Enhancement of Solar PV Hosting Capacity in a Remote Industrial Microgrid: A Methodical Techno-Economic Approach

To meet the zero-carbon electricity generation target as part of the sustainable development goals (SDG7), remote industrial microgrids worldwide are considering the uptake of more and more renewable energy resources, especially solar PV systems. Estimating the grid PV hosting capacity plays an essential role in designing and planning such microgrids. PV hosting capacity assessment determines the maximum PV capacity suitable for the grid and the appropriate electrical location for PV placement. This research reveals that conventional static criteria to assess the PV hosting capacity fail to ensure the grid’s operational robustness. It hence demands a reduction in the theoretical hosting capacity estimation to ensure grid compatible post-fault voltage and frequency recovery. Energy storage technologies, particularly fast-responsive batteries, can potentially prevent such undesirable scenarios; nevertheless, careful integration is required to ensure an affordable cost of energy. This study proposes a novel methodical techno-economic approach for an off-grid remote industrial microgrid to enhance the PV hosting capacity by integrating battery energy storage considering grid disturbance and recovery scenarios. The method has been validated in an industrial microgrid with a 2.6 MW peak demand in a ready-made garment (RMG) factory having a distinctive demand pattern and unique constraints in remote Bangladesh. According to the analysis, integrating 2.5 MW of PV capacity and a 1.2 MVA battery bank to offset existing diesel and grid consumption would result in an energy cost of BDT 14.60 per kWh (USD 0.1719 per kWh). For high PV penetration scenarios, the application of this method offers higher system robustness, and the financial analysis indicates that the industries would not only benefit from positive environmental impact but also make an economic profit

Detection of stator interturn fault of synchronous machine by rotor current analysis : A SIMULATION APPROACH

One of the major electrical faults of synchronous machines is an interturn short circuit in the stator winding, due to winding insulation failure. A synchronous machine is designed to have electrical and mechanical symmetry in the stator and rotor. An interturn fault in a synchronous machine damages the symmetrical property, thereby inducing abnormal symptoms like varying torque, mechanical vibration, and deviation of stator and rotor terminal currents from their usual waveform. This last symptom is what is studied in this thesis, as an indicator of the presence of an interturn fault. An interturn fault during machine operation can lead to a catastrophic machine failure and consequent long outage, unless it is rapidly detected and the machine shut down. Prevention of such outages is an important concern for machine owners and power system operators. That is why early detection of interturn faults is desirable to prevent such machine failure. Several external sensors can be implemented to detect such interturn fault, which is costly. That is why it is desirable if the interturn fault can be detected by analyzing the measured currents that already are available to a protective relay. In this thesis a simulation approach is presented to observe the pattern and frequency spectrum of rotor field current in presence of a stator inter turn fault. All simulations have been performed using Matlab-based programs written during this thesis work in the Electromagnetic department (ETK) in KTH. The outcome of the thesis is that in the presence of an interturn fault in the stator, several even harmonic components are found in the frequency spectrum of the rotor field current. The presence of these harmonics is not a definitive sign of an interturn fault, as almost the same even harmonics are found in the rotor field current if the stator winding asymmetry is taken into account.En av de största elektriska felen i synkronmaskiner är en kortslutning mellan varv i statorlindningen, på grund av skadad lindningsisolering. En synkronmaskins konstruktion ger elektrisk och mekanisk symmetri i statorn och rotorn vilket ger en hög effektivitet. Ett varvfel i statorn skadar symmetrin och inducerar onormalt stora strömmarvilket leder till ett tidsvarierande vridmoment, mekanisk vibration, och onormala vågformer av strömmarna vid statorns och rotorns poler. Varvfel under maskinens drift kan snabbt orsaka stora skador, med följd av långa avbrottstider. Förebyggande av sådana avbrott är viktig hos maskinägare och systemansvariga. Därför är snabb detektering av sådana fel, och urdrifttagning av maskinen önskvärd för att minska skadan. Däremot ska detekteringen ha låg sannolikhet att lösa ut i onödan, av annat skäl. Externa sensorer kan användas för att upptäcka sådana fel, men det är tydligt önskvärt om detekteringen kan göras genom att analysera strömmarna som redan mäts av skyddsreläer för synkronmaskiner. I denna avhandling presenteras en metod för att simulera och observera mönster och frekvensspektrum av rotors magnetiseringsström i fall där statorn har varvfel, samt i andra fall som måste kunna skiljas från varvfel. Alla simuleringar har utförts med Matlab hos avdelningen för Elektroteknisk teori och konstruktion (ETK) i Skolan för Elektro- och systemteknik (EES) på KTH

