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Against the dual background of frequent occurrence of typhoon disaster and increasing penetration of new energy generation, a rolling optimal scheduling strategy of multiple flexibility resources including scaled electric vehicle (EV) is proposed to enhance the resilience of the distribution networks under typhoon disaster. Firstly, the fault scenarios of lines and photovoltaic (PV) in the region are simulated by Monte Carlo method based on typical meteorological characteristics, and the typical scenarios are screened by using system information entropy to get the temporal fault states of lines and PV. Secondly, a multiple flexibility resources optimization regulated model is established with the objective of minimizing the weighted load loss rate. Based on the spatio-temporal characteristics of EVs, they are expropriated and regulated, and the network is reconfigured and coordinated with mobile emergency generators (MEG) to maximize the use of resources in the network. Finally, in order to adapt to the evolution of the system fault state and adjust the regulated scheme in real time, a two-stage rolling solution method is proposed to reduce the problem solving complexity. A simulation analysis is conducted on an improved actual power supply unit network in a certain area of Jiangsu province, and the results show that the proposed strategy can effectively reduce load losses and enhance the resilience of the distribution networks in extreme scenarios.

This paper investigates on dynamic topology reconfiguration of distribution networks to enhance PV hosting capacity. Firstly, a dynamic topology reconfiguration model of distribution networks considering N-1 security constraints is proposed to accommodate intermittent PV generation, and thus high penetration of renewable resources can be ensured to satisfy operational requirements under both normal and fault conditions with load transfer of feeders. Then, a hosting capacity enhancement strategy is presented to decrease risks of voltage and line overloading with reactive power flexibility of energy storage inverters, and is implemented to enhance the maximum hosting capacity of distributed renewable energy sources. Finally, simulation results have validated the effectiveness of the proposed method for PV hosting capacity enhancement of distribution networks. [ABSTRACT FROM AUTHOR]

Power system flexibility is becoming increasingly critical in modern power systems due to the quick switch from fossil fuel-based power generation to renewables, old-fashioned infrastructures, and a sharp rise in demand. If a power system complies with financial restrictions and responds quickly to unforeseen shifts in supply and demand, it can be considered flexible. It can ramp up production during periods of high demand or increase it during unanticipated or scheduled events. The broad use of renewable energy in the power grid can provide environmental and economic benefits; nevertheless, renewables are highly stochastic in nature, with variability and uncertainty. New management with adequate planning and operation in the power system is necessary to address the challenges incorporated with the penetration of renewable energy. The primary aim of this review is to provide a comprehensive overview of power system flexibility, including appropriate definitions, parameters, requirements, resources, and future planning, in a compact way. Moreover, this paper potentially addresses the effects of various renewable penetrations on power system flexibility and how to overcome them. It also presents an emerging assessment and planning of influential flexibility solutions in modern power systems. This review's scientific and engineering insights provide a clear vision of a smart, flexible power system with promised research direction and advancement. [ABSTRACT FROM AUTHOR]

Modern power systems are developing rapidly, with distributed energy, energy storage devices, adjustable loads, and other flexible resources consolidated through microgrids, virtual power plants, and integrated source–network–load–storage systems. This consolidation under various balancing zone models facilitates synergistic operations and has become critical to enhancing distributed power consumption and ensuring the reliability of electricity supply. Therefore, in light of the challenges of inadequate economic efficiency, reduced accommodation of renewable energy, and poorer operational reliability in distribution networks, this study proposes a category selection and flexibility resource scheduling method that considers the differences in multiple balancing zone models and modes. Firstly, the approach establishes a multi-dimensional characteristic evaluation index and multiple balancing zone operation models. The characteristic evaluation indicators are then utilized to assess the unique properties of the balancing zone system and eliminate unreasonable operating modes. Finally, through analyzing the effectiveness and differences of various balancing zone operation modes, an optimal operation mode is selected, and a scheduling plan is formulated. We conclude that the scheduling plan optimization method considering the operation mode can realize a reasonable choice of operation modes and achieve benefit optimization. [ABSTRACT FROM AUTHOR]

