Assessment Of Available Transfer Capability Research Articles

Available Transfer Capability Assessment of Multiarea Power Systems with Conditional Generative Adversarial Network

Available transfer capability (ATC) is an important measurement index to evaluate the security margin of interconnected power grids and serve as a reference for the transmission right transaction. In modern power systems, ATC is affected by the transmission network topology, renewable power output uncertainty, and load demand uncertainty. Traditional works usually model the power source-load uncertainty by using robust optimization, interval optimization, or chance-constraint optimization, which cannot fully reflect the probabilistic distribution of the daily source-load uncertainty. This paper proposes an ATC assessment methodology based on the typical stochastic scenarios of renewable output and load demand of multiarea power systems. Furthermore, the conditional generative adversarial network (CGAN) algorithm is adopted to generate and select representative scenario sets based on historical raw data, which can fully reflect the usual operating condition of a system with high renewable energy penetration. The scenario set that is fed into the ATC assessment model can fully characterize the impact of source-load uncertainty on daily ATC. Finally, the proposed method is verified by a modified three-area IEEE 9-bus system and a real-world provincial power system.

Probabilistic Assessment of Available Transfer Capability Incorporating Load and Wind Power Uncertainties

This study proposes an available transfer capability (ATC) assessment approach in an intraday market that would enable wind energy participants to raise their level of integration without exposing them to high risk. The presented methodology allows the transmission system operator (TSO) to assess ATC near to the real state while considering voltage stability concerns as well as the uncertainties of the forecasted load and wind power. The proposed formulation is designed so that the existing VAR sources are appropriately exploited during the ATC assessment to maximize its anticipated value and boost the transaction between various zones. To alleviate the complexity of analyzing N-1 contingencies in the ATC estimation, a linear sensitivity technique is applied for ranking the most severe contingencies to be examined carefully. A two-level hybrid algorithm using the primal-dual interior point method (PDIPM) and an improved grey wolf optimizer (IGWO) is suggested for solving the problem. The performance of the proposed approach has been evaluated by its application on IEEE 30-reliability test system (RTS). The outcomes confirm the viability of the proposed approach for optimizing ATC value for various transactions through the best use of installed VAR devices, considering different locations of wind farms. The obtained findings also demonstrate the effectiveness of the suggested method for determining the most severe contingency associated with each scenario under consideration.

Assessment of the influence of wind energy incorporated capacity benefit margin in ATC computation

Available transfer capability (ATC) is an important metric used to measure the techno-economic viability of the transmission networks. Several methods have been presented in literature for ATC assessment, however, only some few articles incorporate CBM in ATC calculation and those few papers only considered conventional power generation sources in CBM evaluation. CBM is a function of the reliability of generating units. This paper presents the inter-area CBM calculation in the presence of wind energy source using graph theory technique and the results are incorporated in ATC computation using repeated power flow. CBM is incorporated in ATC computation as non-recallable and recallable power transfers. The results with and without CBM incorporation, in the presence of wind power system, are compared. The contribution of the paper is to study the influence of wind power (WP) integrated CBM on ATC evaluation. The results showed that the incorporation of CBM, in the presence of renewable energy, has a significant influence on ATC, without which ATC would be inaccurately estimated. Simulations using IEEE 24-Bus RTS is used to implement the proposed approach. This approach can be employed by transmission operators to assess the technoeconomic viability of the power network for possible power transactions.

A Data-Driven Sparse Polynomial Chaos Expansion Method to Assess Probabilistic Total Transfer Capability for Power Systems With Renewables

The increasing uncertainty level caused by growing renewable energy sources (RES) and aging transmission networks poses a great challenge in the assessment of total transfer capability (TTC) and available transfer capability (ATC). In this paper, a novel data-driven sparse polynomial chaos expansion (DDSPCE) method is proposed for estimating the probabilistic characteristics (e.g., mean, variance, probability distribution) of probabilistic TTC (PTTC). Specifically, the proposed method, requiring no pre-assumed probabilistic distributions of random inputs, exploits data sets directly in estimating the PTTC. Besides, a sparse scheme is integrated to improve the computational efficiency. Numerical studies on the modified IEEE 118-bus system demonstrate that the proposed DDSPCE method can achieve accurate estimation for the probabilistic characteristics of PTTC with a high efficiency. Moreover, numerical results reveal the great significance of incorporating discrete random inputs in PTTC and ATC assessment, which nevertheless was not given sufficient attention.

