scholarly journals Adaptive Unified Differential Evolution Algorithm for Optimal Operation of Power Systems with Static Security, Transient Stability and Statcom Device

2019 ◽  
Vol 8 (4) ◽  
pp. 3309-3324
Keyword(s):  
Power Systems ◽  
Power System ◽  
Differential Evolution ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Voltage Stability ◽  
Transient Stability ◽  
Generator System ◽  
Optimal Power ◽  
Voltage Transient

The complexity of a power system operating with transient stability/security constraints increases with increased interconnection of power transmission networks. Many of the power system’s secure operations are affected with the voltage/transient instability problems. Thereby, the modern power systems have considered solving optimal power flow (OPF) problems using voltage/transient stability constraints as a tedious and challenging task. Algebraic and differential equations of the voltage/stability constraints are included in non-linear optimal power flow optimization problems. In this work, the OPF problems with voltage/stability constraints are solved using a newly developed reliable and robust technique. Moreover, the impact of a FACTS device such as STATCOM device was investigated to test its impact in the enhancement of power system performance. An adaptive unified differential evolution (AuDE) technique is proposed to search in the non-convex and nonlinear problems to obtain the global optimal solutions. Compared to other existing methods and basic DE, the proposed AuDE algorithm has achieved better results under simulation conditions. The power system’s performance is considerably enhanced with STATCOM device. Efficiency of the proposed method in solving the transient and security constrained power systems for optimal operations were demonstrated using the numerical results obtained from IEEE 39-bus, 10-generator system and IEEE 30-bus, 6-generator system. Due to page limitation only 30-bus systems results are presented.

Multi-Objective Differential Evolution for Voltage Security Constrained Optimal Power Flow in Deregulated Power Systems

2013 ◽  
Vol 14 (6) ◽  
pp. 591-607 ◽  
Author(s):  
J. Preetha Roselyn ◽  
D. Devaraj ◽  
Subhransu Sekhar Dash
Keyword(s):  
Power Systems ◽  
Differential Evolution ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Voltage Stability ◽  
Congestion Management ◽  
Load Shedding ◽  
Voltage Security ◽  
Optimal Power ◽  
Deregulated Power Systems

Abstract Voltage stability is an important issue in the planning and operation of deregulated power systems. The voltage stability problems is a most challenging one for the system operators in deregulated power systems because of the intense use of transmission line capabilities and poor regulation in market environment. This article addresses the congestion management problem avoiding offline transmission capacity limits related to voltage stability by considering Voltage Security Constrained Optimal Power Flow (VSCOPF) problem in deregulated environment. This article presents the application of Multi Objective Differential Evolution (MODE) algorithm to solve the VSCOPF problem in new competitive power systems. The maximum of L-index of the load buses is taken as the indicator of voltage stability and is incorporated in the Optimal Power Flow (OPF) problem. The proposed method in hybrid power market which also gives solutions to voltage stability problems by considering the generation rescheduling cost and load shedding cost which relieves the congestion problem in deregulated environment. The buses for load shedding are selected based on the minimum eigen value of Jacobian with respect to the load shed. In the proposed approach, real power settings of generators in base case and contingency cases, generator bus voltage magnitudes, real and reactive power demands of selected load buses using sensitivity analysis are taken as the control variables and are represented as the combination of floating point numbers and integers. DE/randSF/1/bin strategy scheme of differential evolution with self-tuned parameter which employs binomial crossover and difference vector based mutation is used for the VSCOPF problem. A fuzzy based mechanism is employed to get the best compromise solution from the pareto front to aid the decision maker. The proposed VSCOPF planning model is implemented on IEEE 30-bus system, IEEE 57 bus practical system and IEEE 118 bus system. The pareto optimal front obtained from MODE is compared with reference pareto front and the best compromise solution for all the cases are obtained from fuzzy decision making strategy. The performance measures of proposed MODE in two test systems are calculated using suitable performance metrices. The simulation results show that the proposed approach provides considerable improvement in the congestion management by generation rescheduling and load shedding while enhancing the voltage stability in deregulated power system.

A Novel Optimization Algorithm for Transient Stability Constrained Optimal Power Flow

2016 ◽  
pp. 147-176
Author(s):  
Sourav Paul ◽  
Provas Kumar Roy
Keyword(s):  
Power Systems ◽  
New England ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Transient Stability ◽  
Linear Optimization ◽  
Standard Test ◽  
Optimal Power ◽  
Teaching Learning ◽  
Bus System

Optimal power flow with transient stability constraints (TSCOPF) becomes an effective tool of many problems in power systems since it simultaneously considers economy and dynamic stability of power system. TSC-OPF is a non-linear optimization problem which is not easy to deal directly because of its huge dimension. This paper presents a novel and efficient optimisation approach named the teaching learning based optimisation (TLBO) for solving the TSCOPF problem. The quality and usefulness of the proposed algorithm is demonstrated through its application to four standard test systems namely, IEEE 30-bus system, IEEE 118-bus system, WSCC 3-generator 9-bus system and New England 10-generator 39-bus system. To demonstrate the applicability and validity of the proposed method, the results obtained from the proposed algorithm are compared with those obtained from other algorithms available in the literature. The experimental results show that the proposed TLBO approach is comparatively capable of obtaining higher quality solution and faster computational time.

scholarly journals A Fuzzy Based Evolutionary Algorithm for Solving Multiobjective Optimal Power Flow with FACTS Devices

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
R. Vanitha ◽  
J. Baskaran
Keyword(s):  
Power System ◽  
Differential Evolution ◽  
Goal Programming ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Optimization Technique ◽  
Fuzzy Goal Programming ◽  
Facts Devices ◽  
Optimal Power ◽  
Fuzzy Goal

A new Fuzzy Differential Evolution (FDE) algorithm is proposed for solving multiobjective optimal power flow with FACTS devices. This new optimization technique combines the advantages of Weighted Additive Fuzzy Goal Programming (WAFGP) and Differential Evolution (DE) in enhancing the capacity, stability, and security of the power system. As the weights used in WAFGP would have a significant impact on the operational and economical enhancements achieved in the optimization, they are optimized using evolutionary DE algorithm. This provides a way for exploring a balanced solution for a multiobjective problem without sacrificing any individual objective’s uniqueness and priority. The multiple objectives considered are maximizing the loadability condition of the power system with minimum system real power loss and minimum installation cost of the FACTS devices. Indian utility Neyveli Thermal Power Station (NTPS) 23 bus system is used to test the proposed algorithm using multiple FACTS devices. The results compared with that of DE based fuzzy goal programming (FGP) demonstrates that DE based WAFGP algorithm not only provides a balanced optimal solution for all objectives but also provides the best economical solution.

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