scholarly journals A Computationally Improved Heuristic Algorithm for Transmission Switching Using Line Flow Thresholds for Load Shed Reduction

2021 ◽  
Author(s):  
Tanveer Hussain ◽  
S M Shafiul Alam ◽  
Timothy M. Hansen ◽  
Siddharth Suryanarayanan
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Heuristic Method ◽  
Search Space ◽  
Load Shedding ◽  
Mesh Topology ◽  
Transmission Switching ◽  
Computational Performance ◽  
Topology Changes ◽  
Line Flow

A computationally improved algorithm to find the best transmission switching (TS) candidate for load shed reduction after (<i>N</i>-2) contingencies is presented. TS is a planned line outage and research from the past shows that changing transmission system's mesh topology changes the power flows and removes post contingency violations (PCVs). One of the major challenges is to find the best TS candidate in a suitable time. Here, the best TS candidate is determined by using a novel heuristic method by decreasing the search space based on proximity to load shedding bus (LSB). The proposed method is capable of finding the best TS candidate faster than the well-known existing algorithm in the literature and guarantees removal of PCVs. Moreover, proposed algorithm is compatible with both AC and DC optimal power flow (OPF) formulations. Finally, the proposed method is implemented by modifying the topology of the transmission system after (<i>N</i>-2) contingencies in the IEEE 39-bus, IEEE 118-bus, and Polish 2383-bus test systems. Two metrics are used to compare results from the proposed method with those from state-of-the-art to show the speedup and accuracy achieved. Parallel computing is used to increase the computational performance of the proposed algorithm.

scholarly journals A Computationally Improved Heuristic Algorithm for Transmission Switching Using Line Flow Thresholds for Load Shed Reduction

2021 ◽  
Author(s):  
Tanveer Hussain ◽  
S M Shafiul Alam ◽  
Timothy M. Hansen ◽  
Siddharth Suryanarayanan
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Heuristic Method ◽  
Search Space ◽  
Load Shedding ◽  
Mesh Topology ◽  
Transmission Switching ◽  
Computational Performance ◽  
Topology Changes ◽  
Line Flow

A computationally improved algorithm to find the best transmission switching (TS) candidate for load shed reduction after (<i>N</i>-2) contingencies is presented. TS is a planned line outage and research from the past shows that changing transmission system's mesh topology changes the power flows and removes post contingency violations (PCVs). One of the major challenges is to find the best TS candidate in a suitable time. Here, the best TS candidate is determined by using a novel heuristic method by decreasing the search space based on proximity to load shedding bus (LSB). The proposed method is capable of finding the best TS candidate faster than the well-known existing algorithm in the literature and guarantees removal of PCVs. Moreover, proposed algorithm is compatible with both AC and DC optimal power flow (OPF) formulations. Finally, the proposed method is implemented by modifying the topology of the transmission system after (<i>N</i>-2) contingencies in the IEEE 39-bus, IEEE 118-bus, and Polish 2383-bus test systems. Two metrics are used to compare results from the proposed method with those from state-of-the-art to show the speedup and accuracy achieved. Parallel computing is used to increase the computational performance of the proposed algorithm.

scholarly journals Smart charging for electric vehicles to minimise charging cost

2017 ◽  
Vol 231 (6) ◽  
pp. 526-534 ◽  
Author(s):  
Yue Wang ◽  
David Infield ◽  
Simon Gill
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Distribution System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Low Voltage ◽  
Wholesale Price ◽  
Heuristic Method ◽  
Domain Model ◽  
Smart Charging

This paper assumes a smart grid framework where the driving patterns for electric vehicles are known, time variations in electricity prices are communicated to householders, and data on voltage variation throughout the distribution system are available. Based on this information, an aggregator with access to this data can be employed to minimise electric vehicles charging costs to the owner whilst maintaining acceptable distribution system voltages. In this study, electric vehicle charging is assumed to take place only in the home. A single-phase Low Voltage (LV) distribution network is investigated where the local electric vehicles penetration level is assumed to be 100%. Electric vehicle use patterns have been extracted from the UK Time of Use Survey data with a 10-min resolution and the domestic base load is generated from an existing public domain model. Apart from the so-called real time price signal, which is derived from the electricity system wholesale price, the cost of battery degradation is also considered in the optimal scheduling of electric vehicles charging. A simple and effective heuristic method is proposed to minimise the electric vehicles’ charging cost whilst satisfying the requirement of state of charge for the electric vehicles’ battery. A simulation in OpenDSS over a period of 24 h has been implemented, taking care of the network constraints for voltage level at the customer connection points. The optimisation results are compared with those obtained using dynamic optimal power flow.

