A multi-objective framework for long-term generation expansion planning with variable renewables

The growing importance of operational flexibility in generation expansion planning with increased integration of variable renewables has been regularly highlighted in recent research. Yet, operational flexibility has been largely overlooked in order to reduce the prohibitive problem size that results when operational details at small timescales are included in this long-term exercise. In this work, we present a multi-objective optimization framework that effectively and tractably incorporates flexibility screening of candidate generation portfolios in long-term generation expansion planning. Operational flexibility is considered as a separate objective along with the traditional economic and environmental objectives. The ability of the proposed methodology to provide valuable insights into the correlations between flexibility, total costs and carbon emissions is demonstrated using a case study. The results clearly reveal that omission of flexibility from the framework gives rise to deficient generation mixes that are unable to match the more frequent and steeper variations in net load. A high-level evaluation of the flexibility needed in generation portfolios to balance net loads with different degrees of variability is also provided. Finally, a procedure is proposed to support the decision-making process for selecting the most appropriate investment plan among the many solution options provided by the multi-objective optimization framework

Chitin hydrolysis with chitinolytic enzymes for the production of chitooligomers with antimicrobial properties

There are many diseases and illnesses in the world that require new drug treatments and chitin has been shown to produce chitooligomeric derivatives which exhibit promising antimicrobial and immune-enhancing properties. However, the rate-limiting step is associated with the high recalcitrance of chitinous substrates, and low hydrolytic activities of chitinolytic enzymes, resulting in low product release. To improve and create a more sustainable and economical process, enhancing chitin hydrolysis through various treatment procedures is essential for obtaining high enzyme hydrolysis rates, resulting in a higher yield of chitooligomers (CHOS). In literature, pre-treatment of insoluble biomass is generally associated with an increase in accessibility of the carbohydrate to hydrolytic enzymes, thus generating more products. The first part of this study investigated the effect of alkali- (NaOH) and acid pre-treatments (HCl and phosphoric acid) on chitin biomass, and chemical and morphological modifications were assessed by the employment of scanning electron microscopy (SEM), Fourier Transform Infrared Spectroscopy (FTIR), Energy-Dispersive X-ray spectrometery (EDX) and x-ray diffraction (XRD). Data obtained confirmed that pre-treated substrates were more chemically and morphologically modified. These results confirmed the fact that pre-treatment of chitin disrupts the structure of the biomass, rendering the polymer more accessible for enzymatic hydrolysis. The commercial chitinases from Bacillus cereus and Streptomyces griseus (CHB and CHS) are costly. Bio-prospecting for other chitin-degrading enzymes from alternate sources such as Oidiodendron maius, or the recombinant expression of CHOS, was a more economically feasible avenue. The chit1 gene from Thermomyces lanuginosus, expressed in Pichia pastoris, produced a large range CHOS with a degree of polymerisation (DP) ranging from 1 to above 6. TLC analysis showed that O. maius exhibited chitin-degrading properties by producing CHOS with a DP length of 1 to 3. These two sources were therefore successful in producing chitin-degrading enzymes. The physico-chemical properties of commercial (CHB and CHS) and expressed (Chit1) chitinolytic enzymes were investigated, to determine under which biochemical conditions and on which type of biomass they can function on optimally, for the production of value-added products such as CHOS. Substrate affinity assays were conducted on the un-treated and pre-treated biomass. TLC revealed that chitosan hydrolysis by the commercial chitinases produced the largest range of CHOS with a DP length ranging from 1 to 6. A range of temperatures (35-90oC) were investigated and CHB, CHS and Chit1 displayed optimum activities at 50, 40 and 45 oC, respectively. Thermostability studies that were conducted at 37 and 50oC revealed that CHB and CHS were most stable at 37oC. Chit1 showed great thermostablity at both temperatures, rendering this enzyme suitable for industrial processes at high temperatures. pH optima studies demonstrated that the pH optima for CHB, CHS and Chit1 was at a pH of 5.0, with specific activities of 33.459, 46.2 and 5.776 μmol/h/mg, respectively. The chain cleaving patterns of the commercial enzymes were determined and exo-chitinase activity was exhibited, due to the production of CHOS that were predominantly of a DP length of 2. Enzyme binary synergy studies were conducted with commercial chitinases (CHB and CHS) on colloidal chitin. Studies illustrated that the simultaneous combination of CHB 75%: CHS 25% produced the highest specific activity (3.526 μmol/h/mg), with no synergy. TLC analysis of this enzyme combination over time revealed that predominantly chitobiose was produced. This suggested that the substrate crystallinity and morphology played an important role in the way the enzymes cleaved the carbohydrate. Since CHOS have shown great promise for their antimicrobial properties, the CHOS generated from the chitinous substrates were tested for antimicrobial properties on Bacillus subtilis, Escherichia coli, Klebsiella and Staphlococcus aureus. This study revealed that certain CHOS produced have inhibitory effects on certain bacteria and could potentially be used in the pharamceutical or medical industries. In conclusion, this study revealed that chitinases can be produced and found in alternate sources and be used for the hydrolysis of chitinous biomass in a more sustainabe and economically viable manner. The chitinases investigated (CHB, CHS and Chit1) exhibited different cleaving patterns of the chitinous substrates due to the chemical and morphological properties of the biomass. CHOS produced from chitinous biomass exhibited some inhibitory effects on bacterial growth and show potential for use in the medical industry

