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With the increasing trend in the integration and deployment of distributed energy resources, the real-time assessment of power system transient stability is becoming more and more challenging. This study presents an enhanced sensitivity-based decentralised transient stability assessment scheme, which first virtually decomposes the large-scale power network into several smaller areas. Then, a new sensitivity-based scheme is developed to derive and quantify the kinetic energy-based stability assessment index. This index allows taking into account the effects of both AC generators and power electronic-based generator units. In addition, thanks to the new sensitivity-based scheme, the transient stability can be assessed in a decentralised manner using only the boundary buses in each segmented area, which relaxes the need for massive data availability and transfer across the network and enables its applicability for online applications in large-scale power systems. Simulation results on the 48-machine IEEE 140-bus and 544-machine 2000-bus synthetic power grid test systems demonstrate the efficacy of the proposed method. [ABSTRACT FROM AUTHOR]

With the increasing trend in the integration and deployment of distributed energy resources, the real‐time assessment of power system transient stability is becoming more and more challenging. This study presents an enhanced sensitivity‐based decentralised transient stability assessment scheme, which first virtually decomposes the large‐scale power network into several smaller areas. Then, a new sensitivity‐based scheme is developed to derive and quantify the kinetic energy‐based stability assessment index. This index allows taking into account the effects of both AC generators and power electronic‐based generator units. In addition, thanks to the new sensitivity‐based scheme, the transient stability can be assessed in a decentralised manner using only the boundary buses in each segmented area, which relaxes the need for massive data availability and transfer across the network and enables its applicability for online applications in large‐scale power systems. Simulation results on the 48‐machine IEEE 140‐bus and 544‐machine 2000‐bus synthetic power grid test systems demonstrate the efficacy of the proposed method. [ABSTRACT FROM AUTHOR]

In this study, the holomorphic-embedding method as a linear and non-iterative method is developed and implemented to solve the load flow of the three-phase unbalanced radial distribution networks. Previously, this method was used to solve the load flow problem of balanced transmission networks. The proposed methodology could be applied for a variety of unbalanced radial distribution networks with any number of buses and branches. The characteristics of unbalanced radial distribution networks including line coupling effects, unbalanced loads and unsymmetrical phases are considered in this study. The proposed method uses an unbalanced network structure and modifies the calculation approach of the admittance matrix. In this manner, an unbalanced network is modelled the same as the balanced networks. The tap-changer, doubly-fed induction generator (DFIG), and photovoltaic system are modelled in the admittance matrix or current injection vector. The performance of the proposed method is validated on the 19-bus unbalanced radial distribution network. Finally, the effectiveness of the proposed method in solving the load flow problem is investigated. [ABSTRACT FROM AUTHOR]

In this study, the holomorphic‐embedding method as a linear and non‐iterative method is developed and implemented to solve the load flow of the three‐phase unbalanced radial distribution networks. Previously, this method was used to solve the load flow problem of balanced transmission networks. The proposed methodology could be applied for a variety of unbalanced radial distribution networks with any number of buses and branches. The characteristics of unbalanced radial distribution networks including line coupling effects, unbalanced loads and unsymmetrical phases are considered in this study. The proposed method uses an unbalanced network structure and modifies the calculation approach of the admittance matrix. In this manner, an unbalanced network is modelled the same as the balanced networks. The tap‐changer, doubly‐fed induction generator (DFIG), and photovoltaic system are modelled in the admittance matrix or current injection vector. The performance of the proposed method is validated on the 19‐bus unbalanced radial distribution network. Finally, the effectiveness of the proposed method in solving the load flow problem is investigated. [ABSTRACT FROM AUTHOR]

This study presents a new powerful method for probability density function (PDF) estimation of the probabilistic power flow problem results. The proposed method works on a prior density function to improve its potential PDF estimation. The generalised cross-entropy method is used to refine the initial dataset. Most of the existing methods for PDF estimation do not provide a sparse result and rely on approximation and simplification. Compared to the other conventional methods, the proposed method has some remarkable features in density estimation. Low computational burden or high-speed response and high-precision results are the most prominent features of the proposed method. The method can deal with a correlated problem which is considered the correlation between uncertain parameters. It is tested on IEEE 14-bus and IEEE 118-bus systems, considering the non-stationary loads, some renewable energy resources and their correlations. The results of the proposed method are compared against more accurate results obtained from Monte Carlo simulation and some other conventional methods in density estimation. Comparisons confirm the high accuracy level and speed of the proposed density estimator against the other methods. [ABSTRACT FROM AUTHOR]

