Energy storage emerged as a top concern for the modern cities, and the choice of the lithium-ion chemistry battery technology as an effective solution for storage applications proved to be a highly ...efficient option. State of charge (SoC) represents the available battery capacity and is one of the most important states that need to be monitored to optimize the performance and extend the lifetime of batteries. This review summarizes the methods for SoC estimation for lithium-ion batteries (LiBs). The SoC estimation methods are presented focusing on the description of the techniques and the elaboration of their weaknesses for the use in on-line battery management systems (BMS) applications. SoC estimation is a challenging task hindered by considerable changes in battery characteristics over its lifetime due to aging and to the distinct nonlinear behavior. This has led scholars to propose different methods that clearly raised the challenge of establishing a relationship between the accuracy and robustness of the methods, and their low complexity to be implemented. This paper publishes an exhaustive review of the works presented during the last five years, where the tendency of the estimation techniques has been oriented toward a mixture of probabilistic techniques and some artificial intelligence.
The optimal coordination of overcurrent relays (OCRs) has recently become a major challenge owing to the ever-increasing participation of distributed generation (DG) and the multi-looped structure of ...modern distribution networks (DNs). Furthermore, the changeable operational topologies of microgrids has increased the complexity and computational burden to obtain the optimal settings of OCRs. In this context, classical approaches to OCR coordination might no longer be sufficient to provide a reliable performance of microgrids both in the islanded and grid-connected operational modes. This paper proposes a novel approach for optimal coordination of directional OCRs in microgrids. This approach consists of considering the upper limit of the plug setting multiplier (PSM) as a variable instead of a fixed parameter as usually done in traditional approaches for OCRs coordination. A genetic algorithm (GA) was implemented to optimize the limits of the maximum PSM for the OCRs coordination. Several tests were performed with an IEC microgrid benchmark network considering several operational modes. Results showed the applicability and effectiveness of the proposed approach. A comparison with other studies reported in the specialized literature is provided showing the advantages of the proposed approach.
Nowadays, microgrids play a significant role in the development of modern distribution networks (DNs). In this context, the ever increasing presence of renewable distributed generation (DG) in ...microgrids has imposed new challenges in protection coordination, rendering traditional coordination schemes inefficient. Thus, it is essential to explore new approaches for protection coordination that take into account specific features of microgrids, such as the presence of DG and the fact that they may operate under different operational modes or topologies. This paper proposes a novel approach for the optimal coordination of over-current relays (OCRs) in microgrids that considers three optimization parameters for each relay: time multiplying setting, plug setting current and characteristic curve. To show the applicability of the proposed approach, several tests were carried out using an IEC benchmark microgrid and a modified version of the IEEE 30 bus test system. Three metaheuristic techniques were implemented for solving the optimal coordination problem, namely: a genetic algorithm (GA), particle swarm optimization (PSO) and a teaching–learning based optimization (TLBO) algorithm. A comparison of results with other coordination models reported in the specialized literature evidenced the applicability and effectiveness of the proposed approach.
•The method solves multi-order and variable coefficients RLFDE and CFD.•Theorem 3.1. transforms RLFI to a linear algebraic equation.•Corollary 3.1.1. transforms CFD to a linear algebraic ...equation.•Theorem 3.2. allows to find with for RLFDE.•Corollary 3.2.1. allows to find and for CFDE.
In this paper, a numerical method is developed to obtain a solution of Caputo’s and Riemann-Liouville’s Fractional Differential Equations (CFDE and RLFDE). Scientific literature review shows that some numerical methods solve CFDE and there is only one paper that numerically solves RLFDE. Nevertheless, their solution is limited or the Fractional Differential Equation (FDE) to be solved is not in the most general form. To be best of the author’s knowledge, the proposed method is presented as the first method that numerically solves RLFDE which includes multi-order fractional derivatives and variable coefficients. The method converts the RLFDE or CFDE to be solved into an algebraic equation. Each Riemann-Liouville’s or Caputo’s Fractional Derivative (RLFD and CFD), derived from the RLFDE or CFDE respectively, is conveniently written as a set of substitution functions and an integral equation. The algebraic equation, the sets of substitution functions and the integral equations are discretized; and then solved using arrays. Some examples are provided for comparing the obtained numerical results with the results of other papers (when available) and exact solutions. It is demonstrated that the method is accurate and easy to implement, being presented as a powerful tool to solve not only FDE but also a wide range of differential and integral equations.
This paper addresses the problem of Distribution Systems Reconfiguration (DSR), which consists of finding the state of switching devices (open or closed) in a given distribution network, aiming to ...minimize active power loses. DSR is modeled as a mixed-integer non-linear optimization problem, in which the integer variables represent the state of the switches, and the continuous variables represent the power flowing through the branches. Given the multi-modal and non-convex nature of the problem, an improved harmony search (IHS) algorithm is proposed to solve the DSR problem. The main novelty of this approach is the inclusion of a Path Relinking phase which accelerates convergence of the DSR problem. Several tests were carried out in four benchmark distribution systems, evidencing the effectiveness and applicability of the proposed approach.
