Forging Ahead : Technology Development & Emerging Economies

Against the pressing challenge of climate change, solar photovoltaic technology is widely considered as a clean and renewable alternative to fossil fuels. Landscaping the development of solar technology worldwide, the case of China is prominent, as it experienced a successful catching-up and a dramatic growth in production, deployment, and development of solar modules over the past few years. This dissertation takes you on a magic carpet ride through the technological innovation system of photovoltaics in China. Through the pages of this book, you will be introduced to the technical components of the solar technology. You will track the development stages of the innovation system in China, meet the main actors, get to know their capabilities, specialization profiles, and interactions. Additionally, you will see how their knowledge networks evolve over time. The dissertation further tells the story of political economy, solar wars, and the role of governmental policies in shaping the present status of the global system and protecting the environment

The development of a green energy sector model for the Southern African Development Community (SADC)

The Southern African Development Community (SADC) region, like most parts of the African continent, faces significant modern energy services access challenges. It is estimated that less than 45% of the SADC region’s populace have access to reliable modern energy forms and the situation is worse in rural areas where access is approximately 30%. Poor energy security is exacerbated by electricity power cuts and load shedding in almost all of the member states in the region. With the advent of battery storage, all forms of green energy have the potential to contribute to the shortfall in the supply of peaking power required to meet the daily (morning and evenings) and seasonal (winter) peaks when most power is required on the grid network. The region is endowed with vast green (renewables/low carbon or clean) energy resources. The purpose of this study is to expand the empirical body of research and knowledge on factors that contribute to widespread access success to green energy in the SADC region. Investments into green energy resources require an understanding of the unique characteristics of the energy sector in the region. In order to achieve this, a conceptual theoretical model was developed and tested empirically. Factors that influence green energy access success were identified through literature reviews and discussions with energy practitioners. All identified factors were then operationalised by carefully defining them in the context of the study. In order to test the proposed theoretical model and the hypothesised relationships, a structured questionnaire was developed and sent to energy practitioners from various sections of the energy sector in the region. STATISTICA 12 was employed to analyse relationships between variables and responses between identified groups. Pearson Product Moment Correlation (Pearson r) was employed to determine correlations between variables. Conclusions about hypotheses six (6) to fifteen (15) were made based on correlations between variables. T-tests were employed to make inferences about the views of various categories of respondents with regard to the twelve (12) identified variables. Multivariate analysis of variance (MANOVA) and Analysis of variance (ANOVA) examined associations between the dependent and independent variables with the identified categories of respondents and conclusions about hypotheses one (1) to five (5) and sixteen (16) were also made. The study finds that policy and the regulatory environment are still the main driving force behind energy access in the region. Power generation is managed by authorities’ power utility companies. Unbundling of power utilities supported by new energy business and operating models to accommodate mini and off grid power plants is found to be a key to green energy access in the region. The energy market is transforming in favour of independent power producers (IPPs) and consumers will significantly influence energy access decisions in the future. Green energy power storage to overcome intermittency will feature prominently in the success of green energy access in the region. Widespread access success to green energy will be attained when green energy access is reliable, affordable, efficient, and socially acceptable, meet the demand and reduces environmental pollution. The study recommends that strategic green energy planning must incorporate green energy infrastructure development, projects finance and human capacity development as priorities amongst SADC region’s member countries. Regional energy access enabling institutions must be strengthened; energy policies implemented with vigour and private sector participation enhanced in an integrated energy market

Understanding, Modeling and Predicting Hidden Solder Joint Shape Using Active Thermography

Characterizing hidden solder joint shapes is essential for electronics reliability. Active thermography is a methodology to identify hidden defects inside an object by means of surface abnormal thermal response after applying a heat flux. This research focused on understanding, modeling, and predicting hidden solder joint shapes. An experimental model based on active thermography was used to understand how the solder joint shapes affect the surface thermal response (grand average cooling rate or GACR) of electronic multi cover PCB assemblies. Next, a numerical model simulated the active thermography technique, investigated technique limitations and extended technique applicability to characterize hidden solder joint shapes. Finally, a prediction model determined the optimum active thermography conditions to achieve an adequate hidden solder joint shape characterization. The experimental model determined that solder joint shape plays a higher role for visible than for hidden solder joints in the GACR; however, a MANOVA analysis proved that hidden solder joint shapes are significantly different when describe by the GACR. An artificial neural networks classifier proved that the distances between experimental solder joint shapes GACR must be larger than 0.12 to achieve 85% of accuracy classifying. The numerical model achieved minimum agreements of 95.27% and 86.64%, with the experimental temperatures and GACRs at the center of the PCB assembly top cover, respectively. The parametric analysis proved that solder joint shape discriminability is directly proportional to heat flux, but inversely proportional to covers number and heating time. In addition, the parametric analysis determined that active thermography is limited to five covers to discriminate among hidden solder joint shapes. A prediction model was developed based on the parametric numerical data to determine the appropriate amount of energy to discriminate among solder joint shapes for up to five covers. The degree of agreement between the prediction model and the experimental model was determined to be within a 90.6% for one and two covers. The prediction model is limited to only three solder joints, but these research principles can be applied to generate more realistic prediction models for large scale electronic assemblies like ball grid array assemblies having as much as 600 solder joints

