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The proliferation of converter-interfaced generation necessitates the investigation of novel small-signal multi-machine interactions. The flexibility and lack of standardisation of converter control approaches results in a plethora of potential implementations, bringing different dynamics that can interact with each other and existing elements of the power system. This paper performs a small-signal analysis of power systems with the inclusion of grid-forming and grid-following converters for varying combinations of common control architectures, in terms of cascaded control loops, within the literature. Investigations are performed for a two-machine system and the WSCC 9-bus (three-machine) system. As well as interaction identification and characterisation, the impact of varying transmission line lengths, system loading, and generation dispatch are investigated.

This paper extends a 1D dynamic physics-based model of the scrape-off layer (SOL) plasma, DIV1D, to include the core SOL and possibly a second target. The extended model is benchmarked on 1D mapped SOLPS-ITER simulations to find input settings for DIV1D that allow it to describe SOL plasmas from upstream to target—calibrating it on a scenario and device basis. The benchmark shows a quantitative match between DIV1D and 1D mapped SOLPS-ITER profiles for the heat flux, electron temperature, and electron density within roughly 50% on: (1) the Tokamak Configuration Variable (TCV) for a gas puff scan; (2) a single SOLPS-ITER simulation of the Upgraded Mega Ampere Spherical Tokamak; and (3) the Upgraded Axially Symmetric Divertor EXperiment in Garching Tokamak (AUG) for a simultaneous scan in heating power and gas puff. Once calibrated, DIV1D self-consistently describes dependencies of the SOL solution on core fluxes and external neutral gas densities for a density scan on TCV whereas a varying SOL width is used in DIV1D for AUG to match a simultaneous change in power and density. The ability to calibrate DIV1D on a scenario and device basis is enabled by accounting for cross field transport with an effective flux expansion factor and by allowing neutrals to be exchanged between SOL and adjacent domains.

In this paper we address the problem of allocating the efforts of a collection of repairmen to a number of deteriorating machines in order to reduce operation costs and to mitigate the cost (and likelihood) of unexpected failures. Notwithstanding these preventive maintenance interventions are aimed at returning the machine to a so-called as-good-as-new state, unforeseeable factors may imply that maintenance interventions are not perfect and the machine is only returned to an earlier (uncertain) state of wear. The problem is modelled as a restless bandit problem and an index policy for the sequential allocation of maintenance tasks is proposed. A series of numerical experiments shows the strong performance of the proposed policy. Moreover, the methodology is of interest in the general context of dynamic resource allocation and restless bandit problems, as well as being useful in the particular imperfect maintenance model described., Comment: Published in Computers and Operations Research (ELSEVIER), July 2020. DOI: https://doi.org/10.1016/j.cor.2020.104927 Article available under the terms of the CC-BY-NC-ND licence

Stabilitas sistem tenaga merupakan kemampuan untuk menjaga variabel sistem agar tetap pada nilai stabil (steady state). Gangguan input penambahan beban yang mengakibatkan sistem eksitasi tidak mampu mengembalikan stabilitas sistem maka diperlukan peralatan yang disebut Power System Stabilizer (PSS). Penggunaan PSS dilakukan dengan mensimulasikan PSS dengan dua pemodelan yaitu sistem kontrol lead-lag dan kontrol PID pada sistem MMIB. Analisis PSS akan dilakukan pada kedua pemodelan kontrol tersebut di mana akan dibandingkan respon tegangan terminal dan performa sudut rotor yang menggunakan optimasi PSO pemodelan secara konvensional dan tanpa penggunaan PSS saat diberikan gangguan. Hasilnya sistem tanpa penggunaan PSS tidak dapat mengembalikan kestabilan akibat dari gangguan yang terjadi dan penggunaan kontrol konvensional serta yang dioptimasi dapat meredam overshoot tegangan terminal dan performa sudut rotor. Dengan hasil penggunaan PID-PSS yang dioptimasi menggunakan PSO lebih baik jika dibandingkan dengan penggunaan kontrol lainnya.

Stabilitas sistem tenaga merupakan kemampuan untuk menjaga variabel sistem agar tetap pada nilai stabil (steady state). Gangguan input penambahan beban yang mengakibatkan sistem eksitasi tidak mampu mengembalikan stabilitas sistem maka diperlukan peralatan yang disebut Power System Stabilizer (PSS). Penggunaan PSS dilakukan dengan mensimulasikan PSS dengan dua pemodelan yaitu sistem kontrol lead-lag dan kontrol PID pada sistem MMIB. Analisis PSS akan dilakukan pada kedua pemodelan kontrol tersebut di mana akan dibandingkan respon tegangan terminal dan performa sudut rotor yang menggunakan optimasi PSO pemodelan secara konvensional dan tanpa penggunaan PSS saat diberikan gangguan. Hasilnya sistem tanpa penggunaan PSS tidak dapat mengembalikan kestabilan akibat dari gangguan yang terjadi dan penggunaan kontrol konvensional serta yang dioptimasi dapat meredam overshoot tegangan terminal dan performa sudut rotor. Dengan hasil penggunaan PID-PSS yang dioptimasi menggunakan PSO lebih baik jika dibandingkan dengan penggunaan kontrol lainnya.

GWSkyNet-Multi is a machine learning model developed for classification of candidate gravitational-wave events detected by the LIGO and Virgo observatories. The model uses limited information released in the low-latency Open Public Alerts to produce prediction scores indicating whether an event is a merger of two black holes, a merger involving a neutron star, or a non-astrophysical glitch. This facilitates time sensitive decisions about whether to perform electromagnetic follow-up of candidate events during LIGO-Virgo-KAGRA (LVK) observing runs. However, it is not well understood how the model is leveraging the limited information available to make its predictions. As a deep learning neural network, the inner workings of the model can be difficult to interpret, impacting our trust in its validity and robustness. We tackle this issue by systematically perturbing the model and its inputs to explain what underlying features and correlations it has learned for distinguishing the sources. We show that the localization area of the 2D sky maps and the computed coherence versus incoherence Bayes factors are used as strong predictors for distinguishing between real events and glitches. The estimated distance to the source is further used to discriminate between binary black hole mergers and mergers involving neutron stars. We leverage these findings to show that events misclassified by GWSkyNet-Multi in LVK's third observing run have distinct sky area, coherence factor, and distance values that influence the predictions and explain these misclassifications. The results help identify the model's limitations and inform potential avenues for further optimization., Comment: 22 pages, 11 figures, submitted to ApJ