ATC assessment and enhancement of integrated transmission and distribution system considering the impact of active distribution network

Assessment and enhancement of transmission network capability have been one of the prime interests of power system monitoring, operation and control. Conventionally, the issue of available transfer capability (ATC) assessment has been tackled considering the transmission and distribution networks as segregated entities because they had little or no influence on each other's performance owing to the unidirectional flow of power from the transmission to distribution networks. Now, with increasing interest in smart transmission and distribution in amalgamation with a paradigm shift in sources of generation from centralised to decentralised even at distribution levels mandating the analysis of power grid while inculcating both the hierarchies simultaneously. In this study, a platform for quasi-static operation of power transmission and distribution networks, employing a multi-agent based system has been developed. The developed multi-agent systembased system has been utilised for assessment of ATC considering active distribution network (ADN) whereby Modified IEEE 24 bus system at transmission and Modified IEEE 123 node system at distribution level has been considered as a test system. It has been observed that the presence of ADN considerably affects the ATC of the system.

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.

Assessment of Available Transfer Capability in the Electricity Market

Assessment of Available Transfer Capability in the Electricity Market

Distributed Probabilistic ATC Assessment by Optimality Conditions Decomposition and LHS Considering Intermittent Wind Power Generation

This paper investigates a probabilistic assessment of available transfer capability (ATC) by optimality condition decomposition (OCD) techniques and latin hypercube sampling (LHS) method in power systems with penetration of wind energy resources. First, the ATC assessment is mathematically formulated as a non-linear optimal power flow problem. Then, an iterative decomposition-coordination methodology based on OCD techniques is conducted for distributed assessment of the ATC. In order to estimate the probability density function and empirical cumulative density function under wind power fluctuations, LHS method is utilized for obtaining samples of the integrated wind power sources. Next, wind power samples are appended into the proposed decomposition-coordination approach to provide a fast LHS-based Monte Carlo (MC) simulation of the ATC at the current system state. In order to provide a preliminary approximation of the range variation of the ATC before executing the MC technique, OCD-based distributed computations of the average-case, best-case, and worst-case scenarios subjected to wind power variations are developed by following three approaches: first, assuming that the average-case of the ATC occurs at the mean power output of integrated wind farms, second, adding box-constraints related to the power output of each wind farm in order to estimate the best-case scenario, and third, developing an iterative sensitivity-based scheme to estimate the worst-case scenario. Numerical experiments in the standard IEEE 118-bus system demonstrate the correctness of the proposed distributed probabilistic ATC assessment.

Optimal Available Transfer Capability Assessment Strategy for Wind Integrated Transmission Systems Considering Uncertainty of Wind Power Probability Distribution

Wind power prediction research shows that it is difficult to accurately and effectively estimate the probability distribution (PD) of wind power. When only partial information of the wind power probability distribution function is available, an optimal available transfer capability (ATC) assessment strategy considering the uncertainty on the wind power probability distribution is proposed in this paper. As wind power probability distribution is not accurately given, the proposed strategy can efficiently maximize ATC with the security operation constraints satisfied under any wind power PD function case in the uncertainty set. A distributional robust chance constrained (DRCC) model is developed to describe an optimal ATC assessment problem. To achieve tractability of the DRCC model, the dual optimization, S-lemma and Schur complement are adopted to eliminate the uncertain wind power vector in the DRCC model. According to the characteristics of the problem, the linear matrix inequality (LMI)-based particle swarm optimization (PSO) algorithm is used to solve the DRCC model which contains first and second-order moment information of the wind power. The modified IEEE 30-bus system simulation results show the feasibility and effectiveness of the proposed ATC assessment strategy.

Probabilistic-Based Available Transfer Capability Assessment Considering Existing and Future Wind Generation Resources

This paper presents a probabilistic-based approach for available transfer capability (ATC) assessment. A composite algorithm is developed to generate ensembles of future wind generation scenarios for the existing and planned wind sites using both measured and model-produced wind data. Then, the ensembles of wind and load are used to calculate their respective probability density functions (pdfs), which are subsequently used to calculate the probabilistic-based ATC for a selected transmission corridor. The method has been tested and validated using historical and operational data provided by the Idaho Power Co. The results show that the method can effectively quantify the uncertainties in the ATC assessment introduced by variable generation resources and load variations. As a result, the grid planners will inform the likelihood for the transmission corridor to exceed its transfer capacity in any targeted future years as well as the duration of such events.

