Transmission System Operators Research Articles

Real-time coordination of integrated transmission and distribution systems: Flexibility modeling and distributed NMPC scheduling

This paper proposes a real-time distributed operational architecture to coordinate integrated transmission and distribution systems (ITD). At the distribution system level, the distribution system operator (DSO) calculates the aggregated flexibility of all controllable devices by power-energy envelopes and provides them to the transmission system operator (TSO). At the transmission system level, a distributed nonlinear model predictive control (nmpc) approach is proposed to coordinate the economic dispatch of multiple TSOs, considering the aggregated flexibility of all distribution systems. The subproblems of the proposed approach are associated with different TSOs and individual time periods. In addition, the aggregated flexibility of controllable devices in distribution networks is encapsulated, re-calculated, and communicated through the power-energy envelopes, facilitating a reduction in computational complexity and eliminating redundant information exchanges between TSOs and DSOs, thereby enhancing privacy and security. The framework’s effectiveness and applicability in real-world scenarios are validated through simulated operational scenarios on a summer day in Germany, highlighting its robustness in the face of significant prediction mismatches due to severe weather conditions.

On the practical aspects of machine learning based active power loss forecasting in transmission networks

AbstractThe cost for covering active power losses makes a significant item in transmission system operators (TSO) annual budgets, and still it received limited attention in the existing literature. The focus of accurate power loss forecasting and procurement is of high increase during the past 2 years due to spikes in electricity prices, making the cost of covering the active power losses a dominant factor of TSO operational costs. This paper presents practical aspects of the highly accurate models for transmission loss forecast in the day ahead time frame for the Croatian transmission system. The contributions are two‐fold: 1) Practical insights into usable TSO data are provided, filling a critical research gap and a foundational literature review is established on transmission loss forecasting. 2) A novel method utilizing only electricity transit data as input which outperforms existing practices is presented. For this, several algorithms such as gradient boosted decision tree model (XGB), support vector regressors, multiple linear regression and fully connected feedforward artificial neural networks are developed, and implemented and validated on data obtained from the Croatian TSO. The results show that the XGB model outperforms current TSO model by 32% for 4 months of comparison and TSCNET's commercial solution by 25% during a year‐long testing period. The developed XGB model is also implemented as a software tool and put into everyday operation with the Croatian TSO.

An iterative approach to grid topology and redispatch optimization in congestion management

The selection of Remedial Actions (RA) to ensure system security is a highly complex task performed by Transmission System Operators (TSOs). Phase shifting transformer (PST) tap changes and active power changes of generation units (redispatch) are some RA available in Security Constrained Optimal Power Flow (SCOPF) simulations within the operational planning processes. Topological RA are not part of these SCOPF yet, as the optimization thereof adds high complexity to the existing optimization problem. To overcome this complexity, this paper introduces an iterative approach that decouples topology optimization from redispatch & PST optimization. Linearized models of RA are used to meet computation time requirements. Exemplary investigations of the presented method were performed based on modified IEEE 39-Bus, 118-Bus and PEGASE-1354-Bus grid models. Within the scope of these investigations, the method shows good results and a great potential for the reduction of congestions and required redispatch through topological RA. In order to eliminate inaccuracies of the approach and to further improve its suitability for use in grid operation, a need for future investigations and possible further developments were identified.

Hierarchical robust Day-Ahead VPP and DSO coordination based on local market to enhance distribution network voltage stability

