Komla A. Folly

Effect of converter DC fault on the transient stability of a Multi-Machine Power System with HVDC transmission lines

This paper deals with the effect of DC faults on the transient stability of a Multi-Machine Power System with two transmission line configurations; HVDC and a hybrid HVAC-HVDC transmission line. The faults are located at the DC terminals of the HVDC converter station. In order to carry out this study, two case studies are presented. In the first case study a double HVDC transmission line is used to transmit 2000MW to an area of the power system called Pookland which has a total load demand of 2440MW. In case two, a parallel hybrid HVAC-HVDC transmission line is used to transmit the same amount of power to Pookland. In both cases, the impact of a short term converter DC fault on the transient stability of the entire system was investigated. This was done by studying the response of the rotor angle of G2 in Pookland, G3 in the Bing Coal plant and the voltage profile at the terminals of the generators to the DC fault at the HVDC converter station. Amongst other results, it was established that in case 1 which has a double HVDC transmission line, the rectifier side (in the Bing coal plant) has less rotor angle oscillations when compared to the inverter side (in Pookland), but the rectifier side took longer than the inverter side for the rotor angle of the generators to stabilize. In case 2, the voltage at G2 in Pookland took six times the amount of time it took G3 in the Bing coal plant to stabilize while the voltage in the Bing Coal plant dipped by 0.35pu (smaller than case 1 which dipped by 0.4pu). In conclusion, the converter DC fault had a smaller impact on the transient stability of the Multi-Machine power system when the hybrid HVAC-HVDC transmission line was adopted.

Assessment of commercially available software tools for transient stability: experience gained in an academic environment

There are many power system simulation software tools for transient stability analysis that are commercially available today. The choice of the most adequate tool for a specific type of stability analysis is a difficult task, and is influenced by economical reasons. It is imperative that a comparative study of various tools be carried out to help users make informed decisions. This work evaluates DIgSILENT, PSS/E and PSCAD, which are commercial software tools used for digital simulation of power systems. As criteria for software assessment, the following features are investigated: (i) modelling capabilities - synchronous generator, generator saturation, transmission line representation, and external network, (ii) flexibility allowed to the user. A well known benchmark power system model from literature is used to validate the simulation results of the commercial tools.

Robust Controller Design Based on a Combination of Genetic Algorithms and Competitive Learning

This paper investigates the robustness of power system stabilizer designs based on an evolutionary algorithm called Population-Based Incremental Learning (PBIL). PBIL combines Genetic Algorithms (GAs) and simple competitive learning derived from Artificial Neural Networks (ANN). The controller design issue is formulated as an optimization problem that is solved via PBIL algorithm. The resulting controllers (PBIL-PSSs) are tested over a wide range of operating conditions for robustness. Simulation results show that PBIL-PSSs are able to stabilize the system adequately over the entire range of operating conditions considered. PBIL-PSSs perform comparably to GA-PSSs under small disturbances but outperform GA-PSSs under large disturbances.

Modeling and simulation of hybrid distributed generation and its impact on transient stability of power system

The present grid is accommodating mixed energies resulting into increasing complexities and instabilities. The dynamic performance is measured by also considering the impact the integration of new technologies such as distributed generation (DG) and hybrid distributed generation (HDG) have on the grid. Hybrid distributed generation with one or more renewable (stochastic) energy sources interact with the existing grid during import and export of power generation. This interaction contributes more fault current therefore making the system vulnerable to instability more than a single energy source. This study investigates the dynamic impact of hybrid Wind/ PV/small Hydro power on transient stability. To investigate this impact, a detail modeling of grid connected wind / solar PV and small hydropower system with single machine infinite system is carried out. The simulation was done in DIgSILENT power factory software. The configuration of the proposed typical grid connected hybrid distributed generation (HDG) consists of variable speed Wind turbine with doubly -fed induction generator (DFIG), solar PV and small hydropower system. The wind turbine is integrated through PWM converter into the existing Grid while the solar PV incorporated into the system consists of DC sources integrated through PWM inverter and the hydro power is directly connected through a synchronous generator.

Design and implementation of power system stabilizers based on evolutionary algorithms

This paper discusses the design and implementation of power system stabilizers based on newly introduced evolutionary algorithms, namely the Population- Based Incremental Learning (PBIL) and the Breeder Genetic Algorithm (BGA) with adaptive mutation. The designed PSSs were implemented on a power system experimental setup and the experimental results are presented in this paper. A Conventional Power System Stabilizer (CPSS) was also designed and implemented for comparison purposes. In total three PSSs were designed and implemented, and their performance compared. It was found that CPSS gives the worst performance and BGA-PSS performs better than the PBIL-PSS for the specific case described in this paper, with the electrical power used as the input to the PSS.