Under-frequency load shedding (UFLS) schemes are the latest safety measures applied for safeguarding the integrity of the grid against abrupt frequency imbalances. The overall inertia of electrical ...power systems is expected to decrease with an increased penetration of renewable energy as well as elements connected through power electronic interfaces. However, voltage source converter-based high voltage direct current (VSC-HVDC) links can provide virtual inertia through a control loop that allows for a reaction to occur at certain frequency fluctuations. This paper evaluates a UFLS scheme that considers the injection of virtual inertia through a VSC-HVDC link. A genetic algorithm (GA) is used to determine the location of the UFLS relays, the activation threshold of each stage, the delay time and the percentage of load shedding at each stage. It was found that the virtual inertia causes the nadir to delay and sometimes reach a greater depth. Furthermore, the implemented GA approximates the frequency response to the limits set with the constraints, reducing the load shedding but achieving a steeper nadir and a lower steady-state frequency level than traditional UFLS. The simulations were performed using the IEEE 39-bus test system.
This paper addresses the protection coordination problem of microgrids combining unsupervised learning techniques, metaheuristic optimization and non-standard characteristics of directional ...over-current relays (DOCRs). Microgrids may operate under different topologies or operative scenarios. In this case, clustering techniques such as K-means, balanced iterative reducing and clustering using hierarchies (BIRCH), Gaussian mixture, and hierarchical clustering were implemented to classify the operational scenarios of the microgrid. Such scenarios were previously defined according to the type of generation in operation and the topology of the network. Then, four metaheuristic techniques, namely, Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Invasive Weed Optimization (IWO), and Artificial Bee Colony (ABC) were used to solve the coordination problem of every cluster of operative scenarios. Furthermore, non-standard characteristics of DOCRs were also used. The number of clusters was limited to the maximum number of setting setting groups within commercial DOCRs. In the optimization model, each relay is evaluated based on three optimization variables, namely: time multiplier setting (TMS), the upper limit of the plug setting multiplier (PSM), and the standard characteristic curve (SCC). The effectiveness of the proposed approach is demonstrated through various tests conducted on a benchmark test microgrid.
The increasing presence of electric vehicles (EVs) requires a thorough understanding of their impact on distribution assets. EV chargers are characterized as nonlinear and multi-state loads due to ...their unique electrical consumption patterns. This paper presents a comprehensive study focused on modelling diverse EV charging units deployed in the industrial, commercial, and residential sectors. To conduct this analysis, a simulation environment utilizing the ETAP tool is employed, taking into account time variations. This approach facilitates the comprehension and anticipation of the effects that EV charging may impose on distribution networks, thereby supporting well-informed decision-making for the adaptation and enhancement of the electrical system. Detailed data on current and voltage from operational EV charging stations were collected to create consumption, current, voltage, and harmonic profiles for these charging units. Subsequently, general models or libraries applicable to Level 1, Level 2 and Level 3 EV chargers available in Colombia were developed. These models underwent rigorous validation and were subjected to a comprehensive analysis using the IEEE 13-bus test system. The research yielded valuable insights and conclusions regarding the integration of EV chargers into the current Colombian distribution systems, as well as the potential impact of adopting these devices on power quality issues within the distribution grid. This study contributes to the improved management of distribution assets, thereby facilitating the integration of sustainable electric mobility in the national electrical system.
Protection coordination of AC microgrids (MGs) is a challenging task since they can operate either in grid-connected or islanded mode which drastically modifies the fault currents. In this context, ...traditional approaches to protection coordination, that only consider the time multiplier setting (TMS) as a decision variable may no longer be able to guarantee network security. This paper presents a novel approach for protection coordination in AC MGs that incorporates non-standard characteristic features of directional over-current relays (OCRs). Three optimization variables are considered for each relay: TMS, maximum limit of the plug setting multiplier (PSM) and standard characteristic curve (SCC). The proposed model corresponds to a mixed integer non-linear programming problem. Four metaheuristic techniques were implemented for solving the optimal coordination problem, namely: particle swarm optimization (PSO), genetic algorithm (GA), teaching-learning based optimization (TLBO) algorithm and shuffled frog leaping algorithm (SFLA). Numerous tests were run on an IEC MG as well as with the distribution portion of the IEEE 30-bus test system. Both systems incorporate distributed generation (DG) and feature several modes of operation. A comparison was made with other MG protection coordination approaches proposed in the specialized literature. In all cases, the proposed approach found reduced coordination times, evidencing the applicability and efficacy of the proposed approach.
Distributed generation; Distribution networks; Microgrids; Power system protection; Over-current relay coordination
This paper deals with the optimal sizing of islanded microgrids (MGs), which use diesel generators to supply energy in off-grid areas. The MG under study integrates photovoltaic (PV) and diesel ...generation, a battery energy storage System (BESS), and an inverter for the connection between AC and DC voltage buses. Levelised cost of energy (LCOE) and annual system cost (ASC) are considered economic indicators, while the loss of power supply probability (LPSP) is used as a reliability indicator. Fiscal incentives such as the tax benefits and accelerated depreciation applied in Colombia are considered for the optimally sizing of each MG element. Solar measurements were taken at a weather station located in the main campus of Universidad de Antioquia in Medellin, Colombia at a latitude of 6.10 and longitude of −75.38. The objective function is the minimization of the total energy delivered from the power sources that successfully meets the load. The model was implemented in Python programming language considering several scenarios. Two cases were evaluated: the first one considered PV panels, a BESS and a diesel generator, while the second one only considered PV panels and a BESS. The option that does not include the diesel generator turned out to be the most expensive, since additional PV and BESS resources are required to meet the load profile. Furthermore, it was found that the LCOE was lower when tax benefits were taken into account.
PDF