Iterative Distributed Algorithms for Real-Time Available Transfer Capability Assessment of Multiarea Power Systems

This paper studies iterative distributed algorithms for real-time available transfer capability (ATC) assessment in energy management systems of multiarea power systems. Since ATC calculations can be modeled as a special nonlinear optimal power-flow problem, iterative decomposition-coordination approaches based on constrained augmented Lagrangian methods can be applied. One special distributed scheme, called the auxiliary problem principle method, will be studied for distributed ATC assessment in this paper. A computation framework of this distributed algorithm is investigated. System partition with nonoverlapping and boundary sub-systems will also be studied. Simulations of several IEEE test systems will be conducted to validate the feasibility and the correctness of this distributed ATC. In addition, the real-time monitoring and reaction mechanism of this distributed algorithm will also be demonstrated by numerical experiments.

Credibility Theory-Based Available Transfer Capability Assessment

Since the development of large scale power grid interconnections and power markets, research on available transfer capability (ATC) has attracted great attention. The challenges for accurate assessment of ATC originate from the numerous uncertainties in electricity generation, transmission, distribution and utilization sectors. Power system uncertainties can be mainly described as two types: randomness and fuzziness. However, the traditional transmission reliability margin (TRM) approach only considers randomness. Based on credibility theory, this paper firstly built models of generators, transmission lines and loads according to their features of both randomness and fuzziness. Then a random fuzzy simulation is applied, along with a novel method proposed for ATC assessment, in which both randomness and fuzziness are considered. The bootstrap method and multi-core parallel computing technique are introduced to enhance the processing speed. By implementing simulation for the IEEE-30-bus system and a real-life system located in Northwest China, the viability of the models and the proposed method is verified.

Fast Assessment of Available Transfer Capability Using Synchrophasor Measurements

In an electricity market, power transmission networks allow power flow that is required to meet different bilateral and pool contracts between customers and suppliers. To ensure power system security, transactions are permitted to the point that the system design and operating conditions are not violated. This article presents a new method for determining the available transfer capability of the transmission system with respect to a particular transaction or flow gate using synchrophasor measurements. The method also utilizes a DC power flow based sensitivity concept. The proposed method is simple, fast, and well suited for real-time applications. The effectiveness of the proposed method is tested on the New England 39-bus test system, IEEE 24-bus reliability test system, and 246-bus Northern Region Power Grid Indian systems.

Assessment of Available Transfer Capability for Congestion Management in Restructured Electrical Power Network for Competent Operation

Congestion is the prime cause of problems, due to open access of power system. The AC Power Transmission Congestion Distribution factor (PTCDF) is suitable for computing change in any line quantity for a change in MW bilateral transaction. The proposed PTCDF method is more accurate as compared to the DC power distribution factor. With PTCDF ATC can be calculated. After calculating ATC it is possible to know the valid multiple transaction on power system. With the help of ATC calculations congestion problem can be solved in restructured electrical power network. The paper presents the method for calculating ATC using PTCDF.

Probabilistic assessment of available transfer capability considering spatial correlation in wind power integrated system

With the increasing integration of wind farms, modification of current tools for evaluating and managing power systems such as available transfer capability (ATC) becomes an important issue. This study presents a computationally accurate and efficient method in evaluating ATC with large amount of uncertainty based on Latin hypercube sampling (LHS) and scenario clustering techniques. LHS is used in Monte Carlo simulation to select a system state with high sampling efficiency and good precision. Cholesky decomposition is combined into the sampling process to deal with the dependencies among input random variables. The sampled scenarios are clustered by vector quantification clustering algorithm, which contributes to the fast calculation of ATC evaluation for numerous scenarios. Finally, a sensitivity method based on optimal power flow is proposed for the clustered scenarios. The case studies, with the IEEE reliability test system, illustrate the advantages of the proposed method that largely reduces the computation burden under the premise of ensuring its accuracy. The results also verify the obvious enhancement of spatially correlated wind power on the volatility of ATC.

