An Effective Coordination Setting for Directional Overcurrent Relays Using Modified Harris Hawk Optimization

The relay optimization expresses quite a challenge for smooth and optimal operation of power system networks. The relay optimization is formulated as a mixed integer non-linear problem and is highly constrained. Furthermore, a reliable relaying system must be able to detect and isolate the faulted portion in a timely manner. Therefore, it is necessary to find optimal parameters for relay settings to be able to respond in a timely way to the encountered fault and at the same time keep in consideration the operational and coordination constraints. This paper proposes modified Harris hawk optimization (MHHO), which is based on the intelligent preying tactics of Harris hawks and the improvement of intended modifications, crowding distance and roulette wheel selection. The proposed algorithm has been tested on IEEE 8 and 15-bus systems, using MATLAB programming. The test systems are the distribution networks covering the medium level voltage for consideration. The simulation results verified the success of MHHO to find optimal settings for the relays. For IEEE 8-bus system, MHHO was able to give 35.45% improvement in the results in comparison to other algorithms. Furthermore, for the IEEE 15-bus system, MHHO showed 24.09% improvement on average. The comparison of the results obtained by MHHO with the other state-of-the-art algorithms proved that it is the strong candidate for optimization of the relay coordination problem.

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Optimal Operation of Soft Open Points-Based Energy Storage in Active Distribution Networks by Considering the Battery Lifetime

Frontiers in Energy Research ◽

10.3389/fenrg.2020.633401 ◽

2021 ◽

Vol 8 ◽

Author(s):

Jian Wang ◽

Niancheng Zhou ◽

Anqi Tao ◽

Qianggang Wang

Keyword(s):

Energy Storage ◽

Reactive Power ◽

Programming Model ◽

Distribution Networks ◽

Optimal Operation ◽

Mixed Integer ◽

Operation Model ◽

Battery Lifetime ◽

Battery Degradation ◽

Active Distribution Networks

Soft open point-based energy storage (SOP-based ES) can transfer power in time and space and also regulate reactive power. These characteristics help promote the integration of distributed generations (DGs) and reduce the operating cost of active distribution networks (ADNs). Therefore, this work proposed an optimal operation model for SOP-based ES in ADNs by considering the battery lifetime. First, the active and reactive power equations of SOP-based ES and battery degradation cost were modeled. Then, the optimal operation model that includes the operation cost of ADNs, loss cost, and battery degradation cost was established. The mixed integer nonlinear programming model was transformed to a mixed integer linear programming model derived through linearization treatment. Finally, the feasibility and effectiveness of the proposed optimization model are verified by the IEEE33 node system.

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Hybrid Harmony Search Algorithm Applied to the Optimal Coordination of Overcurrent Relays in Distribution Networks with Distributed Generation

Applied Sciences ◽

10.3390/app11199207 ◽

2021 ◽

Vol 11 (19) ◽

pp. 9207

Author(s):

Sergio D. Saldarriaga-Zuluaga ◽

Jesús M. López-Lezama ◽

Nicolás Muñoz-Galeano

Keyword(s):

Distributed Generation ◽

Search Algorithm ◽

Short Circuit ◽

Harmony Search ◽

Distribution Networks ◽

Harmony Search Algorithm ◽

Small Scale ◽

Coordination Problem ◽

Overcurrent Relays ◽

Optimal Coordination

In recent years, distributed generation (DG) has become more common in modern distribution networks (DNs). The presence of these small-scale generation units within a DN brings new challenges to protection engineers, since short-circuit currents tend to increase; additionally, as with microgrids, modern DNs may feature several operational modes depending on their topology and the availability of DG. This paper presents a methodology for the optimal coordination of overcurrent relays (OCRs) in modern DNs with a high presence of DG. Given the fact that protection coordination is a non-linear and non-convex optimization problem, a hybrid harmony search and simulated annealing (HS-SA) approach was implemented for its solution and compared against other techniques, such as conventional HS, genetic algorithm (GA), particle swarm optimization (PSO) and hybrid PSO-HS. Several tests were performed on a DN, considering different operative scenarios as a function of the DG available within the network. A comparison with other works reported in the specialized literature was carried out, evidencing the applicability and effectiveness of the HS-SA technique in solving the optimal OCR coordination problem in modern DNs.