As renewable energy becomes more widespread, the uncertainty of its output poses serious challenges for peak and frequency regulation of the power system. Evaluating a grid's capacity to integrate renewable energy sources can provide an early-warning and decision-making basis for grid operation and scheduling. This paper presents a method for evaluating the hosting capacity of renewable energy, considering frequency security constraints. Introducing the system frequency nadir constraint into a system ensures that the frequency does not drop to a dangerous level in the event of power disturbances. The analytical characterization relation equation for the system frequency nadir constraint is constructed based on polynomial chaos expansion (PCE) theory. Furthermore, with the goal of minimizing the reduction in renewable energy, considering multiple flexible resources, like demand response (DR), Combined Heat and Power (CHP), energy storage, and Power-to-Gas (P2G), a renewable energy hosting capacity evaluation model that considers frequency security and flexibility resources is established. Finally, based on the concept of the feasible region, the maximum hosting capacity of a system's renewable energy is visualized using the progressive vertex enumeration method. It identifies the safe operating region for renewable energy output that meets the safety constraints of power grid operations. The simulation results were validated using a modified IEEE 39 bus system. [ABSTRACT FROM AUTHOR]

This paper investigates on dynamic topology reconfiguration of distribution networks to enhance PV hosting capacity. Firstly, a dynamic topology reconfiguration model of distribution networks considering N-1 security constraints is proposed to accommodate intermittent PV generation, and thus high penetration of renewable resources can be ensured to satisfy operational requirements under both normal and fault conditions with load transfer of feeders. Then, a hosting capacity enhancement strategy is presented to decrease risks of voltage and line overloading with reactive power flexibility of energy storage inverters, and is implemented to enhance the maximum hosting capacity of distributed renewable energy sources. Finally, simulation results have validated the effectiveness of the proposed method for PV hosting capacity enhancement of distribution networks.

Modern power systems are developing rapidly, with distributed energy, energy storage devices, adjustable loads, and other flexible resources consolidated through microgrids, virtual power plants, and integrated source–network–load–storage systems. This consolidation under various balancing zone models facilitates synergistic operations and has become critical to enhancing distributed power consumption and ensuring the reliability of electricity supply. Therefore, in light of the challenges of inadequate economic efficiency, reduced accommodation of renewable energy, and poorer operational reliability in distribution networks, this study proposes a category selection and flexibility resource scheduling method that considers the differences in multiple balancing zone models and modes. Firstly, the approach establishes a multi-dimensional characteristic evaluation index and multiple balancing zone operation models. The characteristic evaluation indicators are then utilized to assess the unique properties of the balancing zone system and eliminate unreasonable operating modes. Finally, through analyzing the effectiveness and differences of various balancing zone operation modes, an optimal operation mode is selected, and a scheduling plan is formulated. We conclude that the scheduling plan optimization method considering the operation mode can realize a reasonable choice of operation modes and achieve benefit optimization.

This article explores the challenges and solutions related to scheduling flexibility resources in active distribution networks (ADNs) with renewable energy sources. The authors propose a bi-level distributed scheduling model to minimize operational costs and promote the integration of renewable energy. They also present a fast distributed asynchronous optimization method to improve real-time scheduling. Case studies using the IEEE33 bus distribution system demonstrate the effectiveness of the proposed method. The authors suggest that future research should consider uncertainties in renewable energy resources and load demand when optimizing ADNs. The article provides information about the authors' affiliations and the publication process, including the names of reviewers. [Extracted from the article]

Abstract Flexibility potentials are mostly provided by centrally coordinated flexibility resources such as natural-gas-fired power plants. However, the decentralization of power generation combined with the decarbonization of the sector due to the energy transition requires the exploration of new types of flexibility resources. In particular, to reduce dependence on natural-gas-fired power plants, it would be desirable to replace them with alternative flexibility resources. Therefore, the objective of this paper is to analyze, using Germany as an example, to what extent the flexibility potential of already existing battery storage systems can replace the flexibility potential of natural-gas-fired power plants. The methodology used is based on a multi-time-scale flexibility model together with an approach for temporal aggregation of flexibility potentials and two approaches for spatial aggregation of flexibility potentials. Based on the methodology and an analysis of publicly available data, a comprehensive potential analysis is carried out. This analysis shows, among others, that existing battery storage systems have a promising potential to replace a considerable number of natural-gas-fired power plants in Germany in terms of their flexibility potentials.