Detection of stator interturn fault of synchronous machine by rotor current analysis : A SIMULATION APPROACH

One of the major electrical faults of synchronous machines is an interturn short circuit in the stator winding, due to winding insulation failure. A synchronous machine is designed to have electrical and mechanical symmetry in the stator and rotor. An interturn fault in a synchronous machine damages the symmetrical property, thereby inducing abnormal symptoms like varying torque, mechanical vibration, and deviation of stator and rotor terminal currents from their usual waveform. This last symptom is what is studied in this thesis, as an indicator of the presence of an interturn fault. An interturn fault during machine operation can lead to a catastrophic machine failure and consequent long outage, unless it is rapidly detected and the machine shut down. Prevention of such outages is an important concern for machine owners and power system operators. That is why early detection of interturn faults is desirable to prevent such machine failure. Several external sensors can be implemented to detect such interturn fault, which is costly. That is why it is desirable if the interturn fault can be detected by analyzing the measured currents that already are available to a protective relay. In this thesis a simulation approach is presented to observe the pattern and frequency spectrum of rotor field current in presence of a stator inter turn fault. All simulations have been performed using Matlab-based programs written during this thesis work in the Electromagnetic department (ETK) in KTH. The outcome of the thesis is that in the presence of an interturn fault in the stator, several even harmonic components are found in the frequency spectrum of the rotor field current. The presence of these harmonics is not a definitive sign of an interturn fault, as almost the same even harmonics are found in the rotor field current if the stator winding asymmetry is taken into account.En av de största elektriska felen i synkronmaskiner är en kortslutning mellan varv i statorlindningen, på grund av skadad lindningsisolering. En synkronmaskins konstruktion ger elektrisk och mekanisk symmetri i statorn och rotorn vilket ger en hög effektivitet. Ett varvfel i statorn skadar symmetrin och inducerar onormalt stora strömmarvilket leder till ett tidsvarierande vridmoment, mekanisk vibration, och onormala vågformer av strömmarna vid statorns och rotorns poler. Varvfel under maskinens drift kan snabbt orsaka stora skador, med följd av långa avbrottstider. Förebyggande av sådana avbrott är viktig hos maskinägare och systemansvariga. Därför är snabb detektering av sådana fel, och urdrifttagning av maskinen önskvärd för att minska skadan. Däremot ska detekteringen ha låg sannolikhet att lösa ut i onödan, av annat skäl. Externa sensorer kan användas för att upptäcka sådana fel, men det är tydligt önskvärt om detekteringen kan göras genom att analysera strömmarna som redan mäts av skyddsreläer för synkronmaskiner. I denna avhandling presenteras en metod för att simulera och observera mönster och frekvensspektrum av rotors magnetiseringsström i fall där statorn har varvfel, samt i andra fall som måste kunna skiljas från varvfel. Alla simuleringar har utförts med Matlab hos avdelningen för Elektroteknisk teori och konstruktion (ETK) i Skolan för Elektro- och systemteknik (EES) på KTH

Market Reactions to Dual-class Share Creation and Unification: Evidence from Canada