To provide real-time visibility of physics-based states, phasor measurement units (PMUs) are deployed throughout power networks. PMU data enable real-time grid monitoring and control -- and is essential in transitioning to smarter grids. Various considerations are taken into account when determining the geographic, optimal PMU placements (OPP). This paper focuses on the control-theoretic, observability aspect of OPP. A myriad of studies have investigated observability-based formulations to determine the OPP within a transmission network. However, they have mostly adopted a simplified representation of system dynamics, ignored basic algebraic equations that model power flows, disregarded including renewables such as solar and wind, and did not model their uncertainty. Consequently, this paper revisits the observability-based OPP problem by addressing the literature's limitations. A nonlinear differential algebraic representation (NDAE) of the power system is considered and implicitly discretized -- using various different discretization approaches -- while explicitly accounting for uncertainty. A moving horizon estimation approach is explored to reconstruct the joint differential and algebraic initial states of the system, as a gateway to the OPP problem which is then formulated as a computationally tractable integer program (IP). Comprehensive numerical simulations on standard power networks are conducted to validate various aspects of this approach and test its robustness to various dynamical conditions.

Design of floating terminals requires integrated approach as it requires multi-machine systems. Master students in mechanical engineering from Multi-machine engineering track at TU Delft were assigned design of floating terminals as part of their Integration Project course. Each of seven student groups designed a specific piece of port equipment that was later integrated in the floating terminal design. This required different design approaches: a detailed one for the equipment design (structure and functionality), and conceptual one for the floating terminal (overall layout and operational strategy). This encouraged the students to develop skills needed in real working environment, managing the design process and decision making within their own group and discussing setup, basic designs and dimensions together with the other groups. Owning their design throughout the entire process was in particularly important to the students, as they wanted other groups to use their equipment design. For the terminal design they needed to make a case for the feasibility of the floating terminal, including logistics simulations and cost. This paper shows the benefits of integrated design project course, the methods used for its implementation, as well as addressing current challenges of online group design work and supervision. Being part of European Horizon 2020 project motivated the students even more to contribute to an overall bigger objective., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Transport Engineering and Logistics

Design of floating terminals requires integrated approach as it requires multi-machine systems. Master students in mechanical engineering from Multi-machine engineering track at TU Delft were assigned design of floating terminals as part of their Integration Project course. Each of seven student groups designed a specific piece of port equipment that was later integrated in the floating terminal design. This required different design approaches: a detailed one for the equipment design (structure and functionality), and conceptual one for the floating terminal (overall layout and operational strategy). This encouraged the students to develop skills needed in real working environment, managing the design process and decision making within their own group and discussing setup, basic designs and dimensions together with the other groups. Owning their design throughout the entire process was in particularly important to the students, as they wanted other groups to use their equipment design. For the terminal design they needed to make a case for the feasibility of the floating terminal, including logistics simulations and cost. This paper shows the benefits of integrated design project course, the methods used for its implementation, as well as addressing current challenges of online group design work and supervision. Being part of European Horizon 2020 project motivated the students even more to contribute to an overall bigger objective., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Transport Engineering and Logistics

Railway networks are to play an increasingly large role in European transportation. This has boosted the urgency of railway innovations, of which the development of decision support systems for conflict resolution is an important aspect. This research contributes to this development by formulating a suitable mathematical approach for railway networks equipped with moving block signalling systems. Two dispatching actions to reschedule trains are applied, namely retiming and reordering. The designed approach is an extension to an existing method, based on graph theory, that is able to reschedule trains in case of conflict. The novel method uses additional node- and arc types in order to ensure moving block suitability. The new node type enables the possibility to create nodes that are related to trains, rather than infrastructure. The new arc type ensures a continuously safe time interval between two trains in the absence of trackside signals. An optimization problem, with the objective of minimizing the maximum propagated delay, is formulated. Hereafter, the performance is evaluated by a case study in the Rotterdam-The Hague corridor. According to the experimental results, the designed model is able to reduce delay propagation up to 50% for the majority of input situations within 10 seconds of computation time. Overall, the designed method shows promising results, but further research will be necessary to make it applicable in practice., Mechanical Engineering | Multi-Machine Engineering

Massive growth in global electrical energy demand has necessitated a genuine exploration and integration of solar and wind energy into the electrical power mix. This incorporation goes a long way in improving the cumulative generated power capacity of the power system. However, wind and solar photovoltaic (PV) are intermittent in nature, making the provisioning of a good maximum power tracking (MPPT) scheme necessary. Furthermore, the integration is characterized by synchronization challenges and introduces various modes of power system oscillations as it is converter-driven. This greatly affects the overall stability of the integrated power mix. Consequently, various technological models have been designed to address these challenges ranging from MPPT schemes, phase-lock loop (PLL), virtual synchronous generator (VSG), power system stabilizers (PSS), flexible AC transmission system (FACTS), coordinated control and artificial intelligence (AI). In this work, a multi-machine power system model is reviewed for integration stability studies. Various technical solutions associated with the integration are also reviewed. MPPT, PLL, VSG, PSS, FACTS, coordinated control, and various optimization technique schemes used for damping controller design are discussed.

Massive growth in global electrical energy demand has necessitated a genuine exploration and integration of solar and wind energy into the electrical power mix. This incorporation goes a long way in improving the cumulative generated power capacity of the power system. However, wind and solar photovoltaic (PV) are intermittent in nature, making the provisioning of a good maximum power tracking (MPPT) scheme necessary. Furthermore, the integration is characterized by synchronization challenges and introduces various modes of power system oscillations as it is converter-driven. This greatly affects the overall stability of the integrated power mix. Consequently, various technological models have been designed to address these challenges ranging from MPPT schemes, phase-lock loop (PLL), virtual synchronous generator (VSG), power system stabilizers (PSS), flexible AC transmission system (FACTS), coordinated control and artificial intelligence (AI). In this work, a multi-machine power system model is reviewed for integration stability studies. Various technical solutions associated with the integration are also reviewed. MPPT, PLL, VSG, PSS, FACTS, coordinated control, and various optimization technique schemes used for damping controller design are discussed.