As distributed energy resources (DER) are increasing, a variety of business models and markets are appearing. Business models such as virtual power plants (VPPs) contribute to enhanced stability of the power system while improving the profits of participating resources. However, the uncertainty of the behavior of DERs and the resulting stability issues are a major barrier to DER deployment and require a coordination framework between grid operators and business models to overcome. Therefore, in this paper, a hierarchical robust day-ahead coordination of a VPP and distribution system operator (DSO) based on the local market is proposed to improve the voltage stability of the distribution network by considering the uncertainty of DERs. For fairness reasons, the contribution of DERs to the distribution system can be addressed by a market-based approach. Local markets are divided into local energy markets (LEM) and local flexibility markets (LFM), which can consider the uncertainty and profitability of DERs. First, the DER determines the seller and buyer status of the LEM based on its self- scheduling with expected prices and is matched based on a double-auction mechanism. At this time, the worst-case scenario of load and renewable energy generation predicted by the Gaussian process (GP) is considered. The mismatched amounts in the LEM are aggregated by the VPP and bid into the wholesale energy market (WEM) operated by the TSO (Transmission system operator). Subsequently, DSO operates a LFM that coordinates microgrid (MG) and VPP on the distribution grid to increase voltage stability. The LFM and WEM problems are considered as interval optimization in the form of mixed integer linear programming and are applied together. The flexibility supply resulting from the adjustment of VPP is compensated by a loss-sensitivity-based flexibility price. Since voltage stability exists in upper and lower bounds, the upper and lower bound of net load through GP-based forecasting is considered along with the linearized network constraints. The results are validated through Monte-Carlo simulation-based scenarios on IEEE benchmark system in MATLAB environment. As a result, it is proved that the proposed model improves the distribution network voltage stability and the profit of the participants.

Cost-Effective Target Capacity Assessment in the Energy Transition: The Italian Methodology

Long-term transmission expansion planning has to face the energy transition in a restructured electricity market environment. Increased transmission capacity within and between Member States is likely to play an essential role in maintaining the secure and economic operation of the whole European power system and ensuring the integration of growing renewable generation. This paper proposes a novel iterative methodology aimed at assessing an optimal level of interconnection between relevant bidding zones, simultaneously investigating different potential alternatives. Starting from a reference grid, a multi-criteria analysis is adopted to select the additional transmission capacities to be tested in each iteration via network and market simulations in order to confirm that transmission expansion benefits outweigh the estimated realization costs. The proposed approach is applied to the Italian case in two contrasting energy scenarios for the mid-term 2030 and very-long-term 2040 horizons: different development strategies are derived, and the least regret criterion is applied to define the most cost-effective as the target development strategy for the Transmission System Operator (TSO). Furthermore, sensitivity analyses on relevant input data variation are performed to test the robustness of the results obtained.

Bi-Level Continuous-Time Model for the Coordinated Operation of Coupled Electric Power Transmission and Energy Storage Transportation Systems

Bi-Level Continuous-Time Model for the Coordinated Operation of Coupled Electric Power Transmission and Energy Storage Transportation Systems

Life Cycle Analysis of a Battery Energy Storage System

For Latvian government and transmission system operator energy security and independence has been an issue for a period of time, even more when political situation changed, motivating to act faster in order to swich off from BREL system completely. Therefore, three Baltic states have made an agreement on building more stable electricity transmission system within Baltic region and to connect with European transmission systems, building new stations with synchronous compensators and energy storage systems. In order to build a system, that allows to include more energy from renewable resources and secure possible disbalances in system, Latvian TSO operator is building a new battery energy storage system. This paper is aimed to look at what are the costs of this battery energy storage system from climate perspective to Latvia and its society in order to gain energy security and possibility to include more energy from renewable resources.

Aggregated model of an active distribution system for coordinated TSO–DSO fast frequency control

The growing integration of distributed energy sources (DERs) challenges the traditional independent operation of transmission system operators (TSOs) and distribution system operators (DSOs). The coordination between TSOs and DSOs becomes essential, as DERs not only offer local ancillary services but also enable the provision of these services at the distribution network level following disturbances in the transmission system. To enhance power system analyses in TSO–DSO coordination, the availability of reduced-order or aggregated models proves crucial, avoiding detailed modeling and reducing computational burden. Addressing the lack of reduced-order models capturing the dynamics of diverse distributed technologies and their control systems within a unified single-device model, this paper introduces a single equivalent device based on virtual synchronous machine (VSM) technology. This device effectively subsumes the frequency response of various DERs and loads. The proposed aggregation methodology undergoes validation on systems of different sizes and compositions of DERs. Results from simulated scenarios consistently demonstrate the accuracy and generalizability of the proposed aggregated model, irrespective of system size and included technologies.