This study examines the short-term market reactions to the creation of dual-class shares and the unification of dual-class shares in Canada from 1980 to2022. Specifically, we analyze abnormal returns, trading volume, liquidity, and institutional ownership changes surrounding these two events. We use the event study methodology to conduct abnormal return analysis on three event days: The Announcement Day (AD), the Approval Day (ApD), and the Effective Day (ED). For our creation sample, we observe the market reaction on all three days and abnormal returns of more than 5% associated with the Announcement Day. For our unification sample, we find a significant abnormal gain of nearly 4% on the Announcement Day. We also observe that trading volume activity increases significantly around both the creation and unification of dual-class shares. Consistent with previous literature, we find that stocks that adopt the dual-class share structure experience a significant decline in liquidity. Cross-sectional regression analysis suggests that positive abnormal returns of dual-class share creation can be explained by the firm’s arrangement of financing or prospect of financing, whereas positive abnormal returns of unification are associated with changes in institutional ownership. Overall, our analyses suggest strong market reactions and changes in important aspects, such as liquidity of firms, to both events

Global mortality associated with 33 bacterial pathogens in 2019: a systematic analysis for the Global Burden of Disease Study 2019

Summary Background Reducing the burden of death due to infection is an urgent global public health priority. Previous studies have estimated the number of deaths associated with drug-resistant infections and sepsis and found that infections remain a leading cause of death globally. Understanding the global burden of common bacterial pathogens (both susceptible and resistant to antimicrobials) is essential to identify the greatest threats to public health. To our knowledge, this is the first study to present global comprehensive estimates of deaths associated with 33 bacterial pathogens across 11 major infectious syndromes. Methods We estimated deaths associated with 33 bacterial genera or species across 11 infectious syndromes in 2019 using methods from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, in addition to a subset of the input data described in the Global Burden of Antimicrobial Resistance 2019 study. This study included 343 million individual records or isolates covering 11 361 study-location-years. We used three modelling steps to estimate the number of deaths associated with each pathogen: deaths in which infection had a role, the fraction of deaths due to infection that are attributable to a given infectious syndrome, and the fraction of deaths due to an infectious syndrome that are attributable to a given pathogen. Estimates were produced for all ages and for males and females across 204 countries and territories in 2019. 95% uncertainty intervals (UIs) were calculated for final estimates of deaths and infections associated with the 33 bacterial pathogens following standard GBD methods by taking the 2·5th and 97·5th percentiles across 1000 posterior draws for each quantity of interest. Findings From an estimated 13·7 million (95% UI 10·9–17·1) infection-related deaths in 2019, there were 7·7 million deaths (5·7–10·2) associated with the 33 bacterial pathogens (both resistant and susceptible to antimicrobials) across the 11 infectious syndromes estimated in this study. We estimated deaths associated with the 33 bacterial pathogens to comprise 13·6% (10·2–18·1) of all global deaths and 56·2% (52·1–60·1) of all sepsis-related deaths in 2019. Five leading pathogens—Staphylococcus aureus, Escherichia coli, Streptococcus pneumoniae, Klebsiella pneumoniae, and Pseudomonas aeruginosa—were responsible for 54·9% (52·9–56·9) of deaths among the investigated bacteria. The deadliest infectious syndromes and pathogens varied by location and age. The age-standardised mortality rate associated with these bacterial pathogens was highest in the sub-Saharan Africa super-region, with 230 deaths (185–285) per 100 000 population, and lowest in the high-income super-region, with 52·2 deaths (37·4–71·5) per 100 000 population. S aureus was the leading bacterial cause of death in 135 countries and was also associated with the most deaths in individuals older than 15 years, globally. Among children younger than 5 years, S pneumoniae was the pathogen associated with the most deaths. In 2019, more than 6 million deaths occurred as a result of three bacterial infectious syndromes, with lower respiratory infections and bloodstream infections each causing more than 2 million deaths and peritoneal and intra-abdominal infections causing more than 1 million deaths. Interpretation The 33 bacterial pathogens that we investigated in this study are a substantial source of health loss globally, with considerable variation in their distribution across infectious syndromes and locations. Compared with GBD Level 3 underlying causes of death, deaths associated with these bacteria would rank as the second leading cause of death globally in 2019; hence, they should be considered an urgent priority for intervention within the global health community. Strategies to address the burden of bacterial infections include infection prevention, optimised use of antibiotics, improved capacity for microbiological analysis, vaccine development, and improved and more pervasive use of available vaccines. These estimates can be used to help set priorities for vaccine need, demand, and development