Transmission Line Capacity Research Articles

Optimal Scheduling Strategy of Wind–Solar–Thermal‐Storage Power Energy Based on CGAN and Dynamic Line–Rated Power

This paper introduces a new way to plan and manage the use of wind and solar power, along with traditional thermal power (TP) and batteries, to get the most environmental and economic benefits. It uses a special kind of artificial intelligence, called conditional generative adversarial networks (CGAN), to predict how much power wind and solar sources will produce. Subsequently, it takes into account the dynamic line–rated power (DLRP) in order to determine the dynamic transmission capacity of lines associated with wind and solar power generation. The primary objectives are to reduce the operating costs of TP plants, maximize the utilization of wind and solar energy, minimize power deviations in electricity transmission, and enhance revenue from electricity transmission. To solve this complex problem, the paper uses a smart method to simplify the model, making it possible to find solutions with CPLEX. Tests on a small network with six nodes show that this approach not only saves money but also makes better use of clean energy sources.

Large-scale offshore wind energy integration by wind-thermal bundled power system: A case study of Yangxi, China

A large-scale offshore wind power integration has a reverse peak regulation effect on the electric load and requires newly built transmission corridors. This work adopts a wind-thermal (WT) bundled system for offshore wind power integration and transmission line capacity factor improvement. The Qingzhou I-VII offshore wind farms (5000 MW) and the Yangxi coal-fired power plant units #5, #6 (2 × 1240 MW) are taken as a case study. The offshore wind farms (OWF) act as the must-take generator to increase the renewable fraction while the thermal power plants (TPP) provide peak regulation service to trace the changing net load. The OWF and TPP share the transmission line and point of interconnection. The OWF integration level is determined by the 8760-h production simulation and the wind-thermal (W-T) capacity ratio is 1.4516:1 (3600 MW OWF) in the studied site. The curtailment rate, electricity shortage rate, transmission line capacity factor (CF), load following precision, renewable fraction, CO2 emission of WT-W3600 condition are 9.02%, 5.41%, 61.36%, 91.43%, 50.46%, 6.97 million ton/year. There is a trade-off relationship between renewable fraction and curtailment rate in the WT system which restricts higher OWF integration. The demand-side response technologies such as power-to-X and energy storage are required to break the trade-off relation and reduce the electricity shortage rate. The WT system is economically viable and the net present value (NPV), levelized cost of electricity (LCOE), internal rate of return (IRR) of WT-W3600 are 3.55 billion¥, 0.4859¥/kWh, 4.82%. Co-locating the OWF and the floating solar photovoltaic (PV) is the future direction that benefits the intensive exploitation of sea area and offshore renewable energy development.

Large-scale offshore wind integration by wind-thermal-electrolysis-battery (WTEB) power system: A case study of Yangxi, China

Offshore wind power integration is a grand challenge due to the volatility, randomness and intermittency This work presents a wind-thermal-electrolysis-battery (WTEB) hybrid energy system designed to integrate large-scale offshore wind energy and reduce curtailment. The system composes of offshore wind farms (OWF), thermal power plants (TPP), electrolysis station, battery bank. The Qingzhou (geographic name) I-VII offshore wind farms (5000 MW) and the Yangxi (geographic name) coal-fired power plant units #5, #6 (2 × 1240 MW) are taken as a case study. The OWF is the indispensable generator and the renewable fraction increases with integration level. The TPP adjusts the load ratio to meet the changing net load. The electrolysis station consumes the excess electricity and the battery bank time-shifts the electricity to reduce the electrolyzer downtime. The recommended wind-thermal (W-T) capacity ratio is 1.452:1 in the studied case, namely 3600 MW OWF. The WTEB system breaks the trade-off relationship between renewable fraction (50.11%) and curtailment rate (1.48%) compared to traditional wind-thermal (WT) bundled system. The WPEB system improves the electricity shortage rate (4.74%), transmission line capacity factor (61.79%), load following precision (91.79%). The internal rate of return (IRR), levelized cost of electricity (LCOE), levelized cost of hydrogen (LCOH) of WTEB-W3600 are 34.70%, 0.5172 ¥/kWh, 29.76 ¥/kg. The WTEB hybrid energy system for a large-scale offshore wind power integration is first proposed and the techno-economic feasibility analysis proves the feasibility and forward-looking of the system. Collaborative capacity optimization of OWF, TPP, electrolysis station, battery can improve the system performance and economy. The wind-photovoltaic-thermal-electrolysis-battery (WPTEB) system co-locating the OWF and floating photovoltaic (PV) is an important development direction.