This article explores the resilient operations of active distribution networks (ADNs) in the face of challenges posed by distributed renewable energy and extreme climate events. The authors propose a cellular architecture for ADNs that enhances resilience and presents a two-stage resilient model and a multi-level distributed control strategy. The model optimally schedules flexibility resources and coordinates network reconfiguration and repair crew to minimize costs and maintain reliable power supplies. The study also discusses the autonomous resilient operations of distribution networks under extreme climates, including pre-disaster prevention and post-disaster recovery stages. Future research will focus on integrating diversified flexibility resources into active distribution networks. [Extracted from the article]

High penetrated renewable energy has brought great challenges to the flexibility of the power system due to its volatility and intermittency. To improve the capacity of renewable energy accommodation, the flexibility reformation of thermal power units, the construction of gas-fired units, and the electrical energy storage installation are considered as effective solutions. Thus, an optimization model for power system planning scheme considering multi-type flexible resources with their different output characteristics is established. The simulation results on a modified IEEE 24-bus power system and 12-node natural gas system demonstrate the effectiveness of the proposed model. In addition, the applicability of different flexible resource planning schemes is comprehensively evaluated from the perspectives of economy, accommodation capacity, and carbon reduction, so as to meet the different planning goals.

Flexibility potentials are mostly provided by centrally coordinated flexibility resources such as natural-gas-fired power plants. However, the decentralization of power generation combined with the decarbonization of the sector due to the energy transition requires the exploration of new types of flexibility resources. In particular, to reduce dependence on natural-gas-fired power plants, it would be desirable to replace them with alternative flexibility resources. Therefore, the objective of this paper is to analyze, using Germany as an example, to what extent the flexibility potential of already existing battery storage systems can replace the flexibility potential of natural-gas-fired power plants. The methodology used is based on a multi-time-scale flexibility model together with an approach for temporal aggregation of flexibility potentials and two approaches for spatial aggregation of flexibility potentials. Based on the methodology and an analysis of publicly available data, a comprehensive potential analysis is carried out. This analysis shows, among others, that existing battery storage systems have a promising potential to replace a considerable number of natural-gas-fired power plants in Germany in terms of their flexibility potentials. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Shanghai Jiao Tong University (1006-2467) is the property of Journal of Shanghai Jiao Tong University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Under the high proportion of renewable energy access in the integrated energy system, the insufficient total allocation of flexible resources and the unreasonable spatial allocation of resources are important causes of wind abandonment and load shedding. The fundamental solution to this problem is to increase the flexibility of the system to meet demand, so it is important to study multiple types of flexible resources, the state of supply and demand for system flexibility and the optimization of flexibility resource scheduling. This paper studies the flexibility of the integrated energy system. First, it analyzes the basic characteristics of the flexible resources of the system and gives the basic structure of the integrated energy system;Then, the typical flexible resources are modeled and analyzed. Based on the time-of-use price, the minimum daily operation cost of the system is optimized as the objective function, and the particle swarm optimization algorithm is introduced to solve it, so as to explore the flexible adjustment of the system with the participation of flexible resources;Finally, the model established in this paper is used to verify the rationality of the scheduling scheme, and the relationship between the access effect of flexible resources and the location of access nodes is explored. The research on the modeling of integrated energy system and system flexibility in this paper not only provides a tool to reflect the fluctuation of system supply and demand state, but also provides an important basis for system reasonable scheduling, ensuring energy supply quality and improving operation flexibility.