Railway networks are to play an increasingly large role in European transportation. This has boosted the urgency of railway innovations, of which the development of decision support systems for conflict resolution is an important aspect. This research contributes to this development by formulating a suitable mathematical approach for railway networks equipped with moving block signalling systems. Two dispatching actions to reschedule trains are applied, namely retiming and reordering. The designed approach is an extension to an existing method, based on graph theory, that is able to reschedule trains in case of conflict. The novel method uses additional node- and arc types in order to ensure moving block suitability. The new node type enables the possibility to create nodes that are related to trains, rather than infrastructure. The new arc type ensures a continuously safe time interval between two trains in the absence of trackside signals. An optimization problem, with the objective of minimizing the maximum propagated delay, is formulated. Hereafter, the performance is evaluated by a case study in the Rotterdam-The Hague corridor. According to the experimental results, the designed model is able to reduce delay propagation up to 50% for the majority of input situations within 10 seconds of computation time. Overall, the designed method shows promising results, but further research will be necessary to make it applicable in practice., Mechanical Engineering | Multi-Machine Engineering

Simultaneous optimization of controllers in power systems is a challenging research due to the inherent nonlinearity of such a system. Multi-objective optimization is a useful tool for tuning excitation controllers and minimizing oscillations that are described through definition of transient and small-signal stability in power systems. In this paper, a Two-Area-Four-Machine (TAFM) power system model is tested on multiple short circuit and load disturbances. A multi-objective performance analysis is investigated by observing the system's behaviour in different cases involving the no-preference method and a priori method called weighted sum objective. The analysis is done through observation of two different objective functions. First objective function includes the sum of the integral of time-weighted absolute errors of rotor speed differences, generator voltage, and tie-line power transfer. Second objective function observes time domain elements: overshoot, undershoot, and settling time of machines' rotor speeds. Results are compared for two methods combined with four different algorithms to provide better insight into the computational performance of each algorithm and objective search method. Algorithms used for controllers' parametrization include two novel algorithms: multi-objective ant lion optimizer (MOALO) and salp swarm algorithm (MOSSA), and two classic algorithms: multi-objective particle swarm optimization with velocity relaxation (MOVRPSO) and simulated annealing (MOSA).

In this paper, we propose a coherent framework for multi-machine analysis, using a group clustering model, which can be utilized for predictive maintenance (PdM). The framework benefits from the repetitive structure posed by multiple machines and enables for assessment of health condition, degradation modeling and comparison of machines. It is based on a hierarchical probabilistic model, denoted Gaussian topic model (GTM), where cluster patterns are shared over machines and therefore it allows one to directly obtain proportions of patterns over the machines. This is then used as a basis for cross comparison between machines where identified similarities and differences can lead to important insights about their degradation behaviors. The framework is based on aggregation of data over multiple streams by a predefined set of features extracted over a time window. Moreover, the framework contains a clustering schema which takes uncertainty of cluster assignments into account and where one can specify a desirable degree of reliability of the assignments. By using a multi-machine simulation example, we highlight how the framework can be utilized in order to obtain cluster patterns and inherent variations of such patterns over machines. Furthermore, a comparative study with the commonly used Gaussian mixture model (GMM) demonstrates that GTM is able to identify inherent patterns in the data while the GMM fails. Such result is a consequence of the group level being modeled by the GTM while being absent in the GMM. Hence, the GTM are trained with a view on the data that is not available to the GMM with the consequence that the GMM can miss important, possibly even key cluster patterns. Therefore, we argue that more advanced cluster models, like the GTM, can be key for interpreting and understanding degradation behavior across machines and ultimately for obtaining more efficient and reliable PdM systems., CC BY 4.0Corresponding author: Alexander Karlsson (alexander.karlsson@his.se)This work was supported by grant 2019-00789 at Vinnova, Project: Predictive Maintenance using Advanced Cluster Analysis (PACA)., Predictive Maintenance using Advanced Cluster Analysis (PACA)

In this paper, we propose a coherent framework for multi-machine analysis, using a group clustering model, which can be utilized for predictive maintenance (PdM). The framework benefits from the repetitive structure posed by multiple machines and enables for assessment of health condition, degradation modeling and comparison of machines. It is based on a hierarchical probabilistic model, denoted Gaussian topic model (GTM), where cluster patterns are shared over machines and therefore it allows one to directly obtain proportions of patterns over the machines. This is then used as a basis for cross comparison between machines where identified similarities and differences can lead to important insights about their degradation behaviors. The framework is based on aggregation of data over multiple streams by a predefined set of features extracted over a time window. Moreover, the framework contains a clustering schema which takes uncertainty of cluster assignments into account and where one can specify a desirable degree of reliability of the assignments. By using a multi-machine simulation example, we highlight how the framework can be utilized in order to obtain cluster patterns and inherent variations of such patterns over machines. Furthermore, a comparative study with the commonly used Gaussian mixture model (GMM) demonstrates that GTM is able to identify inherent patterns in the data while the GMM fails. Such result is a consequence of the group level being modeled by the GTM while being absent in the GMM. Hence, the GTM are trained with a view on the data that is not available to the GMM with the consequence that the GMM can miss important, possibly even key cluster patterns. Therefore, we argue that more advanced cluster models, like the GTM, can be key for interpreting and understanding degradation behavior across machines and ultimately for obtaining more efficient and reliable PdM systems., CC BY 4.0Corresponding author: Alexander Karlsson (alexander.karlsson@his.se)This work was supported by grant 2019-00789 at Vinnova, Project: Predictive Maintenance using Advanced Cluster Analysis (PACA)., Predictive Maintenance using Advanced Cluster Analysis (PACA)

In this paper, we propose a coherent framework for multi-machine analysis, using a group clustering model, which can be utilized for predictive maintenance (PdM). The framework benefits from the repetitive structure posed by multiple machines and enables for assessment of health condition, degradation modeling and comparison of machines. It is based on a hierarchical probabilistic model, denoted Gaussian topic model (GTM), where cluster patterns are shared over machines and therefore it allows one to directly obtain proportions of patterns over the machines. This is then used as a basis for cross comparison between machines where identified similarities and differences can lead to important insights about their degradation behaviors. The framework is based on aggregation of data over multiple streams by a predefined set of features extracted over a time window. Moreover, the framework contains a clustering schema which takes uncertainty of cluster assignments into account and where one can specify a desirable degree of reliability of the assignments. By using a multi-machine simulation example, we highlight how the framework can be utilized in order to obtain cluster patterns and inherent variations of such patterns over machines. Furthermore, a comparative study with the commonly used Gaussian mixture model (GMM) demonstrates that GTM is able to identify inherent patterns in the data while the GMM fails. Such result is a consequence of the group level being modeled by the GTM while being absent in the GMM. Hence, the GTM are trained with a view on the data that is not available to the GMM with the consequence that the GMM can miss important, possibly even key cluster patterns. Therefore, we argue that more advanced cluster models, like the GTM, can be key for interpreting and understanding degradation behavior across machines and ultimately for obtaining more efficient and reliable PdM systems., CC BY 4.0Corresponding author: Alexander Karlsson (alexander.karlsson@his.se)This work was supported by grant 2019-00789 at Vinnova, Project: Predictive Maintenance using Advanced Cluster Analysis (PACA)., Predictive Maintenance using Advanced Cluster Analysis (PACA)

