Transfer Capability Evaluation Research Articles

Linearized AC power flow model based interval total transfer capability evaluation with uncertain renewable energy integration

Total transfer capability (TTC) evaluation plays an essential role in guaranteeing reliable power transactions in a deregulated electricity market. However, the large-scale integration of wind power brings significant challenges to TTC calculations. The conventional probabilistic TTC evaluation methods are highly dependent on the pre-defined probabilistic distributions of the input random variables, which could not be accurately predicted in practical situations. This paper proposes an interval TTC evaluation method based on the linearized AC power flow (LACPF) model, which can provide intuitive TTC boundary information without any prior distributions. The adoption of LACPF also contributes to yielding more accurate TTC values than those DC power flow (DCPF) based methods. The proposed interval optimization model is equivalently translated into an optimistic model and a pessimistic model. The optimistic model is formulated as a max-max problem and can be directly converted to a single-level linear programming model. The pessimistic model is formulated as a min-max problem that cannot be solved directly. Hence, the strong duality theory and the big-M method are introduced to transfer the original bilevel model into a single-level mixed integer linear programming (MILP) model for an efficient solution. The proposed method is validated on the IEEE 118-bus system and a modified actual power grid in Northwest China. Numerical results demonstrate its computational efficiency.

Interval Total Transfer Capability for Mesh HVDC Systems Based on Sum of Squares and Multi-Dimensional Holomorphic Embedding Method

Total transfer capability evaluation is an effective method to analyze the backbone transmission capability among regions. To address renewable energy uncertainties, an interval total transfer capability model based on the multi-dimensional holomorphic embedding method and sum of squares relaxation technique is proposed to solve the regional total transfer capability in meshed high voltage direct current systems. First, the multi-dimensional holomorphic embedding method is used to derive the analytical expressions of regional tie lines. Second, the interval total transfer capability model can be reformulated by two bi-level optimization models. Third, sum of squares relaxation is employed to solve the two optimization problems. Numerical results on a 40-bus European Synthetic System and the Chinese meshed high voltage direct current system validate the effectiveness of the proposed model and method.

Available transfer capability evaluation in electricity-dominated integrated hybrid energy systems with uncertain wind power: An interval optimization solution

Available transfer capability (ATC) is widely used in the deregulated electricity market to ensure secure and reliable power trading among market participants. However, most conventional ATC calculation methods do not fully consider the impacts of renewable energy integration and the close interdependency among electricity, natural gas, and district heating networks. To overcome these challenges, this work evaluates the ATC in an electricity-gas-heating integrated hybrid energy system (IHES) in a more practical manner by considering renewable energy uncertainties. In the proposed approach, the detailed models of electricity, natural gas, and district heating infrastructures are provided and their operational constraints are fully respected. To reduce input data requirements, the wind power uncertainty is modeled as interval bounds instead of detailed probability distribution functions (PDFs). Consequently, this interval optimization-based ATC model is converted to two sub-problems to solve the lower and upper boundaries of the objective function value. The proposed approach provides a quantitative approach to numerically calculate the impact on ATC from various components in an IHES. Simulation results on the IHES 5–7-6 and the IHES 118–96-6 + 32 systems validate its effectiveness.

Interpretable Neighborhood Deep Models for Online Total Transfer Capability Evaluation of Power Systems

Deep learning is considered to be a promising method for total transfer capability (TTC) evaluation due to its high speed and accuracy for nonlinear and complicated problems. However, the operating scenarios of power systems are complex and ever changing. It is difficult to train a single deep model using an overly complex dataset containing operating scenarios with high variability. In addition, making the deep model transparent to validate for operators is another challenge to its application in the power system. To enable the practical application of deep models in TTC evaluation, the operating sample space is clustered into simpler spaces via a two-stage clustering method, and the idea of neighborhood model for the deep TTC evaluation network (DTEN) is proposed. Then, the local post hoc interpretability for the DTEN based on first-order control variable sensitivity is presented. During the interpretability analysis, the quasi-steady state is introduced to assess the coupling effects among different inputs. Case studies on the IEEE 39-bus system and a real-world regional system in China validate the effectiveness of the proposed method.

Total transfer capability assessment of HVDC tie‐lines in asynchronous grids

This paper discusses how frequency-stable operational decision-making of asynchronous grids with intensive high-capacity HVDC tie-lines, can be achieved leveraging a novel total transfer capability (TTC) evaluation approach. This problem is formulated as a hierarchical optimization model with multiple decision-makers, in which the master problem is solved by the coordinator to determine the base case maximum acceptable transmission power of each HVDC tie-line, while the sending- and receiving-end grid's local TSO each autonomously solves a frequency constrained optimal power flow sub-problem. Coordinated fast and slow frequency arrest strategies are fully integrated into the TTC assessment framework, which not only ensure that last-resort protections are not triggered following the HVDC bi-pole block contingency, but also take advantage of the potential control capability of the sending- and receiving-end grids and would therefore increase the TTC of HVDC tie-lines. A decentralized algorithm based on accelerated analytical target cascading is developed to solve the formulated model. Case studies on a modified two-area RTS-96 system and a practical large-scale system demonstrate the effectiveness of the proposed approach.