In recent years, the increasing of non-dispatchable resources has posed severe challenges to the operation planning of power systems. Since these resources are random in nature, the issue of flexibility to cover their uncertainty and variability has become an important research topic. Therefore, having flexible resources to cover changes in the generation of these resources during their operation can play an essential role in eliminating node imbalances, system reliability, providing the required flexible ramping capacity, and reducing system operating costs. Among flexibility resources, there are quick-act generation units such as gas units that can play an important role in covering net load changes. Also, on the demand side, the optimal design of demand response programs as responsive resources to price and incentive signals, by modifying the system load factor can prevent severe ramps at net load, especially during peak load hours, and as a result, increase system flexibility while decreasing operational cost of the power system. In this paper, unlike the existing literature, the effect of the mentioned flexibility resources (both on the generation side and the demand side) in day-ahead operation planning under high penetration of wind generation units has been studied on the IEEE RTS 24-bus test system. Also, for this scheduling, a mixed-integer, two-stage, and tri-level adaptive robust optimization have been used, which is solved by column-and-constraint generation decomposition-based algorithm to clear the energy and ramping capacity reserve jointly. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper presents a new methodology to exploit consumers’ flexibility for the provision of ancillary services (AS) in the smart grid era. The proposed framework offers a control-based approach that adopts price signalsas the economic driver to modulate consumers’ response. In this framework, various system operators broadcast price signals independently to fulfil their AS requirements. Appropriate flexibility estimators are developed from the transmission system operator (TSO) and distribution system operator (DSO) perspectives for price generation. An artificial neural network (ANN) controller is used for the TSO to infer the price-consumption reaction from pools of consumers in its territory. A proportional-integral (PI) controller is preferred to represent the consumers’ price-response and generate time-varying electricity prices at the DSO level for voltage management. A multi-timescale simulation model is built in MATLAB to assess the proposed methodology in different operational conditions. Numerical analyses show the applicability of the proposed method for the provision of AS from consumers at different levels of the grid and the interaction between TSO and DSOs through the proposed framework. [ABSTRACT FROM AUTHOR]

In recent years, the increasing of non-dispatchable resources has posed severe challenges to the operation planning of power systems. Since these resources are random in nature, the issue of flexibility to cover their uncertainty and variability has become an important research topic. Therefore, having flexible resources to cover changes in the generation of these resources during their operation can play an essential role in eliminating node imbalances, system reliability, providing the required flexible ramping capacity, and reducing system operating costs. Among flexibility resources, there are quick-act generation units such as gas units that can play an important role in covering net load changes. Also, on the demand side, the optimal design of demand response programs as responsive resources to price and incentive signals, by modifying the system load factor can prevent severe ramps at net load, especially during peak load hours, and as a result, increase system flexibility while decreasing operational cost of the power system. In this paper, unlike the existing literature, the effect of the mentioned flexibility resources (both on the generation side and the demand side) in day-ahead operation planning under high penetration of wind generation units has been studied on the IEEE RTS 24-bus test system. Also, for this scheduling, a mixed-integer, two-stage, and tri-level adaptive robust optimization have been used, which is solved by column-and-constraint generation decomposition-based algorithm to clear the energy and ramping capacity reserve jointly.

This study presents a flexible, reliable, and renewable power system resource planning approach to coordinate generation, transmission, and energy storage (ES) expansion planning in the presence of demand response (DR). The flexibility and reliability of the optimal resource expansion planning are ensured by means of appropriate constraints incorporated into the proposed planning tool where thermal generation units, ES systems, and DR programs are considered as flexibility resources. The proposed planning tool is a mixed‐integer non‐linear programming (MINLP) problem due to the non‐linear and non‐convex constraints of AC power flow equations. Accordingly, to linearise the proposed MINLP problem, the AC nodal power balance constraints are linearised by means of the first‐order expansion of Taylor's series and the line flow equations are linearised by means of a polygon. Additionally, the stochastic programming is used to characterise the uncertainty of loads, a maximum available power of wind farms, forecasted energy price, and availability/unavailability of generation units and transmission lines by means of a sufficient number of scenarios. The proposed planning tool is implemented on the IEEE 6‐bus and the IEEE 30‐bus test systems under different conditions. Case studies illustrate the effectiveness of the proposed approach based on both flexibility and reliability criteria. [ABSTRACT FROM AUTHOR]

Demand flexibility will be an inevitable part of the future power system operation to compensate stochastic variations of ever-increasing renewable generation. One way to achieve demand flexibility is to provide time-varying prices to customers at the edge of the grid. However, appropriate models are needed to estimate the potential flexibility of different types of consumers for day ahead and real-time ancillary services (AS) provision. The proposed method should account for rebound effect and variability of the customers’ reaction to the price signals. In this study, an efficient algorithm is developed for consumers’ flexibility estimation by the transmission system operator (TSO) based on offline data. No aggregator or real-time communication is involved in the process of flexibility estimation, although real-time communication channels are needed to broadcast price signals to the end-users. Also, the consumers’ elasticity and technical differences between various types of loads are taken into account in the formulation. The problem is formulated as a mixed-integer linear programming (MILP) problem, which is then converted to a chance-constrained programming to account for the stochastic behavior of the consumers. Simulation results show the applicability of the proposed method for the provision of AS from consumers at the TSO level. [ABSTRACT FROM AUTHOR]