The role of data-driven methods in power system security assessment from aggregated grid data

Data-driven techniques have been considered as an enabling technology for reducing the computational burden of both static and dynamic power system security analysis. Anyway, the studies reported in the literature mainly focused on inferring from historical data the mapping between the bus variables before and after a certain contingencies set, while, to the best of the Author's knowledge, limited contributions have been devoted to try and classify the power system security state by processing aggregated grid data. This is a relevant issue to address for a Transmission System Operator since it could allow a sensible decrease in the computational burden and, considering that aggregated grid data can be reliably predicted from several hours to one day ahead, it may enable the evolution of security assessment to security forecasting. In trying and filling this research gap, this paper explores the role of machine learning and feature selection algorithms. A realistic case study involving 2 years of synthetic grid data simulated on the Italian power system model against future potential operational scenarios characterized by a high share of renewables is presented and discussed to identify the most promising computing paradigms, analyzing the criticality of tuning the feature selection and classifier algorithms.

A Survey on Data Compression Techniques for Automotive LiDAR Point Clouds.

In the evolving landscape of autonomous driving technology, Light Detection and Ranging (LiDAR) sensors have emerged as a pivotal instrument for enhancing environmental perception. They can offer precise, high-resolution, real-time 3D representations around a vehicle, and the ability for long-range measurements under low-light conditions. However, these advantages come at the cost of the large volume of data generated by the sensor, leading to several challenges in transmission, processing, and storage operations, which can be currently mitigated by employing data compression techniques to the point cloud. This article presents a survey of existing methods used to compress point cloud data for automotive LiDAR sensors. It presents a comprehensive taxonomy that categorizes these approaches into four main groups, comparing and discussing them across several important metrics.

Getting Ready for Multi-Vendor and Multi-Terminal HVDC Technology

Interoperable multi-vendor High-Voltage Direct-Current (HVDC) grids are a key enabler for the integration of renewable energy (in particular offshore wind) and its transmission over longer distances to consumers. However, most HVDC systems today are single-vendor and point-to-point. Various technical and non-technical aspects need to be considered, for example, (real-time) testing, legal aspects (intellectual property and regulation), and the multi-vendor interoperability process. This paper presents findings from the READY4DC project, which is a larger and open European effort involving diverse stakeholders, including HVDC manufacturers, transmission system operators, wind developers, academia, and research institutes. It summarizes key technical recommendations, emphasizing comprehensive interaction studies and the development of a structured legal framework to facilitate the development and operation of a multi-vendor, multi-terminal HVDC grid. The READY4DC project highlights the need for increased harmonization, transparent communication among stakeholders, and future-oriented research to ensure the robustness and interoperability of interconnected grids. Collaborative efforts are key for addressing technical complexities and advancing the deployment of multi-vendor multi-terminal HVDC technology.

Experimental and Finite Element Analyses of Adjustable Foundation Bolts in Transmission Towers

Uneven settlement of transmission tower foundations can result in catastrophic events, such as tower collapse and line failures, disrupting power transmission operations. To address the challenging repairs caused by uneven foundation settlement of transmission towers, we propose an adjustable foundation bolt (AFB). This paper provides a detailed theoretical analysis of the AFB’s stability and load-bearing capacity, including critical buckling force formulas and maximum normal stress expressions. Finite element simulations confirm the precision of our theoretical formulations. Additionally, we introduce a method using baffles to enhance its load-bearing capacity, analyzing the impact of different numbers of baffles through numerical simulations. The experimental results validate the effectiveness of baffles in enhancing structural load-bearing capacity. The device brings convenience and efficiency to the maintenance of transmission towers.

An energy management system to schedule the optimal participation to electricity markets and a statistical analysis of the bidding strategies over long time horizons