A Dynamic Load Increasing Method for 220 kV Overhead Transmission Lines and Application

With the continuous development of China’s economy, the demand for electricity in society is increasing year by year, and it is necessary to continuously strengthen the construction of transmission capacity. This article aims to develop a terminal monitoring device that can monitor the status of transmission lines and the environment, analyze the monitoring data of overhead line status and micrometeorological data, and, based on the prediction model of the current carrying capacity of transmission lines, fully tap the power supply potential of transmission lines, which is of great significance for improving the transmission capacity of transmission channels.

Optimal Grid Flexibility Assessment for Integration of Variable Renewable-Based Electricity Generation

This study delves into power system flexibility, with a keen focus on the integration of variable renewable electricity generation into power grids. Two scenarios were analyzed. The base scenario revealed an aging grid, insufficient generation capacity, frequent outages, and little renewable energy generation (1.9%), along with a significant (71.23%) loss of load. In contrast, the investment scenario presented solutions including raising VRE capacity to 44%, adding 1000 MW capacity transmission lines, installing 200 MW capacity grid-scale battery storage, and technological enhancements. These interventions effectively eliminated loss of load, reinforcing energy resilience. Investments in CCGPP and grid-scale batteries proved instrumental in mitigating the variability of renewable energy. Improved transmission promised efficient power exchange and regional collaboration. The elimination of annualized energy spills and the removal of ramping constraints marked significant strides in enhancing power system flexibility. This research underscores the pivotal role of grid flexibility in accommodating VRE sources. By implementing the proposed optimal solutions, Afghanistan can lead the way toward a cleaner, more resilient, and more interconnected energy future. These findings offer a replicable framework for addressing similar challenges in integrating renewable energy sources globally and supporting the transition to sustainable and reliable energy.

Optimal Power Flow of Power System with Static VAR Compensator using Moth Flame Optimization with Locational Marginal Price

The determination of a generation unit's locational marginal price (LMP), which depends on our understanding of transmission line capacity and optimal power flow (OPF) based on reality, is crucial to evaluating the performance of the unit and determining its profit. Minimising the total cost of the generators will lower the price of electricity on the market. Since power flow equations are nonlinear, numerical and repetition-based approaches should be used to solve them. The equations in this paper are solved using a Moth Flame Optimization (MFO), and to enhance the performance of the MFO in its structure, for simultaneous calculations of power passing through in transmission lines so that by learning about the capacity of transmission lines, in addition to the optimal power flow becoming a reality, the price of electricity is determined using uniform market pricing, or LMP method. The FACTS device used for the problem is Static Var Compensator (SVC). Finally, values for bus voltages, line losses, power injected to buses, power travelling via lines, total generating costs, and generator profits would be included in the output of the proposed MFO algorithm. Additionally, the results of testing the proposed methodology on the IEEE 30-BUS network reveal improvements on the OPF problem.

Current Limiting Simulation of Magneto-biased Superconducting Fault Current Limiter (SFCL)Applied in 66 kV/10 kV Power Substation in China

The short-circuit fault currents in the large capacity transmission lines pose a challenge to the stability and safety of power system. Magneto-biased superconducting fault current limiter (MBSFCL) is with the advantages of two-stage current limiting, self-triggering and fast recovery so that it can effectively reduce the short-circuit fault current when applied to the urban power system. This paper analyzes the operation principle of MBSFCL and establishes a package type magneto-thermal coupled simulation model of MBSFCL based on MATLAB/SIMULINK. A power system model of a 66 kV/10 kV Zhang Tai Zi power substation which is in Liaoning province in China has been established and the grid-connected simulation applied MBSFCL has been achieved. Moreover, the grid-connected test is carried out, and the results of fault current, quench resistance and temperature change are obtained. The comparison of results between simulation and test verifies the accuracy of the simulation model and the application feasibility of MBSFCL.