Probabilistic Available Transfer Capability Evaluation Considering Dynamic Line Rating Based on a Sequential Game-Theoretic Approach

Available transfer capability (ATC) plays an essential role in deregulated power network scheduling. This value determines the power that can be transferred between deregulated regions. The ATC value is limited by transmission line constraints and reliability marginal terms. In this article, the impact of dynamic line rating (DLR) instruments, which are generally used to enhance the capacity of transmission lines, on the ATC is investigated. In addition, a robust ATC evaluation model is proposed to find worst cases for determining the reliability marginal terms and considering them in the ATC evaluation. The robust ATC evaluation model includes a master problem, formulated to determine ATC and total transfer capability, as well as two bilevel subproblems, formulated to find the reliability marginal terms. The Benders decomposition algorithm is derived to solve the proposed robust ATC evaluation. An uncertain environment, including wind farm powers, dynamic line capacities, and load demand values, is also considered to cover the stochastic nature of such uncertainty sources. A probabilistic approach is proposed to calculate the expected value of ATC and depict the cumulative distribution function of each variable. The proposed probabilistic model is based on dividing the stochastic set into smaller groups, similar to clustering techniques. However, the significant differences between the proposed probabilistic and cluster-based models are due to detecting the optimal value of a reduced number of stochastic sets and finding the members of each cluster set. In other words, a sequential game-theoretic approach is applied to divide the data into smaller sets. The impact of DLR on the proposed robust ATC evaluation problem and the efficiency of the proposed probabilistic model are evaluated by comprehensive studies based on the IEEE 118-bus test system.

Day ahead dynamic available transfer capability evaluation incorporating probabilistic transmission capacity margins in presence of wind generators

Day ahead dynamic available transfer capability evaluation incorporating probabilistic transmission capacity margins in presence of wind generators

An efficient holomorphic embedded based approach for available transfer capability evaluation

Available Transfer Capability (ATC) is the additional power that can be securely and reliably transacted over and above the already committed transactions in a power network. In the electricity market, where every player (power producer and consumer) tries to earn higher profit, quick and accurate assessment of ATC of the power network is a prime concern. Holomorphic Embedding (HE) is a novel and non-iterative way of solving the Power Flow (PF) equations, which guarantees to find the operational High Voltage (HV) solution, in case it exists. Analytic continuation extends the domain of convergence of non-analytic functions to have voltage solutions. This paper, thus, proposes an extremely efficient and accurate approach for evaluation of ATC using the Holomorphic Embedded PF (HEPF) considering the intact system condition and N-1 contingency situations. This approach is successfully tested on IEEE 30 bus, IEEE 118 bus, and IEEE 300 bus systems for various bilateral and multilateral transactions. The results, thus, obtained prove the efficacy of the proposed approach in comparison with those obtained from the repeated Newton-Raphson PF (NRPF), Fast Decoupled PF (FDPF) and Continuation PF (CPF) based methods.

Synchrophasor measurement‐based approach for online available transfer capability evaluation

This study proposes a synchrophasor measurement-based approach for online available transfer capability (ATC) evaluation. It utilises an expression which correlates the nodal power injections to the line flows. A new set of measurement-dependent injection distribution factors (MDIDFs) has been computed using this expression. The measurements, obtained from optimally placed phasor measurement units, are used to carry out linear state estimation (LSE). The voltage phasors of all system buses, obtained by LSE, are required to compute the MDIDFs. ATCs for bilateral and multilateral transactions are directly evaluated using these MDIDFs for system intact and contingency cases. If required, the MDIDFs can also be used to directly compute AC power transfer distribution factors and line outage distribution factors without factorising the Jacobian of AC power flow (ACPF). The proposed approach has been validated in real-time digital simulator at different system operating points of WSCC 9-bus and IEEE 14-bus systems. Simulations are also performed on an Indian 246-bus Northern Regional Power Grid system to demonstrate the effectiveness of the proposed approach. The results thus obtained, when compared with those evaluated through repeated ACPF-based approach, prove the efficacy of the proposed approach.