A new scenario-based electricity system model, SILVER, explores the trade-offs among alternative balancing strategies for high variable renewable energy (VRE) electricity grids. SILVER optimizes the asset dispatch for a user-defined electricity system configuration that specifies demand response availability, generation assets, storage assets, and transmission infrastructure. SILVER has been applied to twelve Ontario-based scenarios to explore the implications of high VRE penetrations in a 100% renewable scenario. The role that storage, demand response, electric vehicles, and transmission expansion might play in balancing VRE is analyzed. The results highlight the operational differences between balancing options: demand response, with a fixed price remuneration, is dispatched in proportion to net load curve variability, whereas storage technologies which take advantage of price arbitrage, are dispatched in proportion to marginal cost variability. GHG emissions fall with increasing VRE penetrations; however, there are local maxima when natural gas replaces nuclear generation, which interrupt this trend. Weak wind resources in the summer necessitate significant non-VRE capacity, which increases capital costs for higher VRE penetrations. Ontario planners have a number of interdependent challenges to contend with: integrating VREs on a nuclear-dominated system, mitigating wind's significant seasonal variability, and establishing effective remuneration mechanisms to improve grid flexibility. [ABSTRACT FROM AUTHOR]

Although there is large consensus regarding the significance of flexibility in power systems, there exists significant disparity in the definitions and models employed to describe flexibility. To structure existing flexibility descriptions, this work classifies the mathematical principles underlying the flexibility models and finds quality metrics, machine learning models, and flexibility envelopes to be the main higher-order classes, with envelopes being the most popular one. It finds that there is a significant degree of mathematical incompatibility among different flexibility models, even within the same class. This is primarily due to the utilization of distinct flexibility metrics. To address the ambiguities in flexibility definitions and terminology, this paper introduces FLEXBLOX, a formal flexibility taxonomy. FLEXBLOX encompasses three core building blocks: a power system's flexibility requirements, the flexibility potentials provided by flexibility resources, and flexibility mediators that facilitate between the requirements and the potentials. An analysis of 49 flexibility models shows that three of them cover both flexibility requirements and potentials. However, only one of the three approaches also considers a flexibility mediator between them. Two models are generic enough to describe the flexibility potential of diverse flexibility resources, but certain resource characteristics are often excluded. To date, there is no flexibility model that addresses all three flexibility building blocks of the FLEXBLOX taxonomy coherently. This leaves room for future research directions that are suggested in this work. • Flexibility taxonomy based on the concepts of flexibility requirements and potentials. • Categorization of existing flexibility concepts to structure the research area. • Classification scheme for flexibility models based on mathematical principles. • Analysis of 49 flexibility models with regard to the flexibility taxonomy. • Discussion of future research directions in formal flexibility modeling. [ABSTRACT FROM AUTHOR]

Power systems are transitioning toward having high shares of variable renewable energy (VRE) with the help of flexibility resources. However, multiple flexibility resources on the generation, storage and demand sides introduce multiple technical and economic uncertainties, making the transition hard to predict. Moreover, the benefit of these resources in the transition is unclear. To fill these gaps, this paper proposes a data-driven approach to explore the transition to a high VRE share-oriented power system with multiple flexibility resources. This approach generates a wealth of possible transition paths under multiple uncertainties and then uses them to quantitatively analyze the transition. Specifically, the proposed method includes principal component analysis-based path visualization, multiple index-based transition milestone identification, cluster and distance calculation-based key influential factor identification, marginal index-based flexibility resource benefit comparison and Pareto frontier-based path recommendation. Case studies based on the Northwest China power system, which involves wind, photovoltaics and concentrated solar plants, validate the effectiveness of the proposed approach and further indicate that flexibility resources increase rapidly with the growth of the VRE share. Of the multiple flexibility resources, storage contributes the most. Key influential factors include the capital cost of VRE and storage along with coal price. These factors should be the focus in a low-cost and low-carbon transition. [ABSTRACT FROM AUTHOR]