Dynamic thermal line rating model of conductor based on prediction of meteorological parameters

This paper developed a new algorithm to predict dynamic thermal line rating to increase the capacity of transmission lines, which can enhance the capacity of wind power integrated to the grid and reduce the curtailment. The proposed dynamic thermal line rating prediction model was trained by analyzing historical meteorological data and conductor physical parameters, and used deep learning with parameters optimized by an optimized algorithm. The prediction accuracy of the model is verified by Mean Absolute Error, R2 and comparison with other models. The simulation results show that the proposed prediction model has a good performance. The suggested dynamic thermal line rating algorithm, which bears resemblance to the actual value, boosts the static thermal line rating by varying degrees of 23% to 75% at different instances throughout the sample. At the same time, this paper designs an optimal power flow economic dispatch objective function. By comparing the economic dispatch of the power grid calculated by adding static thermal line rating and the prediction models, the method proposed in this paper can effectively increase the amount of wind power integration and reduce power generation costs.

Analysis of System Balancing and Wind Power Curtailment Challenges in the Ethiopian Power System under Different Scenarios

In this paper, an hourly dispatch model was developed to analyze the system balancing and wind power curtailment challenges in the future of the Ethiopian electric power grid system. The developed model was validated using historical data and was used for the analysis of the grid system in 2030 with different scenarios. The model was used to examine the impacts of transmission capacity, regulation reserve requirement, and daily minimum generation of hydropower for irrigation with three cases of wind annual energy share of 14.5%, 17.8%, and 25.2%. Thus, the curtailment was found to be below 0.2%, 1.1%, and 9.8% for each case, respectively. The cost of wind energy increases in proportion to the percentage of curtailment and the increase in transmission line capacity. Reducing the minimum hydropower generation results in smaller wind power curtailment and better generation–consumption balancing.

Northern Goshawk Optimization Algorithm for Optimal Power Flow with FACTS Devices in Wind Power Integrated Electrical Networks

Power-operational problems must be resolved with flexible AC transmission systems (FACTS) and optimum power flow (OPF). The complexity of power flow analysis in modern power network models is increased by the unpredictability of renewable energy generating sources in addition to the challenge of determining the appropriate locations and ratings for FACTS devices. FACTS devices can increase the thermal capacity of power transmission lines, enabling the network to accommodate more electricity from renewable sources. The major goals of this study are to lower production costs, decrease power losses, enhance the voltage profile of the system, and enhance load capability. To solve a variety of optimization issues optimally, optimization meta-heuristics approaches have been created in response to the increased emphasis on renewable energy sources, such as wind power. Wind energy is an important component of modern power systems due to its affordability and clean nature. This article presents an OPF method for efficiently scheduling energy from wind farms using the Northern Goshawk Optimization (NGO) meta-heuristic technique. The Weibull probability distribution function is used to represent wind speed and estimate the cost of electricity produced by wind turbines based on the planned power. To validate the NGO approach and its results compared with those of other meta-heuristic optimization techniques, such as Chef-Based Optimization Algorithm, Dingo Optimization Algorithm, and Chameleon Swarm Algorithm, the IEEE system 30-bus is used to solve the OPF problem.

