On representative day selection for capacity expansion planning of power systems under extreme operating conditions

Author(s):  
Can Li ◽  
Antonio J. Conejo ◽  
John D. Siirola ◽  
Ignacio E. Grossmann
Energies ◽  
2020 ◽  
Vol 13 (2) ◽  
pp. 335 ◽  
Author(s):  
Álvaro García-Cerezo ◽  
Luis Baringo ◽  
Raquel García-Bertrand

Short-term uncertainty needs to be properly modeled when analyzing a planning problem in a power system. Since the use of all available historical data may lead to problems of computational intractability, clustering algorithms may be applied in order to reduce the computational effort without compromising accurate representation of historical data. In this paper, we propose a modified version of the traditional K-means method, seeking to represent the maximum and minimum values of input data, namely, electricity demand and renewable production in several locations of a power system. Extreme values of these parameters must be represented as they are high-impact decisions that are taken with respect to expansion and operation. The method proposed is based on the K-means algorithm, which represents the correlation between demand and wind-power production. The chronology of historical data, which influences the performance of some technologies, is characterized through representative days, each made up of 24 operating conditions. A realistic case study, applying representative days, analyzes the generation and transmission expansion planning of the IEEE 24-bus Reliability Test System. Results show that the proposed method is preferable to the traditional K-means technique.


2019 ◽  
Vol 14 (1) ◽  
pp. 5-11
Author(s):  
S. Rajasekaran ◽  
S. Muralidharan

Background: Increasing power demand forces the power systems to operate at their maximum operating conditions. This leads the power system into voltage instability and causes voltage collapse. To avoid this problem, FACTS devices have been used in power systems to increase system stability with much reduced economical ratings. To achieve this, the FACTS devices must be placed in exact location. This paper presents Firefly Algorithm (FA) based optimization method to locate these devices of exact rating and least cost in the transmission system. Methods: Thyristor Controlled Series Capacitor (TCSC) and Static Var Compensator (SVC) are the FACTS devices used in the proposed methodology to enhance the voltage stability of power systems. Considering two objectives of enhancing the voltage stability of the transmission system and minimizing the cost of the FACTS devices, the optimal ratings and cost were identified for the devices under consideration using Firefly algorithm as an optimization tool. Also, a model study had been done with four different cases such as normal case, line outage case, generator outage case and overloading case (140%) for IEEE 14,30,57 and 118 bus systems. Results: The optimal locations to install SVC and TCSC in IEEE 14, 30, 57 and 118 bus systems were evaluated with minimal L-indices and cost using the proposed Firefly algorithm. From the results, it could be inferred that the cost of installing TCSC in IEEE bus system is slightly higher than SVC.For showing the superiority of Firefly algorithm, the results were compared with the already published research finding where this problem was solved using Genetic algorithm and Particle Swarm Optimization. It was revealed that the proposed firefly algorithm gives better optimum solution in minimizing the L-index values for IEEE 30 Bus system. Conclusion: The optimal placement, rating and cost of installation of TCSC and SVC in standard IEEE bus systems which enhanced the voltage stability were evaluated in this work. The need of the FACTS devices was also tested during the abnormal cases such as line outage case, generator outage case and overloading case (140%) with the proposed Firefly algorithm. Outputs reveal that the recognized placement of SVC and TCSC reduces the probability of voltage collapse and cost of the devices in the transmission lines. The capability of Firefly algorithm was also ensured by comparing its results with the results of other algorithms.


Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1658
Author(s):  
Leandro Almeida Vasconcelos ◽  
João Alberto Passos Filho ◽  
André Luis Marques Marcato ◽  
Giovani Santiago Junqueira

The use of Direct Current (DC) transmission links in power systems is increasing continuously. Thus, it is important to develop new techniques to model the inclusion of these devices in network analysis, in order to allow studies of the operation and expansion planning of large-scale electric power systems. In this context, the main objective of this paper is to present a new methodology for a simultaneous AC-DC power flow for a multi-terminal High Voltage Direct Current (HVDC) system with a generic representation of the DC network. The proposed methodology is based on a full Newton formulation for solving the AC-DC power flow problem. Equations representing the converters and steady-state control strategies are included in a power flow problem formulation, resulting in an expanded Jacobian matrix of the Newton method. Some results are presented based on HVDC test systems to confirm the effectiveness of the proposed approach.


2021 ◽  
Vol 13 (12) ◽  
pp. 6708
Author(s):  
Hamza Mubarak ◽  
Nurulafiqah Nadzirah Mansor ◽  
Hazlie Mokhlis ◽  
Mahazani Mohamad ◽  
Hasmaini Mohamad ◽  
...  

Demand for continuous and reliable power supply has significantly increased, especially in this Industrial Revolution 4.0 era. In this regard, adequate planning of electrical power systems considering persistent load growth, increased integration of distributed generators (DGs), optimal system operation during N-1 contingencies, and compliance to the existing system constraints are paramount. However, these issues need to be parallelly addressed for optimum distribution system planning. Consequently, the planning optimization problem would become more complex due to the various technical and operational constraints as well as the enormous search space. To address these considerations, this paper proposes a strategy to obtain one optimal solution for the distribution system expansion planning by considering N-1 system contingencies for all branches and DG optimal sizing and placement as well as fluctuations in the load profiles. In this work, a hybrid firefly algorithm and particle swarm optimization (FA-PSO) was proposed to determine the optimal solution for the expansion planning problem. The validity of the proposed method was tested on IEEE 33- and 69-bus systems. The results show that incorporating DGs with optimal sizing and location minimizes the investment and power loss cost for the 33-bus system by 42.18% and 14.63%, respectively, and for the 69-system by 31.53% and 12%, respectively. In addition, comparative studies were done with a different model from the literature to verify the robustness of the proposed method.


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