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Impact of Demand Response on Reliability Enhancement in Distribution Networks

Sustainability ◽

10.3390/su132313201 ◽

2021 ◽

Vol 13 (23) ◽

pp. 13201

Author(s):

Mohammad Reza Mansouri ◽

Mohsen Simab ◽

Bahman Bahmani Firouzi

Keyword(s):

Demand Response ◽

Electricity Market ◽

Distribution System ◽

Distribution Systems ◽

Market Price ◽

Distribution Networks ◽

Optimal Operation ◽

Mixed Integer ◽

Reliability Indices ◽

Operation Costs

This paper presents an innovative instantaneous pricing scheme for optimal operation and improved reliability for distribution systems (DS). The purpose of the proposed program is to maximize the operator’s expected profit under various risk-taking conditions, such that the customers pay the minimum cost to supply energy. Using the previous information of the energy consumption for each customer, a customer baseline load (CBL) is defined; the energy price for consumption costs higher and lower than this level would be different. The proposed scheme calculates the difference between the baseline load and the consumption curve with the electricity market price instead of calculating the total consumption of the customers with the unstable price of the electricity market, which is uncertain. In the proposed tariff, the developed cost and load models are included in the distribution system operation problem, and the objective function is modeled as a mixed integer linear programming (MILP) problem. Also, the effect of demand response (DR) and elasticity on the load curve, the final profit of the distribution system operator, and payment risk and operation costs are examined. Since there are various uncertainties in the smart distribution grid, the calculations being time-consuming and volumetric is important in the evaluation of reliability indices. Thus, when computation volume can be decreased and computation speed can be increased, analytical reliability analysis methods can be used, as they were in the present work. Finally, the changes in the reliability indices were calculated for the ratio of the customers’ sensitivity to the price and the customers’ participation in the proposed tariff using an analytical method based on Monte Carlo simulation (MCS). The results showed the efficiency of the proposed method in increasing the operator profit, reducing the operation costs, and enhancing the reliability indices.

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Optimal Investments in PV Sources for Grid-Connected Distribution Networks: An Application of the Discrete–Continuous Genetic Algorithm

Sustainability ◽

10.3390/su132413633 ◽

2021 ◽

Vol 13 (24) ◽

pp. 13633

Author(s):

Oscar Danilo Montoya ◽

Luis Fernando Grisales-Noreña ◽

Alberto-Jesus Perea-Moreno

Keyword(s):

Genetic Algorithm ◽

Objective Function ◽

Fitness Function ◽

Distribution Networks ◽

Voltage Regulation ◽

Successive Approximation Method ◽

Optimization Approach ◽

Voltage Profile ◽

Matlab Programming ◽

Bus System

The problem of the optimal siting and sizing of photovoltaic (PV) sources in grid connected distribution networks is addressed in this study with a master–slave optimization approach. In the master optimization stage, a discrete–continuous version of the Chu and Beasley genetic algorithm (DCCBGA) is employed, which defines the optimal locations and sizes for the PV sources. In the slave stage, the successive approximation method is used to evaluate the fitness function value for each individual provided by the master stage. The objective function simultaneously minimizes the energy purchasing costs in the substation bus, and the investment and operating costs for PV sources for a planning period of 20 years. The numerical results of the IEEE 33-bus and 69-bus systems demonstrate that with the proposed optimization methodology, it is possible to eliminate about 27% of the annual operation costs in both systems with optimal locations for the three PV sources. After 100 consecutive evaluations of the DCCBGA, it was observed that 44% of the solutions found by the IEEE 33-bus system were better than those found by the BONMIN solver in the General Algebraic Modeling System (GAMS optimization package). In the case of the IEEE 69-bus system, the DCCBGA ensured, with 55% probability, that solutions with better objective function values than the mean solution value of the GAMS were found. Power generation curves for the slack source confirmed that the optimal siting and sizing of PV sources create the duck curve for the power required to the main grid; in addition, the voltage profile curves for both systems show that voltage regulation was always maintained between ±10% in all the time periods under analysis. All the numerical validations were carried out in the MATLAB programming environment with the GAMS optimization package.

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Modelling of Distributed Resource Aggregation for the Provision of Ancillary Services

Energies ◽

10.3390/en13184598 ◽

2020 ◽

Vol 13 (18) ◽

pp. 4598

Author(s):

Adam Lesniak ◽

Dawid Chudy ◽

Rafal Dzikowski

Keyword(s):

Power System ◽

Distribution System ◽

Distribution Systems ◽

Distribution Networks ◽

Optimal Operation ◽

Ancillary Services ◽

Mixed Integer ◽

Large Power ◽

Operation Pattern ◽

Point Of Common Coupling

Nowadays, ancillary services (ASs) are usually provided by large power generating units located in transmission networks, while smaller assets connected to distribution systems remain passive. It is expected that active distribution systems will start to play an important role due to numerous issues related to power system operation caused mainly by developing renewable generation and restrictions imposed on conventional power generating units by climate policies. The future development of the power system management will also lead to the establishment of new market agents such as distributed resource aggregators (DRAs). The article presents the concept of the DRA as part of an active distribution system enabling small resources to participate in wholesale markets, provide ASs and indicates the functions of the DRA coordinator in the modern power system. The proposed method of the DRA structure modelling with the use of the mixed-integer linear programming (MILP) is aimed at evaluating the optimal operation pattern of participating resources, the desired shape of the load profile at the point of common coupling (PCC) and the AS provision. The performed simulations of the DRA’s operation show that various types of aggregated resources located in distribution networks are able to provide different services effectively to support the power system in terms of load–generation balancing and allow for further development of renewables.