Expansion of cogeneration technologies, such as combined heat and power units, has boosted the growth of multi-carrier energy systems. A two-step method is presented to enable residential demand response (DR) programmes in the multi- carrier energy systems. In the first step, the energy management system at each home solves an optimisation problem to achieve the desired energy cost and demand schedule for the customer according to received price signals. In the second step, the system operator revises the demand scheduling by running another optimisation problem to minimise the total electrical losses, subject to the operational characteristics of electrical and natural gas systems. In order to persuade customers to participate in the DR programmes, it is guaranteed that the resulted cost of the second step is not more than the desired cost of the customer in the first step. Results of applying the proposed method, incorporating different penetration levels of customer participation in a time-of-use programme is studied in a test energy system. Simulation results verify the effectiveness of proposed method in minimising the total electrical losses, improving the operational characteristics of the energy system as well as providing customers' utilities. [ABSTRACT FROM AUTHOR]

Due to current transformer (CT) saturation, the secondary current waveform may contain distortions which results in mal‐operation of the protective system. This study presents a framework that attempts to detect and reconstruct saturated secondary current of the CT. To such aim, first an algorithm is proposed which detects and discriminates between normal and abnormal condition. This algorithm which is based on high‐order derivatives and statistical criterion, classifies load change, inrush current and fault condition. In addition, this algorithm is designed so that it detects the first time that CT becomes saturated. After fault detection and phase fault selection, based on analytical and comprehensive formulations, the parameter of fault current signal is calculated in the sub‐cycle. Moreover, the dynamic behaviour of the CT is considered in the waveform reconstruction. Several case studies are carried out to investigate the performance of the proposed method. Simulation results show that proposed method can effectively classify the inrush current and fault signal even in the CT saturation condition. Also, under different CT saturation condition, proposed method quickly and precisely detects and reconstructs saturated waveform without sacrificing details. [ABSTRACT FROM AUTHOR]

Simultaneous expansion of the electrical and thermal energies collected with conventional expansion options is scrutinised. A robust, bio‐inspired evolutionary optimisation method is proposed, to handle the complex expansion planning of a system consisting of both electrical and thermal forms of energy. Rewiring, network reconfiguration, installation of new lines and also new electrical and thermal generation units are considered as the traditional alternatives in expansion planning. To solve the problem, overall generation requirements of a network are assigned along the planning horizon. The allocation problem is formulated as a mixed‐integer non‐linear programming problem that minimises the overall system cost owing to generation capacity among the grid nodes and the newly added or upgraded lines. The performance of the original shuffled frog leaping (SFL) optimisation algorithm is advanced to overcome the complexity of the proposed expansion planning problem. Two modification steps were added to the original SFL technique to enable the proposed modified SFL algorithm to extricate from local minima. The two modification phases pledge a fast convergence rate by achieving a rapid adaptive algorithm, besides a better diversification which is the key to extricate from local minima. The efficacy and robustness of the proposed methodology are verified by applying the method to two modified standard test systems. [ABSTRACT FROM AUTHOR]

In this study, a stochastic multi‐objective framework is proposed for energy expansion planning (EEP). The proposed multiobjective framework can concurrently optimise the competing objective functions including total real energy losses, voltage deviation and the total cost of the installation equipments. Also, regarding the uncertainties of the new complicated energy systems, in this study, for the first time, system uncertainties including load uncertainty are explicitly considered in the EEP problem by the use of the probabilistic load flow technique based on the point estimate method. Since the objectives are different and incommensurable, it is difficult to solve the problem by the conventional approaches that may optimise a single objective. Hence, the metaheuristic algorithm is applied to this problem. Here, the particle swarm optimisation (PSO) algorithm as a new evolutionary optimisation algorithm is utilised. To improve the total ability of the PSO for global search and exploration, a new modification adaptive process is suggested in such a way that the algorithm will search the total search space globally. To evaluate the feasibility and the effectiveness of the proposed algorithm, three modified standard distribution systems are used as the case studies. [ABSTRACT FROM AUTHOR]