Evaluation Of Available Transfer Capability Research Articles

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.

Appraisal of Available Transfer Capability Determination Methods in Competitive Electricity Market

The existing power market is contentiously promoting sustainability and competitiveness in the electricity industry. It has raised the transmission networks' transfer capacity as an emerging area for researchers. The electricity production units and consumers share the same transmission network. All stakeholders try to generate power from cheaper sources to make more significant profit margins. This situation creates transmission congestion, violation of voltage and thermal limits, and system security threats. The accurate measurement and optimal use of the available transfer capability (ATC) shall resolve this issue up to some extent. Thus, efficient evaluation of ATC is needed to ensure system security, and it provides an open and trending research topic. This article presents a review of the various techniques for ATC determination and provides the characteristics, practices, and features of the methods. This analysis demonstrates the issues of ATC evaluation techniques and provides the research areas to the researchers.

Probability Evaluation of Available Transfer Capability Considering Wind Power Correlation

Probability Evaluation of Available Transfer Capability Considering Wind Power Correlation

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.

Reactive Power Loss Reduction in Distribution Network Using Crow Search Optimization and Available Transfer Capability

In distribution systems, it is important to guarantee the protected operating state of the power system by the transmission suppliers. To transmit a secure, dependable and economical supply of electric power, long separation bulk power transmission is fundamental. Despite that, the power transfer capacity of the power system is constrained because of the elements like thermal limits, voltage limits and security limits. Crow Search Optimizations (CSO) have been exhibited to be reasonable methodologies in taking care of nonlinear power system issues with Available Transfer Capability (ATC). It is conceivable to improve transmission capabilities. This proposed method based on the IEEE 30-bus system is considered with two distinct areas, and furthermore, the input source is a typical load system with a distributed network. There is a need to control the reactive power flow at the Point of Common Coupling (PCC) between the grids of various voltage levels. To operate a power system securely and furthermore to acquire the benefit of bulk power transfer, ATC evaluation is required. The load gets raised from 50% to 100% in the distribution side by including the thermal power plant (85% and 95% load is included) and with the procured condition, ATC and losses are to be determined. This ATC is determined for verified power supply to the consumers.

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.

Integrating flexible demand response toward available transfer capability enhancement

Available transfer capability (ATC) has been widely adopted as a crucial measure to guarantee free and reliable power trading. The existing literature generally evaluates the ATC of a power grid considering inelastic load. However, the impacts of responsive load have not yet been systematically explored, which underestimates the ability of demand side resources in ATC enhancement. Therefore, we propose a two-stage ATC evaluation framework in this paper integrating flexible demand response (FDR). In the first stage, i.e., a day-ahead market, a demand side bidding scheme is developed in which electricity users can make flexible choices to participate in demand response (DR) programs according to their preferences. In this paper, FDR is categorized into three typical patterns: (i) deferrable DR, (ii) switchable DR and (iii) adjustable DR. The objective is to minimize the total generation and dispatch costs, while respecting the constraints for FDR, the minimal accommodation of renewable energy, the inter-area power trading, etc. Then based on generation and demand side bidding, a day-ahead unit commitment model is formulated to schedule thermal generators, interchange power and FDR. In the second stage, a real-time ATC evaluation model based on the aforementioned unit commitment results is proposed to quantify the contributions of FDR on ATC enhancement. Case studies based on IEEE 14-bus system and a provincial power grid in China demonstrate that FDR can effectively improve real-time ATC by load shifting and peak shaving, and facilitate the accommodation of renewable energy.

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.

ATC Evaluation In A Deregulated Power System

Restructured power system helps to meet the active power requirements of the consumers in an effective way. In an Independent System Operator (ISO) model of restructured power system, Available Transfer Capability (ATC) is calculated so as to determine how much extra power can be injected into one site apart from base consumption. ATC computation plays a significant role during power transactions because it helps the participants to schedule their transaction more effectively and quickly. This paper mainly focuses on ATC calculation using linear sensitivity factors for normal mode and line outage mode.

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.

Optimal Evaluation of Available Transfer Capability of Transmission Line Using Bio-inspired Algorithm for Multiple Transactions in Deregulated Electrical Power Network

In restructured Electrical Power network the transmission line gets congested by multiple transactions over the line. In such scenario the operator must analyze optimum value of ATC for said transaction. When the transactions between the transmission lines are carried out for a specific destination node/source node pair in a system, the Independent System operator (ISO) must calculate the available transfer capacity (ATC) of that node/source pair. This paper proposes a comprehensive approach to find out the optimized value of ATC for given transaction using Genetic Algorithm. With the help of Genetic algorithm transactions between pair of node can be generated randomly and can be used to calculate optimized value of ATC for each transaction. With the help of this method ISO can declare the value of transacted power from source to destination bus for optimum value of ATC. The objective function is to maximize the power flow capability of transmission line with safest transaction. The solution to the optimization problem gives the amount of accepted requests and available capability of transmission line that could result in a safe and reliable transmission system. The proposed method is applied to an IEEE 30 bus test system.