Interval Optimization for Available Transfer Capability Evaluation Considering Wind Power Uncertainty

In deregulated electricity markets, available transfer capability (ATC) provides valuable information for market participants, because ATC indicates the remaining amount of power that can be transferred between different areas over already committed capacity. Under the paradigm of renewable power with uncertainty, it is reasonable to apply probabilistic ATC evaluation. However, the probabilistic distribution of uncertainty is not always readily available. In this paper, an interval optimizationbased model is proposed for ATC evaluation that only requires the bounds of uncertainty without the precise data of wind power probabilistic distribution. The purpose of introducing interval optimization is to determine the possible ATC range considering wind power uncertainty. In the proposed method, the original interval-based model is first decomposed into a lower boundary (optimistic) model and an upper boundary (pessimistic) model. Then, strong duality theory and a big-M algorithm are applied to convert the combinatorial max-min problem in the pessimistic model to a single level maximization problem for efficient calculations. The proposed methodology is implemented on the PJM 5-bus and IEEE 118-bus systems. Simulation results validate its effectiveness.

Available transfer capability evaluation in a deregulated electricity market considering correlated wind power

Evaluation of available transfer capability (ATC) is a complicated process involving the determination of the total transfer capability (TTC) and the existing transfer commitments (ETC). Considering the uncertain renewable generation such as wind power will bring more challenge to this process. Previously the uncertainty of wind power is considered either in the ED model or the following TTC calculation, but not included in two process simultaneously. Therefore, the ATC output may not be accurate since the uncertainty impact two problem simultaneously. To consider the uncertainty and correlation of wind power in both ISO's ED and ATC evaluation, this paper proposes a bi-level optimization framework in which the ATC evaluation is formulated as the upper level problem and the ED is the lower level. The bi-level model is first converted to a mathematic program with equilibrium constraints (MPEC) by recasting the lower level problem as its Karush-Kuhn-Tucker (KKT) optimality conditions, and then transformed to a mixed-integer linear programming (MILP) problem which can be solved by existing optimization tools. Case studies on the PJM 5-bus and IEEE 118-bus systems are presented to verify the proposed methodology and the impacts of correlation of wind power on ATC are analysed.

Available transfer capability evaluation and enhancement using various FACTS controllers: Special focus on system security

Abstract Nowadays, because of the deregulation of the power industry the continuous increase of the load increases the necessity of calculation of available transfer capability (ATC) of a system to analyze the system security. With this calculation, the scheduling of generator can be decided to decrease the system severity. Further, constructing new transmission lines, new substations are very cost effective to meet the increasing load and to increase the transfer capability. Hence, an alternative way to increase the transfer capability is use of flexible ac transmission system (FACTS) controllers. In this paper, SSSC, STACOM and UPFC are considered to show the effect of these controllers in enhancing system ATC. For this, a novel current based modeling and optimal location strategy of these controllers are presented. The proposed methodology is tested on standard IEEE-30 bus and IEEE-57 bus test systems with supporting numerical and graphical results.

Bi-Level Optimization for Available Transfer Capability Evaluation in Deregulated Electricity Market

Available transfer capability (ATC) is the transfer capability remaining in the physical transmission network for further commercial activity over and above already committed uses which needs to be posted in the electricity market to facilitate competition. ATC evaluation is a complicated task including the determination of total transfer capability (TTC) and existing transfer capability (ETC). In the deregulated electricity market, ETC is decided by the independent system operator’s (ISO’s) economic dispatch (ED). TTC can then be obtained by a continuation power flow (CPF) method or by an optimal power flow (OPF) method, based on the given ED solutions as well as the ETC. In this paper, a bi-level optimization framework for the ATC evaluation is proposed in which ATC results can be obtained simultaneously with the ED and ETC results in the deregulated electricity market. In this bi-level optimization model, ATC evaluation is formulated as the upper level problem and the ISO’s ED is the lower level problem. The bi-level model is first converted to a mathematic program with equilibrium constraints (MPEC) by recasting the lower level problem as its Karush-Kuhn-Tucher (KKT) optimality condition. Then, the MPEC is transformed into a mixed-integer linear programming (MILP) problem, which can be solved with the help of available optimization software. In addition, case studies on PJM 5-bus, IEEE 30-bus, and IEEE 118-bus systems are presented to demonstrate the proposed methodology.

Power System Node Loadability Evaluation Using Flexibility Analysis Method

System transfer capability evaluation is an important research topic in power system analysis. However, as the uncertainty of load increasing direction, researches on the upper bound of system transfer capability appear to be too optimistic, whereas researches on the lower bound of system transfer capability appear to be too pessimistic. Actually, as load increasing direction cannot be forecasted accurately in practical power systems, obvious flaws in evaluating system transfer capability using deterministic analysis methods exist. In this paper, a method is proposed to give an approximate evaluation on power system node loadability using flexibility analysis method. Conventional rigid node voltage constraints are expressed into flexible form, and a set of critical node voltage values are obtained by solving a standard nonlinear optimization model using interior point algorithm. With the adjustment strategies given, such critical node voltage values show a strong positive correlation with the loadability on the corresponding nodes. Besides, compared with conventional methods, the method proposed can significantly improve the calculation efficiency for the same research purpose. Case study on IEEE 30-bus test system validates the effectiveness of the method proposed. DOI: http://dx.doi.org/10.5755/j01.eee.20.6.7267