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Optimal Placement and Sizing of DGs in Distribution Networks Using MLPSO Algorithm

Energies ◽

10.3390/en13236185 ◽

2020 ◽

Vol 13 (23) ◽

pp. 6185

Author(s):

Eshan Karunarathne ◽

Jagadeesh Pasupuleti ◽

Janaka Ekanayake ◽

Dilini Almeida

Keyword(s):

Power Loss ◽

Distribution Networks ◽

Active Power ◽

Optimization Techniques ◽

Power Grids ◽

Optimal Placement ◽

Unity Power Factor ◽

Suggested Approach ◽

Comparison Of The Results ◽

Bus System

In today’s world, distributed generation (DG) is an outstanding solution to tackle the challenges in power grids such as the power loss of the system that is intensified by the exponential increase in demand for electricity. Numerous optimization algorithms have been used by several researchers to establish the optimal placement and sizing of DGs to alleviate this power loss of the system. However, in terms of the reduction of active power loss, the performance of these algorithms is weaker. Furthermore, the premature convergence, the precision of the output, and the complexity are a few major drawbacks of these optimization techniques. Thus, this paper proposes the multileader particle swarm optimization (MLPSO) for the determination of the optimal locations and sizes of DGs with the objective of active power loss minimization while surmounting the drawbacks in previous algorithms. A comprehensive performance analysis is carried out utilizing the suggested approach on the standard IEEE 33 bus system and a real radial bus system in the Malaysian context. The findings reveal a 67.40% and an 80.32% reduction of losses in the two systems by integrating three DGs with a unity power factor, respectively. The comparison of the results with other optimization techniques demonstrated the effectiveness of the proposed MLPSO algorithm in optimal placement and sizing of DGs.

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The Comparison of Lately Proposed Harris Hawks Optimization and Jaya Optimization in Solving Directional Overcurrent Relays Coordination Problem

Complexity ◽

10.1155/2020/3807653 ◽

2020 ◽

Vol 2020 ◽

pp. 1-22 ◽

Cited By ~ 2

Author(s):

Jiangtao Yu ◽

Chang-Hwan Kim ◽

Sang-Bong Rhee

Keyword(s):

Nonlinear Programming ◽

Convergence Rate ◽

Objective Function ◽

Objective Function Value ◽

Cooperative Behavior ◽

Mixed Integer ◽

Coordination Problem ◽

Computation Efficiency ◽

Design Variables ◽

Overcurrent Relays

In this paper, a lately proposed Harris Hawks Optimizer (HHO) is used to solve the directional overcurrent relays (DOCRs) coordination problem. To the best of the authors’ knowledge, this is the first time HHO is being used in the DOCRs coordination problem. The main inspiration of HHO is the cooperative behavior and chasing style of Harris’ hawks from different directions, based on the dynamic nature of scenarios and escaping patterns of the prey. To test its performances in solving the DOCRs coordination problem, it is adopted in 3-bus, 4-bus, 8-bus, and 9-bus systems, which are formulated by three kinds of optimization models as linear programming (LP), nonlinear programming (NLP), and mixed integer nonlinear programming (MINLP), according to the nature of the design variables. Meanwhile, another lately proposed optimization algorithm named Jaya is also adopted to solve the same problem, and the results are compared with HHO in aspects of objective function value, convergence rate, robustness, and computation efficiency. The comparisons show that the robustness and consistency of HHO is relatively better than Jaya, while Jaya provides faster convergence rate with less CPU time and occasionally more competitive objective function value than HHO.