Evaluation of Available Transfer Capability Using Transient Stability Constrained Line Flows

Abstract This paper presents a methodology to evaluate transient stability constrained available transfer capability (ATC). A linear and fast line flow–based (LFB) method was adopted to optimize the ATC values. This enabled the direct determination of the system source–sink locations. This paper formulated different market transactions considering bilateral and multilateral impacts in the stability constrained ATC. The proposed method was demonstrated on the WECC 9-bus and IEEE 39-bus systems. The critical energy performance index (CEPI) enabled the direct identification of candidates for contingency screening based on ranking. This index helped to reduce the list of credible contingencies for ATC evaluation and, therefore, the computation time. The results of the proposed ATC method are consistent with the literature and can be deployed for fast assessment of the impact of transactions in an electric power system.

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.

A Software Tool for Available Transfer Capability Teaching Purposes

This paper presents an educational software tool with a user-friendly interface, which can be used for evaluation of available transfer capability (ATC). The software was developed using the MATLAB1–2 software package. The software is designed for engineers who are involved in trading in electrical energy and for students (undergraduate and Master's) of Electrical Engineering who could, by using the software, gain a better insight into the theoretical knowledge and solve some practical engineering problems. ATC model limitations include the usual d.c. load flow inherent limitations as well as line thermal limits, prevalent in the literature on ATC. The structure and software capabilities are presented within the example of an ATC sensitivity study on a five node/seven line transmission network, used for zonal market activities tests.

Implementation of FACTS Device for Enhancement of ATC Using PTDF

In this paper an attempt has been made to determine Available Transfer Capability (ATC) with the FACTS device i.e. TCSC. The methods for ATC evaluation are developed considering system thermal limits constraints based on MVA loading of the system. Power Transfer Distribution Factors (PTDF) are used to determine the maximum ATC that may be available across the system in a certain direction without violating line thermal limits. ATC traditionally uses linear methods capable of predicting distances based on thermal limits. However, these methods do not consider bus voltages and static collapse. Most of the studies relating ATC involve contingencies and multi-pattern scenarios that often can only be performed in reasonable time with the use of linear methods. In this paper, a new approach is proposed that first determines the Reactive Power Flows using the exact circle equation for the transmission line complex flow, and then evaluates ATC using active power distribution factors. The effectiveness of proposed method is successfully demonstrated on IEEE 30-Bus system.

Available Transfer Capability Evaluation Considering CO 2 Emissions Using Multi-Objective Particle Swarm Optimization

Under the Kyoto Protocol many countries have been requested to participate in emissions trading with the assigned emissions. In this environment, it is inevitable to change the system and market operation in deregulated power systems, and then ensuring safety margin is becoming more important for balancing system security, economy and emissions. Nowadays, available transfer capability (ATC) is a key index of the remaining capability of a transmission system for future transactions. This paper presents a novel approach to the ATC evaluation with emissions using multi-objective particle swarm optimization (MOPSO) technique. This technique evolves a multi-objective version of PSO by proposing redefinition of global best and local best individuals in multi-objective optimization domain. The optimal power flow (OPF) method using MOPSO is suggested to solve multi-objective functions including fuel cost and emissions simultaneously. To show its efficiency and effectiveness, the results of the proposed method is comprehensively realized by a comparison with the ATC which is not including emissions for the IEEE 30-bus system, and is found to be quite promising.

Dynamic available transfer capability computation using a hybrid approach

In a restructured electricity market, accurate evaluation of available transfer capability (ATC) with dynamic constraints is a challenging task. An approach to determine dynamic ATC, utilising the benefits of a direct method as well as time-domain simulation method, has been developed. Structure-preserving energy function model, which retains the topology of the network, along with transient stability limit, has been used to compute dynamic ATC for bilateral as well as multilateral transactions in an electricity market. Constant impedance as well as composite models for real power loads have been considered. A new contingency severity index, which takes into account the impact of transactions on the severity of the contingencies, has been proposed to reduce the list of credible contingencies to be considered in determining the ATC. To demonstrate the effectiveness of the proposed method, it has been tested on 10-machine, 39-bus New England system and a practical 60-machine, 246-bus Indian system.

Consideration of multiple uncertainties for evaluation of available transfer capability using fuzzy continuation power flow

In today’s electric power industry, accurate and flexible information is needed to provide nondiscriminatory access to all market participants. This paper primarily purports to determine available transfer capability (ATC) based on the fuzzy set theory for continuation power flow (CPF), thereby capturing uncertainty. Assuming that uncertainties involved in the ATC calculation are estimated or measured, a fuzzy model is formulated in which major uncertainty parameters affecting the ATC are regarded as fuzzy variables subject to their possibility distributions. The purpose of this paper is to elaborate main features of the fuzzy continuation power flow (FCPF) algorithm that can handle uncertainties in load parameters and bus injections as well. As such, the robust solution will assist in providing additional information on the actual ability of the network to a system operator. In other respects, it poses a significant influence on the potential curtailment of power trades from which the reinforcement strategy can be set by the system operator. The viability of the proposed method would be verified through a stark contrast with the ones obtained from the conventional CPF and the fuzzy power flow (FPF) in the IEEE-24 RTS bus system and in the IEEE-118 bus system.