Implementation of an Intelligent Grid Computing Architecture for Transient Stability Constrained TTC Evaluation

An intelligent grid computing architecture is proposed and developed for transient stability constrained total transfer capability evaluation of future smart grid. In the proposed intelligent grid computing architecture, a model of generalized compute nodes with 'able person should do more work' feature is presented and implemented to make full use of each node. A timeout handling strategy called conditional resource preemption is designed to improve the whole system computing performance further. The architecture can intelligently and effectively integrate heterogeneous distributed computing resources around Intranet/Internet and implement the dynamic load balancing. Furthermore, the robustness of the architecture is analyzed and developed as well. The case studies have been carried out on the IEEE New England 39-bus system and a real-sized Chinese power system, and results demonstrate the practicability and effectiveness of the intelligent grid computing architecture.

Erratum to: Energy Field Simulating of Heat Transfer Capability and Damage Evaluation on an Improved Langmuir Probe

In this paper we proposed a advanced Langmuir probe (LP)—cooling monoblock (CM) model used in Tokamak of controlled thermonuclear fusion, this model adopted several novel designs used for improving the heat transfer capability. In the transient thermal analysis, the effect of conical degree of AL2O3 ceramic barrel on the thermal contact resistance at the interface of different materials has been systematically studied and a reasonable explanation was given for the phenomenon where the increasing of conical degree lead to the decreasing of thermal contact resistance. Moreover the top part of CM of the plasma facing unit was prepared by pyrolytic graphite can make the temperature of LP obviously reduced. Eventually the thermal state of LP during the 400 s pulse are figured out by ANSYS under optimal loading conditions, the calculation results showed the maximum temperature of LP is 2,253°C at 211 s, meanwhile, the basic characteristics for variation of the maximum temperature of LP with the incident heat flux are presented. These results obtained in this work are helpful to reveal the thermal energy state of LP more accurately, reduce the damage on the device, and improve its working stability.

Energy Field Simulating of Heat Transfer Capability and Damage Evaluation on an Improved Langmuir Probe

Energy Field Simulating of Heat Transfer Capability and Damage Evaluation on an Improved Langmuir Probe

Differential evolution based method for total transfer capability evaluation

The application of Differential Evolution (DE) to compute the Total Transfer Capability (TTC) in deregulated market is proposed in this paper. The objective is to maximize a specific point-to-point power transaction without violating system constraints using DE. This algorithm is based on full ac optimal power flow solution to account for the effects of active and reactive power flow, voltage limits, and line flow limits. The real power output of generators in source area and the real power of the loads in the sink area were adjusted to obtain the maximum transfer capability. In order to calculate TTC more accurately, Transmission Reliability Margin is incorporated in the calculation of TTC by considering single and multiline outages and also a three phase to ground fault near a bus and clearing it by isolating the faulty line after certain time interval. The performance of the proposed method is tested on the modified IEEE-30 bus system and results are compared with that of Particle Swarm Optimization method (PSO). Further, the results are compared with other published results using CPF and EP. It is found that DE provides more reliable results than other methods. Keywords: Total transfer capability, available transfer capability, transmission reliability margin, differential evolution, particle swarm optimization.

RELIABILITY MANAGEMENT AND IMPROVEMENT FOR PLANNING AND OPERATIONAL PROCESS ENHANCEMENT MEASURES IN DEREGULATED POWER SYSTEMS USING ATC

In this paper, beginning with a concise overview of the Available Transfer Capability (ATC) evaluation methods, we make a proposition for reliability management in the planning horizon of deregulated power systems through the concept of Adequacy Resiliency. The derived indices are meant as indicators of adaptability of power systems to ensure the required reliability levels. Improvements to this conceptualization upon the deployment of Flexible AC Transmission System (FACTS) devices are then put forward. We also explore the option of employing the created indices to the operational horizon of power systems, explaining the means of market enhancement. Core reliability issues arising out of the usage of FACTS are then discussed.

Available Transfer Capability Evaluation Based on Sensitivity Analysis

Abstract According to the definition of Available Transfer Capability by North America Electric Reliability Council (NERC), we know that ATC not only depends on the topology of power network but also on the parameters of components. So a series of adequacy indices are proposed to evaluate ATC. Through thorough analyses on these indices, the sensitivities of components parameters to these adequacy indices are deduced. The impact of components parameters’ small variations on ATC can be reflected by these sensitivities, the importance degree of each component can be embodied. Furthermore, by sensitivity analysis we can effectively identify ATC bottlenecks and get important guide information for operation and planning. The algorithm based on MATLAB 6.5 is developed. The correctness and effectiveness of the proposed sensitivity analysis method are verified using IEEE-RTS79 test system.