This paper presents a tool that allows to perform an ex-ante estimation of the profitability to participate to the electric energy and service markets for a microgrid or a polygeneration power plant. The tool is the evolution of an Energy Management System (EMS) previously developed by the University of Genoa and Renantis Solutions Srl. Constraints are added to the original EMS to model the Ancillary Service Market (ASM) and Day Ahead Market (DAM) mechanisms in the framework of a planning tool that allows to get estimates of the microgrid/plant costs and revenues over a long-time horizon. As the market outcome strongly depends on the Transmission System Operator (TSO) acceptance/rejection of bids and offers, a statistical approach is proposed. The optimization process is split in two steps: the first one optimally dispatches the energy units and proposes DAM offers and ASM bid and offers over a specified time horizon. Then, a Monte Carlo method is launched; at each extraction the TSO acceptance/rejection of each ASM bid and offer is simulated and there is a second step of optimization in which the energy sources are optimally re-dispatched to meet the bidding program and so to avoid imbalance power exchange that would increase the energy cost. The cost/revenue is thus computed at each extraction. The result is the probability density function of the costs/revenues that allows to estimate the profitability of the participation to the electricity markets. One test performed on a real microgrid shows that the computational time needed to complete one iteration related to a time horizon of one month is approximately 20 s. Moreover, the comparison of the outcomes with two independent launches to define the set of bids and offers to be accepted in ASM demonstrates that the statistical analysis allows to avoid misleading conclusions on the costs/revenues. Consequently, the fact that the developed EMS allows to perform a statistical analysis in a reasonable time enables the possibility of comparing multiple scenarios and gives an indication related to the range of cost/revenues in which the microgrid/plant may incur. Finally, the computational efficiency of the proposed approach allows to conclude that the developed EMS is appropriate to perform a long-time horizon (of the order of magnitude of years) analysis and, at the same time, allows to model all the involved components with a high level of details.

Security constrained economic dispatch with VSC-HVDC connected wind farms

The rise in wind power in electrical networks creates complex challenges for transmission system operators (TSOs), particularly regarding real-time operation. TSOs rely on grid codes to enforce wind farm (WF) participation in primary frequency control (PFC), like conventional plants. This paper addresses this need by proposing a security constrained economic dispatch (SCED) model with VSC-HVDC connected WFs based on variable speed wind generators. A key differentiator from existing models is the explicit calculation of the spinning reserve and the droop parameter of the WFs. This method uses the deloading schemes related to blade pitch angle and mechanical rotor speed to ensure compliance with grid codes related to PFC. We show that the wind speed and these deloading schemes significantly impact the WF droop parameter. For efficient studies, linear shift factors are used to model the transmission grid and the VSC-HVDC connected WFs. The performance of the SCED model was assessed using two standard test systems that incorporate WFs connected by VSC-HVDC lines. Its effectiveness was confirmed by comparing it with the security constrained optimal power flow (SCOPF). The results showed agreement between both models, with differences less than 3 % and with the SCED saving about 70 % of the computing time.

Controlling the broadband enhanced light chirality with L-shaped dielectric metamaterials

The inherently weak chiroptical responses of natural materials limit their usage for controlling and enhancing chiral light-matter interactions. Recently, several nanostructures with subwavelength scale dimensions were demonstrated, mainly due to the advent of nanofabrication technologies, as a potential alternative to efficiently enhance chirality. However, the intrinsic lossy nature of metals and the inherent narrowband response of dielectric planar thin films or metasurface structures pose severe limitations toward the practical realization of broadband and tailorable chiral systems. Here, we tackle these problems by designing all-dielectric silicon-based L-shaped optical metamaterials based on tilted nanopillars that exhibit broadband and enhanced chiroptical response in transmission operation. We use an emerging bottom-up fabrication approach, named glancing angle deposition, to assemble these dielectric metamaterials on a wafer scale. The reported strong chirality and optical anisotropic properties are controllable in terms of both amplitude and operating frequency by simply varying the shape and dimensions of the nanopillars. The presented nanostructures can be used in a plethora of emerging nanophotonic applications, such as chiral sensors, polarization filters, and spin-locked nanowaveguides.

Centralized Protection and Control for Transmission System Operations: Practical Applications and Perspectives

Centralized Protection and Control for Transmission System Operations: Practical Applications and Perspectives

Nonlinear dynamics analysis of electromechanical planetary gear systems with temperature effects considered

PurposeThe electromechanical planetary transmission system has the advantages of high transmission power and fast running speed, which is one of the important development directions in the future. However, during the operation of the electromechanical planetary transmission system, friction and other factors will lead to an increase in gear temperature and thermal deformation, which will affect the transmission performance of the system, and it is of great significance to study the influence of the temperature effect on the nonlinear dynamics of the electromechanical planetary system.Design/methodology/approachThe effects of temperature change, motor speed, time-varying meshing stiffness, meshing damping ratio and error amplitude on the nonlinear dynamic characteristics of electromechanical planetary systems are studied by using bifurcation diagrams, time-domain diagrams, phase diagrams, Poincaré cross-sectional diagrams, spectra, etc.FindingsThe results show that when the temperature rise is less than 70 °C, the system will exhibit chaotic motion. When the motor speed is greater than 900r/min, the system enters a chaotic state. The changes in time-varying meshing stiffness, meshing damping ratio, and error amplitude will also make the system exhibit abundant bifurcation characteristics.Originality/valueBased on the principle of thermal deformation, taking into account the temperature effect and nonlinear parameters, including time-varying meshing stiffness and tooth side clearance as well as comprehensive errors, a dynamic model of the electromechanical planetary gear system was established.