Feasibility of using phase-shifting transformers to increase the throughput of interconnected power transmission systems

This paper discusses measures aimed at improving the efficiency of power systems by increasing the capacity of power transmission lines. To that end, a FACTS technology based on a phase-shifting transformer was used. The feasibility of using phase-shifting transformers to increase the throughput capacity of interconnected power transmission systems was investigated by determining the maximum allowable cross-section flows of the United Energy System of the Urals – the United Energy System of Siberia. The studied cross-section included 500 kV transmission lines and the extended 220 kV Nizhnevartovskaya GRES – Tomskaya transit. Calculations were performed for normal and various post-emergency schemes using the RastrWin3 software package. The regulation of phas e-shifting transformer branches and the direction of power flow in the section were taken into account. For the considered cross -section, the use of a phase-shifting transformer was shown to provide for the 220 kV transit operation in a closed mode. This i mproved the reliability of power supply in the region and allowed the maximum allowable overflow to be increased by 35 – 71%. In addition, similar calculations were carried out for the option of strengthening the 220 kV transit through the construction of a parallel 500 kV line. The effect of increasing the capacity of this option was established to reach 20 –35%. The decisive factor limiting the maximum permissible cross-section flows during 220 kV transit short circuit in the normal and reinforced versions was found to be the current overload of the head sections. Recommendations on the preferable use of an open transit mode are formulated. In conclusion, the efficiency of power systems can be improved by increasing the transmission capacity of power lines through the use of phase-shifting transformers. A segment of the Unified National Power Grid of Russia, where such devices are technologically expedient, was identified.

配電線スリム化を目的としたダイナミックレーティング適用時の蓄電池設備容量評価

Because of a large number of facilities in distribution lines, the rationalization of power distribution equipment is an important issue. In recent years, photovoltaic power generation system (PV) has become increasingly interconnected, so the use of distributed power sources and storage battery to streamline facilities is also being studied. However, large capacity of the storage battery is required to reduce power flow in distribution lines using only the storage battery. Dynamic rating (DR), on the other hand, dynamically changes the current capacity of transmission lines and transformers according to weather conditions and other factors. In this study, the necessary capacity of the storage battery is evaluated by distribution lines according to DR. Furthermore, considering transitional characteristics of the wire temperature about current that it takes several minutes to change after varying current can increase the allowable current capacity in distribution lines based on DR. Since downsizing distribution lines to rationalize distribution facilities increases the impedance in distribution system, there is a problem that the voltage fluctuation becomes large. Therefore, this paper proposes a method for calculating the necessary capacity of storage battery according to DR considering transient temperature change and voltage fluctuations in the distribution system. Then, the necessary capacity of the storage battery is evaluated through numerical simulations based on actual annual data.

Joint Planning Method of Virtual Power Plant for Distributed Generation and Grid in AC-DC Medium and Low Voltage Distribution Network

The high proportion of virtual power plants (VPPs) used for distributed generation may cause problems such as power fluctuations and voltage distribution. In contrast, AC/DC hybrid power grid has strong transmission capacity due to its power information transmission. However, Its power grid structure and the location and capacity of VPP have an impact on the consumption capacity of the system, and the relationship between them are closely coupled. In addition, Under different operation modes, power grids of different voltage levels also have great differences. Therefore, the cooperative planning of medium and low voltage AC and DC distribution networks can improve the transmission capacity of the power grid Further improve the ability of distribution network to consume distributed power, A method is proposed in this paper about siting and capacity determination and AC-DC distribution grid frame transformation planning for medium and low voltage systems. The upper-layer model mainly focuses on AC-DC transformation scheduling in the power grid, distributed node location in the access grid and transmission line transmission capacity, while the lower-layer model effectively communicates with the low-voltage system through information flow and changes the operation of the power grid to a certain extent.The results show that the distributed generation system can reduce the operation cost and improve the overall operation efficiency of the power grid.

A study on behavior of producers, retailers and speculators in futures and day-ahead markets: A Nash equilibrium model

Uncertainties in different parameters such as the output power of renewable energy sources, available capacity of generators, or the condition of grid lines in the future, face market players with financial risks in the power system. Futures contracts are used in parallel with the day-ahead electricity markets to protect market players against financial risks of undesirable price fluctuations. Supplying a demand by both futures and day-ahead markets leads to mutual impacts between these two markets. In this paper, a Nash equilibrium approach is introduced to model the interactions between the futures and day-ahead markets. The proposed model includes producers, retailers, and speculators as market players, the uncertainty in the output power of wind farms (WFs), the possibility of the financial settlement of contracts, market players' risk preferences, and transmission system limitations. Using this approach, the optimal strategy of market players in futures and day-ahead markets, the effects of transmission system congestion on the Nash equilibrium of the system, and the role of the financial settlement of contracts in dealing with the uncertainty of WFs' output power and transmission lines capacity are discussed. Eventually, the behavior of speculators and their impacts on the gaming of other market players are evaluated. Simulation results highlight the role of the financial delivery feature in the effective utilization of futures contracts and the behavior of market players.