In this paper, we propose a coherent framework for multi-machine analysis, using a group clustering model, which can be utilized for predictive maintenance (PdM). The framework benefits from the repetitive structure posed by multiple machines and enables for assessment of health condition, degradation modeling and comparison of machines. It is based on a hierarchical probabilistic model, denoted Gaussian topic model (GTM), where cluster patterns are shared over machines and therefore it allows one to directly obtain proportions of patterns over the machines. This is then used as a basis for cross comparison between machines where identified similarities and differences can lead to important insights about their degradation behaviors. The framework is based on aggregation of data over multiple streams by a predefined set of features extracted over a time window. Moreover, the framework contains a clustering schema which takes uncertainty of cluster assignments into account and where one can specify a desirable degree of reliability of the assignments. By using a multi-machine simulation example, we highlight how the framework can be utilized in order to obtain cluster patterns and inherent variations of such patterns over machines. Furthermore, a comparative study with the commonly used Gaussian mixture model (GMM) demonstrates that GTM is able to identify inherent patterns in the data while the GMM fails. Such result is a consequence of the group level being modeled by the GTM while being absent in the GMM. Hence, the GTM are trained with a view on the data that is not available to the GMM with the consequence that the GMM can miss important, possibly even key cluster patterns. Therefore, we argue that more advanced cluster models, like the GTM, can be key for interpreting and understanding degradation behavior across machines and ultimately for obtaining more efficient and reliable PdM systems., CC BY 4.0Corresponding author: Alexander Karlsson (alexander.karlsson@his.se)This work was supported by grant 2019-00789 at Vinnova, Project: Predictive Maintenance using Advanced Cluster Analysis (PACA)., Predictive Maintenance using Advanced Cluster Analysis (PACA)

In this paper, we propose a coherent framework for multi-machine analysis, using a group clustering model, which can be utilized for predictive maintenance (PdM). The framework benefits from the repetitive structure posed by multiple machines and enables for assessment of health condition, degradation modeling and comparison of machines. It is based on a hierarchical probabilistic model, denoted Gaussian topic model (GTM), where cluster patterns are shared over machines and therefore it allows one to directly obtain proportions of patterns over the machines. This is then used as a basis for cross comparison between machines where identified similarities and differences can lead to important insights about their degradation behaviors. The framework is based on aggregation of data over multiple streams by a predefined set of features extracted over a time window. Moreover, the framework contains a clustering schema which takes uncertainty of cluster assignments into account and where one can specify a desirable degree of reliability of the assignments. By using a multi-machine simulation example, we highlight how the framework can be utilized in order to obtain cluster patterns and inherent variations of such patterns over machines. Furthermore, a comparative study with the commonly used Gaussian mixture model (GMM) demonstrates that GTM is able to identify inherent patterns in the data while the GMM fails. Such result is a consequence of the group level being modeled by the GTM while being absent in the GMM. Hence, the GTM are trained with a view on the data that is not available to the GMM with the consequence that the GMM can miss important, possibly even key cluster patterns. Therefore, we argue that more advanced cluster models, like the GTM, can be key for interpreting and understanding degradation behavior across machines and ultimately for obtaining more efficient and reliable PdM systems., CC BY 4.0Corresponding author: Alexander Karlsson (alexander.karlsson@his.se)This work was supported by grant 2019-00789 at Vinnova, Project: Predictive Maintenance using Advanced Cluster Analysis (PACA)., Predictive Maintenance using Advanced Cluster Analysis (PACA)

Low frequency oscillations (LFOs) occur in a system of interconnected generators connected by weak interconnection. A power system stabilizer (PSS) is commonly used to improve the capacity of the power system dampening. Under a variety of operating conditions, traditional PSSs fail to deliver superior damping. To address this issue, a Farmland Fertility Algorithm (FFA-PSSs controller) was used to solve an optimization problem for optimal design of PSSs system parameters, and its performance efficiency was compared to GA and PSO-based PSSs controllers. In addition to PSS, flexible current transmission (FACTS) devices are widely used. PSSs controllers and FACTS devices are frequently constructed in tandem to improve the dampening efficiency of the system. In this study, an Interline Power Flow Controller (IPFC) FACTS device will be added to the PSSs controller to improve the power system’s oscillatory stability. PSSs optimal design and supplemental controller of power fluctuations for IPFC were conducted out on WSCC multi-machine test systems using a system linear model. Using time-domain simulations and quantitative analysis, the proposed IPFC model was compared to the FFA-PSSs controller in terms of performance and efficiency. The main disadvantage of this technique is the difficulty in designing a dynamic IPFC model in test systems, as well as the burden of IPFC coordinated PSSs optimization. In both PSSs design using FFA method and FFA-optimized PSS with IPFC cases, rise in the computational and simulation costs was found unavoidable. To compensate for these flaws and obtain the research contribution, this paper proposes a Neuro-Fuzzy Controller (NFC) developed as a damping controller that can take the place of the two controllers (research objectives three). The application of the NFC substitute the computational and simulation cost involved in designing multi-machine PSS and IPFC-FACTS systems simultaneously. With the availability of NFC in SIMULINK, a dynamic m

Low frequency oscillations (LFOs) occur in a system of interconnected generators connected by weak interconnection. A power system stabilizer (PSS) is commonly used to improve the capacity of the power system dampening. Under a variety of operating conditions, traditional PSSs fail to deliver superior damping. To address this issue, a Farmland Fertility Algorithm (FFA-PSSs controller) was used to solve an optimization problem for optimal design of PSSs system parameters, and its performance efficiency was compared to GA and PSO-based PSSs controllers. In addition to PSS, flexible current transmission (FACTS) devices are widely used. PSSs controllers and FACTS devices are frequently constructed in tandem to improve the dampening efficiency of the system. In this study, an Interline Power Flow Controller (IPFC) FACTS device will be added to the PSSs controller to improve the power system’s oscillatory stability. PSSs optimal design and supplemental controller of power fluctuations for IPFC were conducted out on WSCC multi-machine test systems using a system linear model. Using time-domain simulations and quantitative analysis, the proposed IPFC model was compared to the FFA-PSSs controller in terms of performance and efficiency. The main disadvantage of this technique is the difficulty in designing a dynamic IPFC model in test systems, as well as the burden of IPFC coordinated PSSs optimization. In both PSSs design using FFA method and FFA-optimized PSS with IPFC cases, rise in the computational and simulation costs was found unavoidable. To compensate for these flaws and obtain the research contribution, this paper proposes a Neuro-Fuzzy Controller (NFC) developed as a damping controller that can take the place of the two controllers (research objectives three). The application of the NFC substitute the computational and simulation cost involved in designing multi-machine PSS and IPFC-FACTS systems simultaneously. With the availability of NFC in SIMULINK, a dynamic m