Common TSO-DSO market framework with no upfront priority to utilize DER flexibility

Grid integration of distributed energy resources (DERs) is vital to provide flexibility services, required to ensure efficient system operations at both transmission and distribution levels. To prevent negative interactions between transmission system operators (TSO) and distribution system operators (DSOs) while procuring flexibility services from DERs, it is imperative to prioritize them. However, for system's cost-effectiveness allocating DER flexibility to the operator with the highest need is preferable rather than giving upfront priority. To address this, a novel coordinated decision-making approach for a common TSO-DSO market is proposed. This approach considers global balancing for the TSO and distribution congestion management for the DSO as objectives, using them as deciding factor to allocate DER flexibility to the system operator with the greatest need to fulfil its objective. Results show proposed method enhances DSO's flexibility transfer to TSO and maintains reactive power at T-D interface. Gap between TSO's DER flexibility needs and availability, influenced by congestion and line losses, is critical for prioritization. Specifically, network capacity and line losses constitute 18.79 % and 3.42 % of offered DER flexibility, respectively. Reactive power deployment improves Q/P ratio, reducing standard deviation from 0.19 to 0.018. Framework reduces conflicts, provides clear flexibility allocation rules without upfront priority.

Cost minimization of a hybrid PV-to-methanol plant through participation in reserve markets: A Danish case study

In efforts to combat carbon emissions in challenging sectors like heavy industry and shipping, Power-to-X (PtX) technology emerges as a promising solution. PtX involves converting renewable energy into hydrogen via water electrolysis and further processing it into eco-friendly fuels like methanol, ammonia, or kerosene. Denmark has seen a rise in plans for integrating large-scale PtX projects, which will introduce large electrical loads to its power system.To optimize the cost-effectiveness of PtX-based fuel production, a proposal suggests leveraging PtX plants’ inherent flexibility to provide frequency reserves to the electrical grid. The study centers on a real-life hybrid renewable energy system (HRES) dedicated to methanol production in Denmark.Analyzing the HRES technology and current reserve markets reveals that the HRES qualifies for frequency reserve provision certification, encompassing FCR, aFRR, and mFRR, by the transmission system operator. Through participation in the reserve market, the HRES can generate added revenue, resulting in substantial reductions of 12% and 30% in the levelised cost of methanol for 2020 and 2021 operational expenditure outcomes, respectively.The study illustrates significant cost reductions achievable through engagement in reserve markets, and these reductions may escalate further with increased market prices and volatility. Participating in frequency reserve capacity markets not only facilitates overall cost reduction but also serves as an insurance policy against unpredictable energy market fluctuations. This approach presents a promising trajectory to promote PtX technology adoption and nurture sustainable energy practices in challenging sectors.

Hierarchical optimal dispatching method of transmission system operators‐distribution system operators cooperated integrated energy system considering gas‐thermal equivalence model

AbstractThe integrated energy system (IES) is moving towards the large‐scale cooperation between transmission system operators (TSO) and distribution system operators (DSO) with the coupling of electricity, heating, and gas networks. The conventional optimization method is not time‐efficient for solving such a large‐scale problem when taking account of the cooperation of TSO‐DSO of the IES. To solve such a problem, this paper proposed a hierarchical optimization framework for TSO‐DSO cooperated IES. To further improve the computation efficiency, the equivalent models of heating and gas system that retain the heating inertia characteristic and gas pipe storage characteristic are presented. A computation method for the TSO‐DSO cooperated IES is also proposed from the hierarchical distributed optimization perspective. The case study confirms the efficacy of the proposed gas‐thermal equivalent model in significantly enhancing computational speed. Furthermore, the proven effectiveness of the hierarchical distributed optimization approach in leveraging the full potential of flexible resources in transmission and distribution systems while safeguarding internal information privacy enables the development of robust dispatching strategies for each system.