Monte Carlo simulation and bootstrap method based assessment of available transfer capability in AC–DC hybrid systems

In practical power markets, available transfer capability (ATC) can provide important information for all parts of power market participants and the assessment of ATC should be carried out instantly. As high voltage direct current (HVDC) systems have been extensively used in modern power systems, less work has been done on evaluation of ATC in AC–DC hybrid power systems. This paper is dealing with the evaluation of ATC for the integration of HVDC link with an AC power system. The mathematical model of ATC for AC–DC hybrid power system is formulated. Considering the time-varying and uncertainties of the power system, several statistical indices are presented to evaluate ATC. A novel approach combined Monte Carlo simulation with bootstrap method is proposed to calculate these statistics. Sequential solution method is employed to deal with the AC–DC power flow and golden section search method is used to accelerate convergence of load flow. The algorithm is developed in the environment of MATLAB R2008a with MATPOWER. Case studies with a modified IEEE RTS-79 24-bus AC–DC hybrid power system and IEEE 3-area RTS-96 system are used to demonstrate the presented approach. The results show that the proposed method is effective and practical. Some new problems are suggested at the end of paper.

Available transfer capability estimation using Support Vector Machine

In the deregulated power system, effective management of transactions, to meet the active power requirements of the consumers can be done through pool and bilateral/multilateral markets. One of the main functions of ISO in a day ahead market is assessment of Available Transfer Capability (ATC) and updating this value in Open Access Same time Information Systems (OASIS). The market participants use the value of ATC for their transaction planning. Hence it is essential to estimate ATC accurately with lesser computation time. This paper proposes a Support Vector Machine based method for ATC estimation. To the best of our knowledge this is the first attempt to use SVM for ATC estimation. Two methods are proposed in this paper. The first method uses the real power demands and the source bus injections as inputs to SVM model. The second method uses few indices as inputs to estimate ATC. The proposed methods are tested on IEEE 24 bus Reliability Test System (RTS) and IEEE 118 bus system. The results are compared with Repeated Power Flow (RPF) results.

Determination of available transfer capability by means of Ralston's method incorporating cubic-spline interpolation technique

This paper presents a fast and accurate method to determine the power transfer so-called the available transfer capability (ATC). The methodology utilizes the cubic-spline interpolation technique that is incorporated into the Ralston's method in order to provide fast and accurate assessment of ATC. The Ralston's method is used to predict the two trajectory points of voltage magnitude (U), power flow (S), and maximum generator rotor angle difference (Δδ). Then, the cubic-spline interpolation technique is used to accurately trace the P-U, P-S, or P-Δδ curves between two points of trajectory. The P-U, P-S, and P-Δδ curves represent as the variations of voltage magnitude, power flow and maximum generator rotor angle difference due to the increase of power transfer or ATC. The actual value of ATC is then determined when either the voltage magnitude limit, power flow limit or generator rotor angle difference limit intersects the curve. The effectiveness of the proposed method is verified by referring to the results of ATC for a case study of 2737-Polish system and 39-New England bus system. The proposed method gives a satisfactorily accurate and fast computation of ATC as compared to recursive AC power flow method. Copyright © 2010 John Wiley & Sons, Ltd.

Assessment of Available Transfer Capability (ATC) considering Real-time Weather Conditions

Total Transfer Capability (TTC) should be pre-determined in order to estimate Available Transfer Capability (ATC). Typically, TTC is determined by considering three categories; voltage, stability and thermal limits. Among these, thermal limits are treated mainly in this paper on the evaluation of TTC due to the relatively short transmission line length of Korea Electric Power Corporation (KEPCO) system. This paper presents a new approach to evaluate the TTC using the Dynamic Line Rating (DLR) for the thermal limit. Since the approach includes not only traditional electrical constraints but also real-time environmental constraints, this paper obtains more cost-effective and exact results. A case study using KEPCO system confirms that the proposed method is useful for real-time operation and the planning of the electricity market.

Assessment of Available Transfer Capability Incorporating Probabilistic Distribution of Load Using Interval Arithmetic Method

Following the deregulation of electric power utilities around the globe, it has been widely acknowledged that quantifying the power transfer capability is of increasing importance in the operation and planning of interconnected power systems. This paper reports on the application of probabilistic distribution based interval arithmetic method to estimate the Available Transfer Capability (ATC) in a power network in terms of confidence intervals. Interval arithmetic method enables incorporation of the uncertainty in the input parameters and provides strict bounds for the solution. In the present work, the variation of the real power load is represented as a Gaussian distribution function. The proposed method is tested and validated on IEEE 14 bus test system.