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Reduction of Losses and Operating Costs in Distribution Networks Using a Genetic Algorithm and Mathematical Optimization

Electronics ◽

10.3390/electronics10040419 ◽

2021 ◽

Vol 10 (4) ◽

pp. 419 ◽

Cited By ~ 3

Author(s):

Fabio Edison Riaño ◽

Jonathan Felipe Cruz ◽

Oscar Danilo Montoya ◽

Harold R. Chamorro ◽

Lazaro Alvarado-Barrios

Keyword(s):

Genetic Algorithm ◽

Distribution System ◽

Power Flow ◽

System Analysis ◽

Classical Method ◽

Mathematical Optimization ◽

Distribution Networks ◽

Mixed Integer ◽

Time Required ◽

Matlab Programming

This study deals with the minimization of the operational and investment cost in the distribution and operation of the power flow considering the installation of fixed-step capacitor banks. This issue is represented by a nonlinear mixed-integer programming mathematical model which is solved by applying the Chu and Beasley genetic algorithm (CBGA). While this algorithm is a classical method for resolving this type of optimization problem, the solutions found using this approach are better than those reported in the literature using metaheuristic techniques and the General Algebraic Modeling System (GAMS). In addition, the time required for the CBGA to get results was reduced to a few seconds to make it a more robust, efficient, and capable tool for distribution system analysis. Finally, the computational sources used in this study were developed in the MATLAB programming environment by implementing test feeders composed of 10, 33, and 69 nodes with radial and meshed configurations.

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Operating Cost Reduction in Distribution Networks Based on the Optimal Phase-Swapping Including the Costs of the Working Groups and Energy Losses

Energies ◽

10.3390/en14154535 ◽

2021 ◽

Vol 14 (15) ◽

pp. 4535

Author(s):

Oscar Montoya ◽

Jorge Alarcon-Villamil ◽

Jesus Hernández

Keyword(s):

Distribution Networks ◽

Voltage Regulation ◽

Energy Losses ◽

Asymmetric Distribution ◽

Three Phase ◽

Working Groups ◽

Sine Cosine Algorithm ◽

Matlab Programming ◽

Power Curves ◽

Bus System

The problem of optimal phase-balancing in three-phase asymmetric distribution networks is addressed in this research from the point of view of combinatorial optimization using a master–slave optimization approach. The master stage employs an improved sine cosine algorithm (ISCA), which is entrusted with determining the load reconfiguration at each node. The slave stage evaluates the energy losses for each set of load connections provided by the master stage by implementing the triangular-based power flow method. The mathematical model that was solved using the ISCA is designed to minimize the annual operating costs of the three-phase network. These costs include the annual costs of the energy losses, considering daily active and reactive power curves, as well as the costs of the working groups tasked with the implementation of the phase-balancing plan at each node. The peak load scenario was evaluated for a 15-bus test system to demonstrate the effectiveness of the proposed ISCA in reducing the power loss (18.66%) compared with optimization methods such as genetic algorithm (18.64%), the classical sine cosine algorithm (18.42%), black-hole optimizer (18.38%), and vortex search algorithm (18.59%). The IEEE 37-bus system was employed to determine the annual total costs of the network before and after implementing the phase-balancing plan provided by the proposed ISCA. The annual operative costs were reduced by about 13% with respect to the benchmark case, with investments between USD 2100 and USD 2200 in phase-balancing activities developed by the working groups. In addition, the positive effects of implementing the phase-balancing plan were evidenced in the voltage performance of the IEEE 37-bus system by improving the voltage regulation with a maximum of 4% in the whole network from an initial regulation of 6.30%. All numerical validations were performed in the MATLAB programming environment.

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Optimal Placement and Sizing of D-STATCOM in Radial and Meshed Distribution Networks Using a Discrete-Continuous Version of the Genetic Algorithm

Electronics ◽

10.3390/electronics10121452 ◽

2021 ◽

Vol 10 (12) ◽

pp. 1452

Author(s):

Cristian Mateo Castiblanco-Pérez ◽

David Esteban Toro-Rodríguez ◽

Oscar Danilo Montoya ◽

Diego Armando Giral-Ramírez

Keyword(s):

Genetic Algorithm ◽

Objective Function ◽

Programming Model ◽

Distribution Networks ◽

Optimization Method ◽

Optimal Placement ◽

Mixed Integer ◽

Power Balance ◽

Continuous Version ◽

Discrete Part

In this paper, we propose a new discrete-continuous codification of the Chu–Beasley genetic algorithm to address the optimal placement and sizing problem of the distribution static compensators (D-STATCOM) in electrical distribution grids. The discrete part of the codification determines the nodes where D-STATCOM will be installed. The continuous part of the codification regulates their sizes. The objective function considered in this study is the minimization of the annual operative costs regarding energy losses and installation investments in D-STATCOM. This objective function is subject to the classical power balance constraints and devices’ capabilities. The proposed discrete-continuous version of the genetic algorithm solves the mixed-integer non-linear programming model that the classical power balance generates. Numerical validations in the 33 test feeder with radial and meshed configurations show that the proposed approach effectively minimizes the annual operating costs of the grid. In addition, the GAMS software compares the results of the proposed optimization method, which allows demonstrating its efficiency and robustness.

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