Improving Electricity Distribution System State Estimation with AMR-Based Load Profiles

The ongoing battle against global warming is rapidly increasing the amount of renewable power generation, and smart solutions are needed to integrate these new generation units into the existing distribution systems. Smart grids answer this call by introducing intelligent ways of controlling the network and active resources connected to it. However, before the network can be controlled, the automation system must know what the node voltages and line currents defining the network state are.Distribution system state estimation (DSSE) is needed to find the most likely state of the network when the number and accuracy of measurements are limited. Typically, two types of measurements are used in DSSE: real-time measurements and pseudomeasurements. In recent years, finding cost-efficient ways to improve the DSSE accuracy has been a popular subject in the literature. While others have focused on optimizing the type, amount and location of real-time measurements, the main hypothesis of this thesis is that it is possible to enhance the DSSE accuracy by using interval measurements collected with automatic meter reading (AMR) to improve the load profiles used as pseudo-measurements.The work done in this thesis can be divided into three stages. In the first stage, methods for creating new AMR-based load profiles are studied. AMR measurements from thousands of customers are used to test and compare the different options for improving the load profiling accuracy. Different clustering algorithms are tested and a novel twostage clustering method for load profiling is developed. In the second stage, a DSSE algorithm suited for smart grid environment is developed. Simulations and real-life demonstrations are conducted to verify the accuracy and applicability of the developed state estimator. In the third and final stage, the AMR-based load profiling and DSSE are combined. Matlab simulations with real AMR data and a real distribution network model are made and the developed load profiles are compared with other commonly used pseudo-measurements.The results indicate that clustering is an efficient way to improve the load profiling accuracy. With the help of clustering, both the customer classification and customer class load profiles can be updated simultaneously. Several of the tested clustering algorithms were suited for clustering electricity customers, but the best results were achieved with a modified k-means algorithm. Results from the third stage simulations supported the main hypothesis that the new AMR-based load profiles improve the DSSE accuracy.The results presented in this thesis should motivate distribution system operators and other actors in the field of electricity distribution to utilize AMR data and clustering algorithms in load profiling. It improves not only the DSSE accuracy but also many other functions that rely on load flow calculation and need accurate load estimates or forecasts

WP3 – Innovation in Agriculture and Forestry Sector for Energetic Sustainability

The papers published in this Special Issue “WP3—Innovation in Agriculture and Forestry Sector for Energetic Sustainability” bring together some of the latest research results in the field of biomass valorization and the process of energy production and climate change and other areas relevant to energetic sustainability [1–20]. Moreover, several works address the very important topic of evaluating the safety aspects for energy plant use [21–24]. Responses to our call generated the following statistics:• Submissions (21);• Publications (15);• Rejections (6);• Article types: research articles (13), reviews (2). Of the submitted papers, 15 have been successfully published as articles. Reviewing and selecting the papers for this Special Issue was very inspiring and rewarding. We also thank the editorial staff and reviewers for their efforts and help during the process. For better comprehension, the contributions to this Special Issue are divided into sections, as follows

Program and Book of Abstracts: 2019 Undergraduate Research Celebration

The Ramaley Celebration is a highly anticipated event that features student presentations of their research accomplishments. At Winona State, undergraduate research is highly valued as an integral part of the educational process and the Ramaley Celebration is one way we recognize and affirm this. Furthermore, the wonderful diversity of the student presenters, the research projects, and the disciplines represented all provide a strong reminder of the distinctiveness and breadth of research across the entire WSU community. For our purposes, we define “research” very broadly as “an inquiry or investigation that makes an original intellectual or creative contribution to the discipline” (Council on Undergraduate Research).https://openriver.winona.edu/urc2019/1000/thumbnail.jp

Toward a spectroscopy-based approach for estimating time elapsed since bloodstains deposition : development of a novel framework for blood evidence evaluation