Improvements in angle stability are commonly a significant emphasis in power system stability management. Although low frequency oscillations (LFOs) may not appear to be too alarming at first appearance, but failure to mitigate the oscillatory signals might cause the system to lose synchronization. To avoid power system disruption, adequate damping force is required for these oscillations. A power system stabilizer (PSS) well-known option for mitigating the effects of these oscillations have good performance for damping local oscillatory modes in general but they cannot sufficiently damp inter-area modes. Also, tuning PSSs control parameters is a difficult task which possess heavy optimization process and sometimes the PSSs design solution does not always provide a satisfactory solution. As a result, traditional PSSs performance fails to provide superior damping under other operating circumstances. Many adaptive control approaches have been proposed to solve this problem, but they are both difficult and expensive. FACTS (Flexible AC Transmission Systems) devices are efficient at suppressing oscillations and increasing power transmission rates. When a power oscillation damping (POD) controller is coupled to the control loop of the FACTS devices, recent research reveal that the FACTS-POD unit can function to introduce additional damping to the inter-area modes sufficiently. POD was connected to an Interline Power Flow Controller (IPFC) in this studies with the purpose of adding further damping to the inter-area oscillation modes found in power systems and simulation results shows a more viable option than PSSs. However, studies have shown that when controller parameters are set incorrectly, different types of controllers may weaken system damping or even worsen system oscillation, thus, the PSS-IPFC-POD controller needs to be designed correctly. Because of this, IPFC-POD coordinated PSSs optimization burden increases the systems computational and simulation cost. To a

To improve the capacity of the power system damping, a power system stabilizers (PSSs) is typically the chosen option. Traditional PSSs performance fails to provide superior damping under other operating circumstances. Many adaptive control approaches have been proposed to solve this problem, but they are both difficult and expensive. Implementing a PSSs damping controller requires extensive system modeling, placing a heavy computational burden on the system, and is a time-consuming process. A Neuro-Fuzzy Controller (NFC), a damping controller that can take the place of the FFA-PSS controller, was proposed to address these shortcomings. The dynamic model of 10-machine test systems under multiple operating conditions was developed with the presence of NFC in SIMULINK. After carrying out the time-domain simulation on the New England IEEE test system, the proposed NFC model produced a 13% rotor speed and 43% rotor angle respective angle stability enhancement in G5 based on the time to settle when compared to the FFA-PSS model. Our work has led us to conclude that the simulation results with the proposed NFC model shows that the Electromechanical Modes (EMs) eigenvalues were shifted to the left in S-plane and the system damping was greatly enhanced.

To improve the capacity of the power system damping, a power system stabilizers (PSSs) is typically the chosen option. Traditional PSSs performance fails to provide superior damping under other operating circumstances. Many adaptive control approaches have been proposed to solve this problem, but they are both difficult and expensive. Implementing a PSSs damping controller requires extensive system modeling, placing a heavy computational burden on the system, and is a time-consuming process. A Neuro-Fuzzy Controller (NFC), a damping controller that can take the place of the FFA-PSS controller, was proposed to address these shortcomings. The dynamic model of 10-machine test systems under multiple operating conditions was developed with the presence of NFC in SIMULINK. After carrying out the time-domain simulation on the New England IEEE test system, the proposed NFC model produced a 13% rotor speed and 43% rotor angle respective angle stability enhancement in G5 based on the time to settle when compared to the FFA-PSS model. Our work has led us to conclude that the simulation results with the proposed NFC model shows that the Electromechanical Modes (EMs) eigenvalues were shifted to the left in S-plane and the system damping was greatly enhanced.

Improvements in angle stability are commonly a significant emphasis in power system stability management. Although low frequency oscillations (LFOs) may not appear to be too alarming at first appearance, but failure to mitigate the oscillatory signals might cause the system to lose synchronization. To avoid power system disruption, adequate damping force is required for these oscillations. A power system stabilizer (PSS) well-known option for mitigating the effects of these oscillations have good performance for damping local oscillatory modes in general but they cannot sufficiently damp inter-area modes. Also, tuning PSSs control parameters is a difficult task which possess heavy optimization process and sometimes the PSSs design solution does not always provide a satisfactory solution. As a result, traditional PSSs performance fails to provide superior damping under other operating circumstances. Many adaptive control approaches have been proposed to solve this problem, but they are both difficult and expensive. FACTS (Flexible AC Transmission Systems) devices are efficient at suppressing oscillations and increasing power transmission rates. When a power oscillation damping (POD) controller is coupled to the control loop of the FACTS devices, recent research reveal that the FACTS-POD unit can function to introduce additional damping to the inter-area modes sufficiently. POD was connected to an Interline Power Flow Controller (IPFC) in this studies with the purpose of adding further damping to the inter-area oscillation modes found in power systems and simulation results shows a more viable option than PSSs. However, studies have shown that when controller parameters are set incorrectly, different types of controllers may weaken system damping or even worsen system oscillation, thus, the PSS-IPFC-POD controller needs to be designed correctly. Because of this, IPFC-POD coordinated PSSs optimization burden increases the systems computational and simulation cost. To a

Conventional state estimation routines of electrical grids are mainly reliant on dynamic models of fossil fuel-based resources. These models commonly contain differential equations describing synchronous generator models and algebraic equations modeling power flow/balance equations. Fuel-free power systems that are driven by inertia-less renewable energy resources will hence require new models and upgraded estimation routines. To that end, in this paper we propose a robust estimator for an interconnected model of power networks comprised of a comprehensive ninth order synchronous generator model, advanced power electronics-based models for photovoltaic (PV) power plants, constant power loads, constant impedance loads, and motor loads. The presented state estimator design is based on Lyapunov stability criteria for nonlinear differential algebraic equation (DAE) models and is posed as a convex semi-definite optimization problem. Thorough simulations studies have been carried out on IEEE-39 bus test system to showcase the robustness of the proposed estimator against unknown uncertainty from load demand and solar irradiance., Comment: To Appear in the 61st IEEE Conference on Decision and Control (CDC), Canc\'un, Mexico, December 2022