scholarly journals Computational Impacts of SVCs on Optimal Power Flow using Approximated Active-Set Interior Point Algorithm

2021 ◽  
Author(s):  
Sayed Abdullah Sadat ◽  
Xinyang Rui ◽  
mostafa Sahraei-Ardakani
Keyword(s):  
Interior Point ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Optimization Problems ◽  
Interior Point Algorithm ◽  
Active Set ◽  
Computational Performance ◽  
Optimal Power ◽  
Power Dispatch

Interior point methods (IPMs) are popular and powerful methods for solving large-scale nonlinear and nonconvex optimization problems, such as AC optimal power flow (ACOPF). There are various ways to model ACOPF, depending on the objective and the physical components that need to be optimized. This paper models shunt flexible AC transmission systems (FACTS). Shunt FACTS devices such as static VAR compensators (SVCs) are sources for reactive power compensations and addressing voltage stability issues. The co-optimization of SVCs with power dispatch can impact the computational performance of ACOPF. In this paper, we evaluate the performance of different ACOPF formulations with approximated active-set interior point (AASIP) algorithm and co-optimization of SVC set points alongside other decision variables. Our numerical results suggest that both AASIP and SVCs alone improves the computation performance of almost all formulations. The gain in performance, however, depends on the sparsity of the formulation. The most spares formulation, such as branch power flow rectangular voltages (BPFRV), shows the highest gain in performance. In the event of co-optimizing SVCs with power dispatch using AASIP, the performance gain is minimal. Finally, the results are verified using various test cases ranging from 500-bus systems to 9591-bus systems.

scholarly journals Artificial Bee Colony Algorithm for Solving Optimal Power Flow Problem

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Luong Le Dinh ◽  
Dieu Vo Ngoc ◽  
Pandian Vasant
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Artificial Bee Colony ◽  
Optimization Method ◽  
Capacity Limits ◽  
Abc Algorithm ◽  
Bee Colony ◽  
Optimal Power ◽  
Line Flow ◽  
Power Flow Problem

This paper proposes an artificial bee colony (ABC) algorithm for solving optimal power flow (OPF) problem. The objective of the OPF problem is to minimize total cost of thermal units while satisfying the unit and system constraints such as generator capacity limits, power balance, line flow limits, bus voltages limits, and transformer tap settings limits. The ABC algorithm is an optimization method inspired from the foraging behavior of honey bees. The proposed algorithm has been tested on the IEEE 30-bus, 57-bus, and 118-bus systems. The numerical results have indicated that the proposed algorithm can find high quality solution for the problem in a fast manner via the result comparisons with other methods in the literature. Therefore, the proposed ABC algorithm can be a favorable method for solving the OPF problem.

Transient Stability Constrained Line-Flow-Based Optimal Power Flow Analysis

2012 ◽  
Vol 13 (2) ◽  
Author(s):  
Lazarus O. Uzoechi ◽  
Satish M. Mahajan ◽  
Ghadir Radman
Keyword(s):  
New England ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Transient Stability ◽  
Flow Analysis ◽  
Computation Time ◽  
Internal Node ◽  
Machine Model ◽  
Optimal Power ◽  
Line Flow

This paper establishes a new method that adopts the line-flow-based (LFB) approach to develop a transient stability constrained optimal power flow (OPF) analysis called LFB-TSCOPF. The transient energy function (TEF) serves as a direct means of carrying out the stability analysis. The reduction technique was adopted in which the classical machine model was reduced to the internal node model. The proposed method was tested on the WECC 9-bus, three-machine, IEEE 14-bus, five-machine, and the New England 39-bus, ten-machine test systems. The results were compared with other known results from different methods in literature. The results of the active power and total optimal costs are quite promising and consistent with other known methods. The LFB-TSCOPF re-dispatches real power by applying the energy margin performance index as an indication of the generator unit(s) to be rescheduled. The LFB-TSCOPF provides a more comprehensive linear model, reduces computation time and can be useful for online stability studies.

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