Application of Breeder GA to power system controller design

This paper presents the tuning of power system stabilizer (PSS) parameters using a relatively new evolution algorithm called Breeder Genetic Algorithms (BGAs). BGAs are based on the concept of ldquothe survival of the fittestrdquo typical to Genetic Algorithms (GAs). The main difference between GAs and BGAs is that the evolution of BGAspsila population is based on artificial selection similar to the one used by human breeders. However, unlike GAs, the chromosomes in BGAs are always represented as sequences of real numbers rather than sequences of bits or integers. BGAs are particularly suitable to deal with continuous optimization parameters and are a very powerful and versatile optimization algorithm. The proposed BGA-PSS presented in this paper was tested over a wide range of operating conditions and its performance compared with both the Genetic Algorithm based PSS (GA-PSS) and the Conventional PSS (CPSS). Simulation results show that the performance of the BGA-PSS is better than that of the GA-PSS and the CPSS. However, both the BGA-PSS and the GA-PSS outperform the CPSS.

Voltage Rise Issue with High Penetration of Grid Connected PV

Abstract High penetration of Photovoltaic distributed generators (PV-DG) on the low voltage (LV) grid is as a result of the deregulation of the electricity market and increasing environmental issues related to global warming arising from the use of fossil fuel power plants. The penetration of PV systems on LV grid is seen as a viable option to fossil fuel power plants and it is gaining popularity globally. The PV technology is in a period of rapid expansion and is increasingly becoming important in the electricity market due to their ability to carry out stand-alone power, grid support and greenhouse gases reduction. However, the proliferation of PV on LV grid has raised concern to distribution network operators (DNO) due to the negative impact of high penetration level of PV. The negative impact are protection issues, increased losses, transformer and cable rating issues, sudden voltage rise and reverse power flow which has affected the behavior of the traditional LV grid. The negative impact of high PV penetration has affected the operation of on load tap changers (OLTC) and automatic voltage regulation; therefore, there is a need to incorporate communication with PV and voltage control devices to curtail the voltage rise issues. This paper discusses the issue of sudden voltage rise and reverse power flow resulting from high penetration of PV on LV grid and also the need for a smarter grid.

Robust controller design for small-signal stability enhancement of power systems

The paper proposes a technique for designing a robust power system stabilizer that combines Hinfin optimal control with the bilinear transformation. The bilinear transformation is used to prevent the pole-zero cancellation phenomenon inherent in the Hinfin mixed sensitivity design and to assign dominant poles at desired locations in the s-plane. The technique is applied to design a power system stabilizer for a single machine connected to an infinite bus. The proposed controller is compared with both a conventional lead-lag controller and a controller design based on an evolutionary algorithm called PBIL (population based incremental learning). Frequency and time domain simulations are presented to demonstrate the effectiveness of the proposed design approach

Power ystem controller design: A comparison between breeder genetic algorithm and Population Based Incremental Learning

This paper discusses the design of Power System Stabilizers (PSSs) using an Adaptive Mutation Breeder Genetic Algorithm (BGA) and Population Based Incremental Learning (PBIL). BGA is a new form of evolutionary algorithm. It uses the same idea of survival of the fittest like the Genetic Algorithms, however unlike GA; BGA uses the concept of artificial breeding, whereby the offspring takes the best characteristics from the parents. PBIL is an abstraction of genetic algorithm, which explicitly maintains the key components contained in GAs population, but abstracts away the crossover operator and redefines the role of population. The paper compares the performance and effectiveness of the PSSs in damping the electromechanical modes. In evaluating the different methods, an eigenvalue based objective function was used in the design of the PSSs whereby the algorithm maximizes the lowest damping ratio over specified operating conditions. Eigenvalue analysis and time domain simulations show that the systems equipped with BGA-PSS and PBIL - PSS perform very closely. It is also shown that BGA and PBIL based PSSs perform better that the Conventional PSS (CPSS) at all the operating conditions considered except at the nominal operating condition where the CPSS was tuned.

Parallel PBIL applied to power system controller design

Abstract Population-Based Incremental Learning (PBIL) algorithm is a combination of evolutionary optimization and competitive learning derived from artificial neural networks. PBIL has recently received increasing attention in various engineering fields due to its effectiveness, easy implementation and robustness. Despite these strengths, it was reported in the last few years that PBIL suffers from issues of loss of diversity in the population. To deal with this shortcoming, this paper uses parallel PBIL based on multi-population. In parallel PBIL, two populations are used where both probability vectors (PVs) are initialized to 0.5. It is believed that by introducing two populations, the diversity in the population can be increased and better results can be obtained. The approach is applied to power system controller design. Simulations results show that the parallel PBIL approach performs better than the standard PBIL and is as effective as another diversity increasing PBIL called adaptive PBIL