Dynamic state and parameter estimation (DSE) plays a key role for reliably monitoring and operating future, power-electronics-dominated power systems. While DSE is a very active research field, experimental applications of proposed algorithms to real-world systems remain scarce. This motivates the present paper, in which we demonstrate the effectiveness of a DSE algorithm previously presented by parts of the authors with real-world data collected by a Phasor Measurement Unit (PMU) at a substation close to a power plant within the extra-high voltage grid of Germany. To this end, at first we derive a suitable mapping of the real-world PMU-measurements recorded at a substation close to the power plant to the terminal bus of the power plants' synchronous generator (SG). This mapping considers the high-voltage (HV) transmission line, the tap-changing transformer and the auxiliary system of the power plant. Next, we introduce several practically motivated extensions to the estimation algorithm, which significantly improve its practical performance with real-world measurements. Finally, we successfully validate the algorithm experimentally in an auto- as well as a cross-validation., Comment: 10 pages, 8 figures

This study describes the process of interconnected multi-machine power system stabilizer (PSS) optimization using a new intelligent technique called farmland fertility algorithm (FFA) to increase the stability of IEEE three machine nine bus power system and offset the low-frequency oscillations (LFOs) during a symmetrical 100 ms three-phase fault at bus 9. The FFA-PSS controller performance is compared with two familiar classical techniques, i.e. Genetic Algorithm (GA-PSS) and Particle Swarm Optimization (PSO-PSS) to confirm the capability of the proposed technique to realize improved system stability enhancement. The Eigenvalue simulation results with FFA produce stable Eigenvalues that increase the damping ratio of the Electromechanical Modes (EMs) to more than 0.1 with smaller overshoots and time to settle which shows the effectiveness of the method for multi-machine stability improvement. Also, the phasor simulation results show that the transient responses of the system rise time, settling time, peak time and peak magnitude were all impressively improved by an acceptable amount for the interconnected system with the proposed FFA-PSS thus, was able to control the LFOs effectively and produces enhanced performance compared to the GA and PSO based PSS. Similarly, the result validates the effectiveness of the proposed FFA tuned PSS for LFO control which demonstrates robustness, efficiency, and convergence speed ability than the classical GA and PSO tuning methods.

This study describes the process of interconnected multi-machine power system stabilizer (PSS) optimization using a new intelligent technique called farmland fertility algorithm (FFA) to increase the stability of IEEE three machine nine bus power system and offset the low-frequency oscillations (LFOs) during a symmetrical 100 ms three-phase fault at bus 9. The FFA-PSS controller performance is compared with two familiar classical techniques, i.e. Genetic Algorithm (GA-PSS) and Particle Swarm Optimization (PSO-PSS) to confirm the capability of the proposed technique to realize improved system stability enhancement. The Eigenvalue simulation results with FFA produce stable Eigenvalues that increase the damping ratio of the Electromechanical Modes (EMs) to more than 0.1 with smaller overshoots and time to settle which shows the effectiveness of the method for multi-machine stability improvement. Also, the phasor simulation results show that the transient responses of the system rise time, settling time, peak time and peak magnitude were all impressively improved by an acceptable amount for the interconnected system with the proposed FFA-PSS thus, was able to control the LFOs effectively and produces enhanced performance compared to the GA and PSO based PSS. Similarly, the result validates the effectiveness of the proposed FFA tuned PSS for LFO control which demonstrates robustness, efficiency, and convergence speed ability than the classical GA and PSO tuning methods.

In this paper, we address the two-stage multi-machine assembly scheduling problem, a layout consisting of several dedicated parallel machines in the first stage and identical parallel machines in the second stage. The objective considered is the minimisation of the total completion time. Despite its relevance in practice and its NP-hard nature, this problem has not received much attention so far in the literature. In our paper, we propose two new efficient heuristics. The first heuristic constructs a solution taking into account some specific knowledge of the problem domain. This algorithm is embedded into a beam search-based constructive heuristic and its behaviour when the beam width takes different values is analysed. The computational experiments carried out show that the proposals are more efficient than the existing heuristics for the problem and also the adaptations of heuristics from related problems.

This study presents the design of intelligent coordinators for the automatic voltage regulator (AVR) and power system stabiliser (PSS) in a multi-machine power system. The intelligent coordinators are designed to update the gains of AVR and PSS in severe disturbances to guarantee the stability of the studied power system. Three potent intelligent coordinators are proposed: (a) fuzzy logic coordinator, (b) artificial neural network coordinator, and (c) brain emotional learning coordinator. Since the intelligent coordinators are based on the knowledge of the experts, desirable scaling factors are considered in the output signals of the coordinators to achieve optimal results. The scaling factors are optimised using a new evolutionary approach known as the sine–cosine algorithm. To evaluate the efficiency of the proposed intelligent approaches, the performances of coordinators are analysed on a two-area four-machine power system. A range of power system signals, such as rotor speed, terminal voltages, acceleration power and rotor angle of generators are demonstrated to approve and compare the performance of the intelligent coordinators. The simulation results indicate that the intelligent coordinators can guarantee the stability of the power system and satisfy performance objectives, such as desired transient and steady-state errors.

In this paper, we address the two-stage multi-machine assembly scheduling problem, a layout consisting of several dedicated parallel machines in the first stage and identical parallel machines in the second stage. The objective considered is the minimisation of the total completion time. Despite its relevance in practice and its NP-hard nature, this problem has not received much attention so far in the literature. In our paper, we propose two new efficient heuristics. The first heuristic constructs a solution taking into account some specific knowledge of the problem domain. This algorithm is embedded into a beam search-based constructive heuristic and its behaviour when the beam width takes different values is analysed. The computational experiments carried out show that the proposals are more efficient than the existing heuristics for the problem and also the adaptations of heuristics from related problems.

