC. Finally, a series of comparative simulation experiments has been conducted using the Simulink model. Compared with the LQR with ESO, the maximum relative error of the maximum peaks of frequency deviation and tie-line exchanged power of the hybrid power system is reduced by 96% and 83%, respectively, by using the proposed strategy. The experimental results demonstrate that the strategy proposed in this paper exhibits a substantial enhancement in control performance.

Optimal Battery Storage Configuration for High-Proportion Renewable Power Systems Considering Minimum Inertia Requirements

With the continuous development of renewable energy worldwide, the issue of frequency stability in power systems has become increasingly serious. Enhancing the inertia level of power systems by configuring battery storage to provide virtual inertia has garnered significant research attention in academia. However, addressing the non-linear characteristics of frequency stability constraints, which complicate model solving, and managing the uncertainties associated with renewable energy and load, are the main challenges in planning energy storage for high-proportion renewable power systems. In this context, this paper proposes a battery storage configuration model for high-proportion renewable power systems that considers minimum inertia requirements and the uncertainties of wind and solar power. First, frequency stability constraints are transformed into minimum inertia constraints, primarily considering the rate of change of frequency (ROCOF) and nadir frequency (NF) indicators during the transformation process. Second, using historical wind and solar data, a time-series probability scenario set is constructed through clustering methods to model the uncertainties of wind and solar power. A stochastic optimization method is then adopted to establish a mixed-integer linear programming (MILP) model for the battery storage configuration of high-proportion renewable power systems, considering minimum inertia requirements and wind-solar uncertainties. Finally, through a modified IEEE-39 bus system, it was verified that the proposed method is more economical in addressing frequency stability issues in power systems with a high proportion of renewable energy compared to traditional scheduling methods.