Grupą materiałów dowodowych, która na dobre zagościła na salach sądowych, są ślady krwawe stanowiące często główną siłę napędową procesu dochodzeniowego. Wdrożenie do praktyki sądowej genetycznych badań identyfikacyjnych bezsprzecznie stanowiło kamień milowy w rozwoju kryminalistyki, rozpoczynając swoistą „dominację” badań DNA. Okazuje się jednak, że wyniki analiz genetycznych nie zawsze pozwalają udzielić wyczerpującej odpowiedzi na stawiane pytania, a czasowy aspekt utworzenia śladów krwawych niejednokrotnie bywa równie istotny, co przebieg zdarzeń prowadzących do ich powstania. Informacja o czasie uformowania plam krwawych może bowiem wspomóc proces dochodzeniowy w wieloraki sposób. W przypadku ujawnienia śladów krwawych pochodzących od podejrzanego, tak naprawdę dopiero informacja o czasie powstania śladu stanowi dla zleceniodawcy silną przesłankę przemawiającą za udziałem podejrzanego w zdarzeniu. Rezultaty datowania śladów pozwalają więc potwierdzić jego obecność na miejscu zdarzenia w konkretnym czasie, stanowiąc cenniejszy dowód w sprawie aniżeli same wyniki badań genetycznych. Podjęcie próby odpowiedzi na pytanie o czas powstania śladów krwawych jest możliwe dzięki procesom starzeniowym, które prowadzą do zmian właściwości fizykochemicznych badanego materiału. Niestety, wieloletnie próby stworzenia metodyki bezwzględnego datowania krwi nie dały jak dotąd pozytywnego rezultatu, przez co informacja o czasowym aspekcie powstania śladów krwawych wciąż pozostaje poza zasięgiem biegłych. Analiza dotychczasowych badań prowadzi jednak do pewnych wniosków – przyczyna owych niepowodzeń najprawdopodobniej ma swoje źródło w nieodpowiednim podejściu do problemu datowania. Okazuje się bowiem, że zgodnie z powszechnie przyjętą strategią, większość zaproponowanych rozwiązań sprowadzała się do zdefiniowania pewnego mierzalnego parametru, odzwierciedlającego stopień degradacji krwi, a następnie powiązania jego zmian z upływającym czasem (najczęściej za pomocą technik kalibracyjnych). Problem jednak w tym, że proces starzeniowy to nie tylko kwestia czasu. Materiał dowodowy może degradować w różnym tempie w zależności od wielu czynników zewnętrznych – przede wszystkim warunków środowiskowych panujących na miejscu zdarzenia. Tym samym, owe konwencjonalne modele datowania, opracowywane dla próbek degradujących w warunkach laboratoryjnych, okazywały się zawodne podczas prób przeniesienia ich na grunt praktycznych analiz. Rozwiązanie, zaproponowane w ramach nieniejszej rozprawy, stanowi ujęcie zagadnienia datowania jako problemu porównawczego, rozpatrywanego w ramach podejścia korzystającego z ilorazu wiarygodności (LR, ang. likelihood ratio), który uwzględniać będzie wpływ czynników zewnętrznych na proces degradacji krwi. Podstawą owej nowej metodyki szacowania “wieku” śladów krwawych jest ocena podobieństwa pomiędzy stopniem degradacji materiału dowodowego a rozkładem materiałów porównawczych, uzyskanych podczas procesu kontrolowanego starzenia krwi, oddającego – tak dokładnie, jak to tylko możliwe – degradację materiału dowodowego na miejscu zdarzenia. Każda procedura datowania jest więc niejako “szyta na miarę”, dostosowana każdorazowo do zabezpieczonego materiału dowodowego, prowadząc do zminimalizowania wpływu czynników zewnętrznych (jak chociażby warunków środowiskowych) na poprawność procesu datowania. Opracowanie nowej metodyki datowania wymagało rozwiązania dwóch odrębnych zagadnień. W pierwszej części badań, podjęto próbę utworzenia metody analitycznej pozwalającej na charakterystykę stopnia degradacji plam krwawych. Biorąc pod uwagę właściwości fizykochemiczne badanego śladu, wybór spektroskopii ramanowskiej wydawał się dobrze uzasadnioną decyzją, co też zostało potwierdzone przez uzyskane wyniki. Spektroskopia Ramana pozwoliła bowiem na monitorowanie zmian fizykochemicznych, towarzyszących procesom degradacji głównego składnika śladów krwawych – hemoglobiny – w nieinwazyjny i reprezentatywny sposób. Druga część badań polegała na opracowaniu hybrydowych modeli LR służących rozwiązywaniu tzw. problemu porównawczego widm ramanowskich, które charakteryzowały ślady krwawe o nieznanym czasie powstania (potencjalne materiały dowodowe) oraz ślady utworzone w procesie kontrolowanego starzenia (tzw. materiały referencyjne). Wyniki procedury walidacyjnej pozwoliły na wstępne potwierdzenie skuteczności nowo zaproponowanej metodyki datowania śladów krwawych. Najlepsze spośród opracowanych modeli LR dostarczały akceptowalne poziomy odpowiedzi fałszywie pozytywnych i fałszywie negatywnych, które oscylowały odpowiednio wokół 20% oraz 10%. Warunkiem skuteczności procedury było jednak utworzenie materiałów referencyjnych w warunkach środowiskowych jak najbardziej zbliżonych do tych, które panowały podczas degradacji dowodowych śladów krwawych. Wniosek ten nie powinien jednak dziwić – zapewnienie porównywalnej kinetyki procesów starzeniowych materiałów referencyjnych i dowodowych jest w istocie podstawowym wymogiem metodologii opracowanej w ramach nieniejszej rozprawy doktorskiej