Optimal Placement of Reactive Power Compensation Banks for the Maximization of New Generation Capacity

2005 ◽  
Vol 4 (1) ◽  
Author(s):  
Panagis N. Vovos ◽  
Janusz W Bialek
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Low Voltage ◽  
Network Capacity ◽  
Optimal Placement ◽  
Test Case ◽  
Investment Cost ◽  
Generation Capacity ◽  
New Generation

The aim of this paper is to present a novel method for the optimal placement of capacitor and reactor banks, with the objective of maximizing network capacity to absorb new generation. The method is an extension of the Optimal Power Flow used as a tool for network capacity analysis. It can be used to a) plot graphs of the bank investment cost with respect to the increase in network capacity and b) find the optimum investment for the network operator in order to maximize his revenue. A 12-bus low voltage network was used as a test case. The results demonstrate the efficiency of the method to allocate new banks. At a small investment cost, network capacity could nearly double.

FACTS Devices Allocation for Power Transfer Capability Enhancement and Power System Losses Reduction

2013 ◽  
Vol 2 (2) ◽  
pp. 1-14 ◽  
Author(s):  
Peerapol Jirapong
Keyword(s):  
Tabu Search ◽  
Power Systems ◽  
Power Loss ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Evolutionary Programming ◽  
Optimal Placement ◽  
Facts Devices ◽  
Transfer Capability

In this paper, a hybrid evolutionary algorithm (HEA) is proposed to determine the optimal placement of multi-type flexible AC transmission system (FACTS) devices to simultaneously maximize the total transfer capability (TTC) and minimize the system real power loss of power transfers in deregulated power systems. Multi-objective optimal power flow (OPF) with FACTS devices including TTC, power losses, and penalty functions is used to evaluate the feasible maximum TTC value and minimum power loss within real and reactive power generation limits, thermal limits, voltage limits, stability limits, and FACTS devices operation limits. Test results on the modified IEEE 30-bus system indicate that optimally placed OPF with FACTS by the HEA approach could enhance TTC far more than those from evolutionary programming (EP), tabu search (TS), hybrid tabu search and simulated annealing (TS/SA), and improved evolutionary programming (IEP) algorithms, leading to much efficient utilization of the existing transmission systems.

Optimal Location of STATCOM, SSSC, and UPFC Devices for Solving OPF and ORPD Problem Using Different Evolutionary Optimization Techniques

2018 ◽  
pp. 274-317
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Power Transmission ◽  
Optimal Placement ◽  
Unified Power Flow Controller ◽  
Krill Herd Algorithm ◽  
Facts Devices ◽  
Bus Voltage ◽  
Evolutionary Optimization Techniques

The development of FACTS devices based on the advance of semiconductor technology opened up new opportunities for controlling the power flow and extending the load ability of the power transmission network. Amongst the various FACTS devices, the UPFC is considered the most versatile FACTS device that can simultaneously control bus voltage and both active and reactive power flow through the transmission line. This chapter discusses the implementation of grey wolf optimization (GWO), teaching-learning-based optimization (TLBO), biogeography-based optimization (BBO), krill herd algorithm (KHA), chemical reaction optimization (CRO), and hybrid CRO (HCRO) approaches to find the optimal placement and parameter setting of unified power flow controller (UPFC) to achieve the optimal performance of optimal power flow (OPF) and optimal reactive power dispatch (ORPD) problems. Two test systems, namely IEEE 14-bus and IEEE 30 with valve-point non-linearity, are considered to demonstrate the effectiveness of proposed approaches.

Flexible Genetic Algorithm Based Optimal Power Flow of Power Systems

2018 ◽  
Vol 24 (3) ◽  
pp. 84
Author(s):  
Hassan Abdullah Kubba ◽  
Mounir Thamer Esmieel
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Test System ◽  
Multi Objective ◽  
Optimal Power ◽  
Blending Method ◽  
Real Coded Genetic Algorithm

Nowadays, the power plant is changing the power industry from a centralized and vertically integrated form into regional, competitive and functionally separate units. This is done with the future aims of increasing efficiency by better management and better employment of existing equipment and lower price of electricity to all types of customers while retaining a reliable system. This research is aimed to solve the optimal power flow (OPF) problem. The OPF is used to minimize the total generations fuel cost function. Optimal power flow may be single objective or multi objective function. In this thesis, an attempt is made to minimize the objective function with keeping the voltages magnitudes of all load buses, real output power of each generator bus and reactive power of each generator bus within their limits. The proposed method in this thesis is the Flexible Continuous Genetic Algorithm or in other words the Flexible Real-Coded Genetic Algorithm (RCGA) using the efficient GA's operators such as Rank Assignment (Weighted) Roulette Wheel Selection, Blending Method Recombination operator and Mutation Operator as well as Multi-Objective Minimization technique (MOM). This method has been tested and checked on the IEEE 30 buses test system and implemented on the 35-bus Super Iraqi National Grid (SING) system (400 KV). The results of OPF problem using IEEE 30 buses typical system has been compared with other researches.     