Design of floating terminals requires integrated approach as it requires multi-machine systems. Master students in mechanical engineering from Multi-ma-chine engineering track at TU Delft were assigned design of floating terminals as part of their Integration Project course. Each of seven student groups designed a specific piece of port equipment that was later integrated in the floating terminal design. This required different design approaches: a detailed one for the equipment design (structure and functionality), and conceptual one for the floating terminal (overall layout and operational strategy). This encouraged the students to develop skills needed in real working environment, managing the design process and deci-sion making within their own group and discussing setup, basic designs and dimen-sions together with the other groups. Owning their design throughout the entire pro-cess was in particularly important to the students, as they wanted other groups to use their equipment design. For the terminal design they needed to make a case for the feasibility of the floating terminal, including logistics simulations and cost. This paper shows the benefits of integrated design project course, the methods used for its implementation, as well as addressing current challenges of online group design work and supervision. Being part of European Horizon 2020 project motivated the students even more to contribute to an overall bigger objective., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Transport Engineering and Logistics

This study presents the design of intelligent coordinators for the automatic voltage regulator (AVR) and power system stabiliser (PSS) in a multi-machine power system. The intelligent coordinators are designed to update the gains of AVR and PSS in severe disturbances to guarantee the stability of the studied power system. Three potent intelligent coordinators are proposed: (a) fuzzy logic coordinator, (b) artificial neural network coordinator, and (c) brain emotional learning coordinator. Since the intelligent coordinators are based on the knowledge of the experts, desirable scaling factors are considered in the output signals of the coordinators to achieve optimal results. The scaling factors are optimised using a new evolutionary approach known as the sine–cosine algorithm. To evaluate the efficiency of the proposed intelligent approaches, the performances of coordinators are analysed on a two-area four-machine power system. A range of power system signals, such as rotor speed, terminal voltages, acceleration power and rotor angle of generators are demonstrated to approve and compare the performance of the intelligent coordinators. The simulation results indicate that the intelligent coordinators can guarantee the stability of the power system and satisfy performance objectives, such as desired transient and steady-state errors.

In this paper, we address the two-stage multi-machine assembly scheduling problem, a layout consisting of several dedicated parallel machines in the first stage and identical parallel machines in the second stage. The objective considered is the minimisation of the total completion time. Despite its relevance in practice and its NP-hard nature, this problem has not received much attention so far in the literature. In our paper, we propose two new efficient heuristics. The first heuristic constructs a solution taking into account some specific knowledge of the problem domain. This algorithm is embedded into a beam search-based constructive heuristic and its behaviour when the beam width takes different values is analysed. The computational experiments carried out show that the proposals are more efficient than the existing heuristics for the problem and also the adaptations of heuristics from related problems.

In this paper, we address the two-stage multi-machine assembly scheduling problem, a layout consisting of several dedicated parallel machines in the first stage and identical parallel machines in the second stage. The objective considered is the minimisation of the total completion time. Despite its relevance in practice and its NP-hard nature, this problem has not received much attention so far in the literature. In our paper, we propose two new efficient heuristics. The first heuristic constructs a solution taking into account some specific knowledge of the problem domain. This algorithm is embedded into a beam search-based constructive heuristic and its behaviour when the beam width takes different values is analysed. The computational experiments carried out show that the proposals are more efficient than the existing heuristics for the problem and also the adaptations of heuristics from related problems.

In this paper, we address the two-stage multi-machine assembly scheduling problem, a layout consisting of several dedicated parallel machines in the first stage and identical parallel machines in the second stage. The objective considered is the minimisation of the total completion time. Despite its relevance in practice and its NP-hard nature, this problem has not received much attention so far in the literature. In our paper, we propose two new efficient heuristics. The first heuristic constructs a solution taking into account some specific knowledge of the problem domain. This algorithm is embedded into a beam search-based constructive heuristic and its behaviour when the beam width takes different values is analysed. The computational experiments carried out show that the proposals are more efficient than the existing heuristics for the problem and also the adaptations of heuristics from related problems.

Design of floating terminals requires integrated approach as it requires multi-machine systems. Master students in mechanical engineering from Multi-ma-chine engineering track at TU Delft were assigned design of floating terminals as part of their Integration Project course. Each of seven student groups designed a specific piece of port equipment that was later integrated in the floating terminal design. This required different design approaches: a detailed one for the equipment design (structure and functionality), and conceptual one for the floating terminal (overall layout and operational strategy). This encouraged the students to develop skills needed in real working environment, managing the design process and deci-sion making within their own group and discussing setup, basic designs and dimen-sions together with the other groups. Owning their design throughout the entire pro-cess was in particularly important to the students, as they wanted other groups to use their equipment design. For the terminal design they needed to make a case for the feasibility of the floating terminal, including logistics simulations and cost. This paper shows the benefits of integrated design project course, the methods used for its implementation, as well as addressing current challenges of online group design work and supervision. Being part of European Horizon 2020 project motivated the students even more to contribute to an overall bigger objective., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Transport Engineering and Logistics

We propose a novel decentralized mixed algebraic and dynamic state observation method for multi-machine power systems with unknown inputs and equipped with Phasor Measurement Units (PMUs). More specifically, we prove that for the third-order flux-decay model of a synchronous generator, the local PMU measurements give enough information to reconstruct algebraically the load angle and the quadrature-axis internal voltage. Due to the algebraic structure a high numerical efficiency is achieved, which makes the method applicable to large scale power systems. Also, we prove that the relative shaft speed can be globally estimated combining a classical Immersion and Invariance (I&I) observer with - the recently introduced - dynamic regressor and mixing (DREM) parameter estimator. This adaptive observer ensures global convergence under weak excitation assumptions that are verified in applications. The proposed method does not require the measurement of exogenous inputs signals such as the field voltage and the mechanical torque nor the knowledge of mechanical subsystem parameters., Comment: 10 pages, 11 figures

The assembly scheduling problem is a common layout with many applications in real manufacturing scenarios. Despite the high number of studies dealing with this problem, no benchmark has been proposed up-to-now in the literature generating neither hard nor balanced instances. In this paper we present two extensive sets of instances for two variants of the 2-stage assembly scheduling problem. The first set is composed of 240 instances for the variant with one assembly machine in the second stage, while in the second set 960 instances are proposed for the variant with several assembly machines. An exhaustive experimental procedure, generating several preliminary testbeds with different processing times and number of jobs and machines, is carried out in order to identify the most representative instances of the problem under study. A total of 120,000 instances are generated and, among them, 1,200 are selected ensuring that the new benchmarks satisfy the desired characteristics of any benchmark: adequacy, empirical hardness, exhaustiveness, and amenity for statistical analysis. Finally, two computational evaluations are performed comparing and evaluating the existing heuristics in the literature, thus establishing the set of efficient heuristics for this assembly problem.

