Adaptive Multi Objective Parallel Seeker Optimization Algorithm for Incorporating TCSC Devices into Optimal Power Flow Framework

Shafik, M.B.; Chen, Hongkun; Rashed, Ghamgeen Izat; El‐Sehiemy, Ragab A.

doi:10.1109/access.2019.2905266

Cited by 82 publications

(61 citation statements)

References 31 publications

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“…In addition, TCSC can damp the inter area oscillation of the large power systems and provide an opportunity for power flow modulation in response to different contingencies in the power system. Also The TCSC can modulate the steady-state power flow to retain it inside the lines thermal limits [53]. To guarantee the system stability, the series compensation of the line should be a percentage of the line nominal reactance value (Xline), This percentage can be inductive (Kse.ind) or capacitive (Kse.cap).…”

Section: B Tcscmentioning

confidence: 99%

Allocation of FACTS Devices Using a Probabilistic Multi-Objective Approach Incorporating Various Sources of Uncertainty and Dynamic Line Rating

et al. 2020

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Flexible AC transmission system (FACTS) controller play an essential role in increasing the penetration level of renewable energy resources owing to their ability in continuously controlling the active and reactive power flow in the network. This paper presents a probabilistic multi-objective optimization approach to obtain the optimal sizes and locations of static var compensators (SVCs) and thyristor-controlled series capacitors (TCSCs) in a power transmission network with high penetration level of wind generation. The objective of the problem is to maximize the system loadability while minimizing the network power losses and the installation cost of the FACTS controllers. In this study, the uncertainties associated with wind power generation and the correlated load demand are considered. The uncertainties are handled in this work using the points estimation method. Moreover, the dynamic line ratings (DLRs) of the transmission lines are considered in this work. In this case, the maximum transmission capacity of transmission lines is estimated dynamically according to the weather conditions. Considering the DLRs or transmission lines is expected to avoid unrealistic congestion in the network, and hence, improve its loadability. The optimization problem is solved using the multi-objective teaching-learning based optimization (MO-TLBO) algorithm to find the best locations and ratings for the FACTS controllers. Additionally, a technique based on the fuzzy decisionmaking approach is employed to extract one of the Pareto optimal solutions as the best compromise. The proposed approach is applied on the modified IEEE 30-bus system. The numerical results demonstrate the effectiveness of the proposed approach and show that the maximum loadability limit of the study system increases when considering the DLR. This limit can be enhanced to 123.0% without FACTS controller and 137.0 % ,130 % and 132.0% by SVC, TCSC and (SVC-TCSC) respectively.

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Section: B Tcscmentioning

confidence: 99%

Allocation of FACTS Devices Using a Probabilistic Multi-Objective Approach Incorporating Various Sources of Uncertainty and Dynamic Line Rating

et al. 2020

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“…Also, changing the maximum compensation level and the operating voltage range significantly affects the transmission lines selected for compensation. The authors in [16] find optimal location and size of TCSC devices to minimize the generation costs. An adaptive parallel seeker optimization algorithm is employed to solve a multi-objective OPF problem while a linear recursive sequence tool is utilized to reduce the search space.…”

Section: B Literature Reviewmentioning

confidence: 99%

“…Eqs. (16) and (17) calculate maximum active and reactive power flows using susceptance and conductance values of the installed TCSC capacity block determined in (20)- (21), as further explained in [14]. Eqs.…”

Section: B Subproblemsmentioning

confidence: 99%

Transmission Expansion Planning Model Considering Battery Energy Storage, TCSC and Lines Using AC OPF

Luburić¹,

Pandžić

Carrión

2020

IEEE Access

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Flexibility has become a requirement for modern power systems dominated by renewable generation sources. It can be extracted from different assets, ranging from demand response to fast generating units. This paper proposes an investment model that finds an optimal mix of transmissionlevel non-generation flexible assets: battery energy storage (BES), thyristor-controlled series compensators (TCSC), and transmission lines. The role of BES is to offset renewable generation in time, but its power converter is additionally utilized to provide voltage regulation by injecting/withdrawing reactive power. TCSC is used to alter power flows and increase existing lines' capacity, while new power lines are used to increase bulk power transfer. The proposed planning model uses a linearized AC OPF and employs Benders' decomposition to develop an iterative procedure for obtaining the optimal solution. The presented case study illustrates usefulness of the model for different BES costs and investment policies.

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“…On the other hand, mono-objective OPF is becoming unable to meet the diverse needs of optimal operation of power systems. In this context, multi-objective OPF (MOPF) has attracted growing concerns [15][16][17], since it can coordinate multiple and possibly conflicting objectives. Therefore, this work focuses on the corrective securityconstrained MOPF (SC-MOPF) for the AC/VSC-MTDC system.…”

Section: A Background and Motivationmentioning

confidence: 99%

Security-Constrained Multi-Objective Optimal Power Flow for a Hybrid AC/VSC-MTDC System With Lasso-Based Contingency Filtering

2020

IEEE Access

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In order to coordinate the economy and voltage quality of a meshed AC/VSC-MTDC system, a new corrective security-constrained multi-objective optimal power flow (SC-MOPF) method is presented in this paper. A parallel SC-MOPF model with N-1 security constraints is proposed for corrective control actions of the meshed AC/DC system, in which the minimization of the generation cost and voltage deviation are used as objective functions. To solve this model, a novel parallel bi-criterion evolution indicator based evolutionary algorithm (BCE-IBEA) algorithm is developed to seek multiple well-spread Pareto-optimal solutions through the introduction of parallel computation. In this process, a least absolute shrinkage and selection operator (Lasso)-based N-1 contingency filtering scheme with a composite security index is developed to efficiently screen out the most severe cases from all contingencies. And thereby, the best compromise solutions reflecting the preferences of different decision makers are automatically determined via an integrated decision making technique. Case studies in the modified IEEE 14-and 300bus systems demonstrate that the presented approach manages to address this SC-MOPF problem with significantly improved computational efficiency.INDEX TERMS AC/DC system, multi-objective optimization, optimal power flow, VSC-HVDC, decision making, contingency filtering ,2 c PI are the c PI values, which are respectively obtained by using the Lasso approach and the direct computation according to (19).

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Adaptive Multi Objective Parallel Seeker Optimization Algorithm for Incorporating TCSC Devices into Optimal Power Flow Framework

Cited by 82 publications

References 31 publications

Allocation of FACTS Devices Using a Probabilistic Multi-Objective Approach Incorporating Various Sources of Uncertainty and Dynamic Line Rating

Allocation of FACTS Devices Using a Probabilistic Multi-Objective Approach Incorporating Various Sources of Uncertainty and Dynamic Line Rating

Transmission Expansion Planning Model Considering Battery Energy Storage, TCSC and Lines Using AC OPF

Security-Constrained Multi-Objective Optimal Power Flow for a Hybrid AC/VSC-MTDC System With Lasso-Based Contingency Filtering

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