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 Evaluation and Analysis of Available Transfer Capability in Deregulated Power System Environment

2018 ◽  
Vol 7 (1.8) ◽  
pp. 188
Author(s):  
M Dhana Sai Sri ◽  
P Srinivasa Varma
Keyword(s):  
Power System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Simulation Analysis ◽  
Available Transfer Capability ◽  
High Efficient ◽  
Transfer Capability ◽  
Power System Market ◽  
Bus System

Reliability of network is need of the hour in the present power system market and is constrained by capability of the network. The network calculations are performed using accurate and high efficient strategies. In order to perform power transactions in the system, the computation of available transfer capability is essential which a metric of capability of the system. Generally, effect wattless power is not taken into account in the methodologies for computation of linear available transfer capability. In this paper, a methodology which considers the reactive power flows for enhancement of linear ATC is presented. In order to perform analysis theoretically, a standard IEEE 3 bus system is considered. Another case study i.e., 14 bus system available in IEEE test systems is used for simulation analysis. FACTS technology is incorporated in the existing system in order to enhance capability of the network. To facilitate transfer maximum power in the system, an optimal power-flow-based ATC enhancement model is formulated and presented along with simulation results. Studies based on the IEEE 3-bus system and 14-bus systems with TCSC demonstrate the effectiveness of FACTS control on ATC enhancement.  

OPTIMAL POWER FLOW AND FAULT ANALYSIS USING UPFC

2020 ◽  
Vol 5 (8) ◽  
Author(s):  
Anuj Singh ◽  
Dr. Sandeep Sharma ◽  
Karan Sharma ◽  
Flansha Jain ◽  
Shreyanshu Kumar Jena
Keyword(s):  
Power System ◽  
Power Electronics ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Impedance Control ◽  
Fault Analysis ◽  
Unified Power Flow Controller ◽  
Bus Voltage ◽  
Power Flow Controller

A Power System is actually a vast system that requires an outstanding plan for maintaining the continual flow of electricity. When a fault occurs at the power system, number of difficulties arises because of transients in system. so to attenuate these transients, power electronics based devices like FACTS are utilized. A unified power flow controller (UPFC) is one among different power electronics controller which can dispense VAR compensation, line impedance control and phase shifting. The thought is to see potential of UPFC to require care of active and reactive power movement within the compensated line (including UPFC) and to shrink the falloff of the bus voltage in case of grounding fault within the cable. power system block consisting of simulink is used for numerical analysis. Simulation outcomes from MATLAB reflects major improvement in the overall system’s behaviour with UPFC in sustain the voltage and power flow even under severe line faults by proper injection of series voltage into the cable at the point of connection. outcomes shows how the UPFC contributes effectively to a faster regaining of the power system to the pre-fault conditions.

Optimal Power Flow and Optimal Reactive Power Dispatch Using Different Evolutionary Optimization Techniques

2018 ◽  
pp. 117-157
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Cost Minimization ◽  
Voltage Profile ◽  
Fuel Cost ◽  
Loss Minimization ◽  
Optimal Reactive Power Dispatch ◽  
Reactive Power Dispatch ◽  
Fuel Cost Minimization

This chapter describes grey wolf optimization (GWO), teaching-learning-based optimization (TLBO), biogeography-based optimization (BBO), krill herd algorithm (KHA), chemical reaction optimization (CRO), and hybrid CRO (HCRO) algorithms to solve both single and multi-objective optimal power flow (MOOPF) and optimal reactive power dispatch (ORPD) problems while satisfying various operational constraints. The proposed HCRO approach along with GWO, TLBO, BBO, KHA, and CRO algorithms are implemented on IEEE 30-bus system to solve four different single objectives: fuel cost minimization, system power loss minimization, voltage stability index minimization, and voltage deviation minimization; two bi-objectives optimization, namely minimization of fuel cost and transmission loss; minimization of fuel cost and voltage profile; and one tri-objective optimization, namely minimization of fuel cost, minimization of transmission losses, and improvement of voltage profile simultaneously. The simulation results clearly suggest that the proposed is able to provide a better solution than other approaches.

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