Impacts of RPS and FIT on inter-regional power transmission line layout in China: Considerations of high renewable energy penetration

Given China's severely separated renewable energy (RE) supply area and load area, the power transmission capacity across regions restricts RE penetration and is directly affected by RE-related support policies. Thus, a multi-objective optimization model is developed to explore the impacts of changes in renewable portfolio standard (RPS) and feed-in tariff (FIT) policies on the optimal transmission line layout. The model regards the maximization of RE power grid-on and minimization of the total cost for the optimal line layout, transmission capacity, and technology selection. We found that power transmission in "West-to-East" and "North-to-South" is strengthened, with the capacity expected to expand 2.2 times between 2020 and 2040. 2024–2026 is the period with the most new lines. The new line grows when the RPS target increase. Compared with the business-as-usual scenario, in the two scenarios where RPS increased by 10% and 15%, the newly built lines' number could grow by 35% and 21%, respectively. On the contrary, if the FIT subsidy continues beyond 2020, the demand for new line construction may decrease, reducing 480 TWh (FIT2025) and 330 TWh (FIT2040) of RE power on-grid. Further, the penetration proportion of renewable generation could be 55.8%–61.8% in 2040, achieving high penetration of RE in China.

Leveraging the existing German transmission grid with dynamic line rating

The integration of large shares of wind and solar power into the power system benefits from transmission network expansion. However, the construction of new power lines requires long planning phases and is often delayed by citizen protests. As an non-invasive alternative, Dynamic Line Rating (DLR) offers the potential to leverage the existing grid by dynamically adjusting the transmission line capacities to the prevailing weather conditions. In this study, we present the first investment model that includes DLR in a large-scale power system with real-world network data and a high temporal resolution. Using Germany as an example, we show that a system-wide integration of DLR improves the integration of existing and additional renewables while reducing grid congestion. The evolving synergies between DLR and increased wind generation result in total cost savings of about 3% of all system costs for a scenario with 80% renewable power production, mainly due to reduced storage and solar capacity needs. If considering a fully decarbonized electricity system, the cost savings from DLR amount to up to 5.5% of the system costs, i.e. 4 billion Euro per year. Our results underscore the importance of a rapid implementation of DLR in power systems to support the energy transition and relieve grid congestion.

Предел передаваемой мощности управляемой линии электропередачи высокого напряжения для режимов на границе статической устойчивости

The use of series compensation devices is one of the methods to increase the capacity of a power transmission line. In addition, the use of controlled series compensation devices affects the steady-state stability of the electric power system. It is also widely known that automatic excitation control of generators has a positive effect on the stability of the system. Thus, it is reasonable to analyze the influence of the adjustable parameters of the controlled series compensation device on the line capacity when considering modes at the boundaries of the stability regions, taking into account automatic excitation controllers on synchronous generators of the power plant. Methods of mathematical modeling of the electric power system, the theory of long-distance power lines and electromechanical transients, methods of analyzing the stability of electric power systems are used. The original software in the C ++ programming language is used as a modeling tool. The authors have selected the regulation laws parameters of controlled series compensation device and automatic excitation controller, provided that steady-state stability is maintained. The stability regions of the electric power-engineering system under study are constructed depending on the tuning parameters of the considered devices. A technique is proposed to select the coefficients of complex regulation of the devices to increase the capacity of a high-voltage power transmission line. The proposed method of the complex selection of regulation coefficients of controlled devices provides the possibility of obtaining their optimal values in a controlled electric power system to ensure stability.