In this paper the problem of modeling and simulation of voltage stability is improved using Static Synchronous Series Compensator (SSSC). Due to the continuous demand in electric power system, the system is heavily loaded, this causes to voltage instability. In this work, a static synchronous series compensator (SSSC) is used to minimize the effect of this device in controlling active and reactive powers as well as damping power system oscillations in transient mode. The PI controller is used to achieve the zero signal error. The result is obtained from simulation using MATLAB. In short when any disturbances occur in transmission line, if SSSC is connected then disturbance in the system is minimized & system will reach the steady state condition very quickly

In this paper the problem of modeling and simulation of voltage stability is improved using Static Synchronous Series Compensator (SSSC). Due to the continuous demand in electric power system, the system is heavily loaded, this causes to voltage instability. In this work, a static synchronous series compensator (SSSC) is used to minimize the effect of this device in controlling active and reactive powers as well as damping power system oscillations in transient mode. The PI controller is used to achieve the zero signal error. The result is obtained from simulation using MATLAB. In short when any disturbances occur in transmission line, if SSSC is connected then disturbance in the system is minimized & system will reach the steady state condition very quickly

In this paper the problem of modeling and simulation of voltage stability is improved using Static Synchronous Series Compensator (SSSC). Due to the continuous demand in electric power system, the system is heavily loaded, this causes to voltage instability. In this work, a static synchronous series compensator (SSSC) is used to minimize the effect of this device in controlling active and reactive powers as well as damping power system oscillations in transient mode. The PI controller is used to achieve the zero signal error. The result is obtained from simulation using MATLAB. In short when any disturbances occur in transmission line, if SSSC is connected then disturbance in the system is minimized & system will reach the steady state condition very quickly

In this paper the problem of modeling and simulation of voltage stability is improved using Static Synchronous Series Compensator (SSSC). Due to the continuous demand in electric power system, the system is heavily loaded, this causes to voltage instability. In this work, a static synchronous series compensator (SSSC) is used to minimize the effect of this device in controlling active and reactive powers as well as damping power system oscillations in transient mode. The PI controller is used to achieve the zero signal error. The result is obtained from simulation using MATLAB. In short when any disturbances occur in transmission line, if SSSC is connected then disturbance in the system is minimized & system will reach the steady state condition very quickly

In this paper the problem of modeling and simulation of voltage stability is improved using Static Synchronous Series Compensator (SSSC). Due to the continuous demand in electric power system, the system is heavily loaded, this causes to voltage instability. In this work, a static synchronous series compensator (SSSC) is used to minimize the effect of this device in controlling active and reactive powers as well as damping power system oscillations in transient mode. The PI controller is used to achieve the zero signal error. The result is obtained from simulation using MATLAB. In short when any disturbances occur in transmission line, if SSSC is connected then disturbance in the system is minimized & system will reach the steady state condition very quickly

In this paper the problem of modeling and simulation of voltage stability is improved using Static Synchronous Series Compensator (SSSC). Due to the continuous demand in electric power system, the system is heavily loaded, this causes to voltage instability. In this work, a static synchronous series compensator (SSSC) is used to minimize the effect of this device in controlling active and reactive powers as well as damping power system oscillations in transient mode. The PI controller is used to achieve the zero signal error. The result is obtained from simulation using MATLAB. In short when any disturbances occur in transmission line, if SSSC is connected then disturbance in the system is minimized & system will reach the steady state condition very quickly

The assembly scheduling problem is a common layout with many applications in real manufacturing scenarios. Despite the high number of studies dealing with this problem, no benchmark has been proposed up-to-now in the literature generating neither hard nor balanced instances. In this paper we present two extensive sets of instances for two variants of the 2-stage assembly scheduling problem. The first set is composed of 240 instances for the variant with one assembly machine in the second stage, while in the second set 960 instances are proposed for the variant with several assembly machines. An exhaustive experimental procedure, generating several preliminary testbeds with different processing times and number of jobs and machines, is carried out in order to identify the most representative instances of the problem under study. A total of 120,000 instances are generated and, among them, 1,200 are selected ensuring that the new benchmarks satisfy the desired characteristics of any benchmark: adequacy, empirical hardness, exhaustiveness, and amenity for statistical analysis. Finally, two computational evaluations are performed comparing and evaluating the existing heuristics in the literature, thus establishing the set of efficient heuristics for this assembly problem.

The assembly scheduling problem is a common layout with many applications in real manufacturing scenarios. Despite the high number of studies dealing with this problem, no benchmark has been proposed up-to-now in the literature generating neither hard nor balanced instances. In this paper we present two extensive sets of instances for two variants of the 2-stage assembly scheduling problem. The first set is composed of 240 instances for the variant with one assembly machine in the second stage, while in the second set 960 instances are proposed for the variant with several assembly machines. An exhaustive experimental procedure, generating several preliminary testbeds with different processing times and number of jobs and machines, is carried out in order to identify the most representative instances of the problem under study. A total of 120,000 instances are generated and, among them, 1,200 are selected ensuring that the new benchmarks satisfy the desired characteristics of any benchmark: adequacy, empirical hardness, exhaustiveness, and amenity for statistical analysis. Finally, two computational evaluations are performed comparing and evaluating the existing heuristics in the literature, thus establishing the set of efficient heuristics for this assembly problem.

In this paper the problem of modeling and simulation of voltage stability is improved using Static Synchronous Series Compensator (SSSC). Due to the continuous demand in electric power system, the system is heavily loaded, this causes to voltage instability. In this work, a static synchronous series compensator (SSSC) is used to minimize the effect of this device in controlling active and reactive powers as well as damping power system oscillations in transient mode. The PI controller is used to achieve the zero signal error. The result is obtained from simulation using MATLAB. In short when any disturbances occur in transmission line, if SSSC is connected then disturbance in the system is minimized & system will reach the steady state condition very quickly

The assembly scheduling problem is a common layout with many applications in real manufacturing scenarios. Despite the high number of studies dealing with this problem, no benchmark has been proposed up-to-now in the literature generating neither hard nor balanced instances. In this paper we present two extensive sets of instances for two variants of the 2-stage assembly scheduling problem. The first set is composed of 240 instances for the variant with one assembly machine in the second stage, while in the second set 960 instances are proposed for the variant with several assembly machines. An exhaustive experimental procedure, generating several preliminary testbeds with different processing times and number of jobs and machines, is carried out in order to identify the most representative instances of the problem under study. A total of 120,000 instances are generated and, among them, 1,200 are selected ensuring that the new benchmarks satisfy the desired characteristics of any benchmark: adequacy, empirical hardness, exhaustiveness, and amenity for statistical analysis. Finally, two computational evaluations are performed comparing and evaluating the existing heuristics in the literature, thus establishing the set of efficient heuristics for this assembly problem.