Mitigating Low-Frequency Oscillations and Enhancing the Dynamic Stability of Power System Using Optimal Coordination of Power System Stabilizer and Unified Power Flow Controller

The integration of a flexible alternating current transmission system (FACTS) and a power system stabilizer (PSS) can increase dynamic stability. This paper presents the enhancement of power system dynamic stability through the optimal design of a power system stabilizer and UPFC using an ant lion optimization (ALO) technique to enhance transmission line capacity. The gained damping ratio, eigenvalue and time domain results of the suggested ALO technique were compared with a base case system, ALO-based PSS and ALO-based PSS-UPFC to test the effectiveness of the proposed system in different loading cases. Eigenvalues gained from an ant lion approach-based UPFC with a PSS and a base case system are compared to examine the robustness of the ALO method for various loading conditions. Thus, this paper addresses the mechanism regarding the power system dynamic stability of transmission lines by integrating the optimal size of a PSS and UPFC into the power system. Therefore, the main contribution of this manuscript is the optimal coordination of a power system stabilizer, power oscillation damper and unified power flow using ant lion optimization for the mitigation of low-frequency oscillation.

Determining the Transmission Capacity of Existing Transmission Lines Under High Wind Generation Conditions

Determining the transmission capacity of existing transmission lines is determine by the conductor current. Transmission line can withstand current below thermal standpoint limit to avoid irreparable damage to conductor. The maximum value of current can be determined with static approach (STR – Static Thermal Rating) and dynamic approach (DTR - Dynamic Thermal Rating). STR is defined by simple calculations and does not change often throughout the year where the DTR is calculated for in time conditions taking into account atmospheric conditions, conductor geometry and conductor current. Most common approach to calculate conductor temperature is done by applying IEEE standard (IEEE 738, 2012) or CIGRE (TB601, 2014). Most congestion in the transmission network occurs during the higher production from wind farms when the wind have significant speed. It is to be expected that similar meteorological conditions (wind speed and direction) will occur on transmission lines in the immediate geographical area of wind power plants. In this paper, analysis of relations between atmospheric parameters (wind speed and direction, ambient temperature and solar radiation) and ampacity is described as functional dependence. Taking historical weather data from meteorological stations, atmospheric conditions on transmission line corridors and taking account the frequency of occurrence of individual meteorological variations ampacity of conductor will be determined. For such determined conditions that are influenced by a certain parameters variation of ampacity have a different rating scales. The obtained results will provide an insight into the current ampacity and the possibilities of the transmission line capacity during the high engagement of wind power plants.

Electricity supply chain hybrid long‐term demand forecasting approach based on deep learning—a case study of basic metals industry

AbstractDemand forecasting is a key parameter to achieve optimal supply chain management at different levels. The basic metals industry is one of the most energy‐intensive industries in the electricity supply chain. The impossibility of large‐scale energy storage, reservation constraints, and its high costs, limitations on electricity transmission lines capacity, real‐time response to high priority strategic demands, and variety of energy rates at different hours and seasons are issues that challenge the electricity supply chain. A hybrid approach is presented in this paper to improve the accuracy of long‐term demand forecasting in the electricity supply chain. The proposed approach uses wavelet decomposition and long short‐term memory (LSTM) neural networks to produce new predictors for demand forecasting in case of defective data. The data used in this study consists of the recorded hourly demand of Espidan Iron Stone (EIS) company and data of Mobarakeh Steel (MS) company in Isfahan Province. The understudy time series includes a lot of interruptions due to non‐production of the factory or power outages and spikes which cause uncertainty that makes the forecasting more difficult in comparison with continuous time series. Multiple machine learning models including decision trees (DTs), boosted and bagged trees (BGTs), support vector regression (SVR) models, extreme learning machines (ELMs), and a LSTM neural network model are employed to evaluate the effectiveness of the proposed approach in this paper. A comparison of the results obtained using the hybrid proposed approach and training machine learning (ML) methods shows a notable reduction in forecasting error.