Johansen model for photovoltaic a very short term prediction to electrical power grids in the Island of Mauritius

Sudden variability in solar photovoltaic (PV) power output to electrical grid can not only cause grid instability but can also affect power and frequency quality. Therefore, to study the balance of electrical grid or micro-grid power generated by PV systems in an upstream direction, predicting models can help. The power output conversion is directly proportional to the solar irradiance. Unlike time horizons predictions, many technics of irradiance forecasting have been proposed, long, medium and short term forecasting. For the Island of Mauritius in the Indian Ocean, and regards to key policy decisions, the government has outlined its intention to promote the PV technologies through the local electricity supplier but oversee the technical requirements of PV power output predicts for 1 hour to 15-minutes ahead. So, this paper is illustrating results of the Johansen vector error correction model (VECM) cointegration approach, from the author original and previous studies, but for a very short term prediction of 15-minutes to PV power output in Mauritius. The novelty of this study, is the long run equilibrium relationship of the Johansen model, that was initially determined in previous research works and from dataset in Reunion Island, is then applied to the PV plant in the Island of Mauritius. The proposed prediction model is trained for an hourly and 15-minutes period from year 2019 to year 2022 for a random month and a random day. The experimental results show that the performance metric R2 values are more than 93% signifying that Johansen model is positively and strongly correlated to onsite measurements. This proposed model is a powerful predicting tool and more accuracy should be attained when associated to a machine learning method that can learn from datasets

Generation expansion planning optimisation with renewable energy integration: A review

Generation expansion planning consists of finding the optimal long-term plan for the construction of new generation capacity subject to various economic and technical constraints. It usually involves solving a large-scale, non-linear discrete and dynamic optimisation problem in a highly constrained and uncertain environment. Traditional approaches to capacity planning have focused on achieving a least-cost plan. During the last two decades however, new paradigms for expansion planning have emerged that are driven by environmental and political factors. This has resulted in the formulation of multi-criteria approaches that enable power system planners to simultaneously consider multiple and conflicting objectives in the decision-making process. More recently, the increasing integration of intermittent renewable energy sources in the grid to sustain power system decarbonisation and energy security has introduced new challenges. Such a transition spawns new dynamics pertaining to the variability and uncertainty of these generation resources in determining the best mix. In addition to ensuring adequacy of generation capacity, it is essential to consider the operational characteristics of the generation sources in the planning process. In this paper, we first review the evolution of generation expansion planning techniques in the face of more stringent environmental policies and growing uncertainty. More importantly, we highlight the emerging challenges presented by the intermittent nature of some renewable energy sources. In particular, we discuss the power supply adequacy and operational flexibility issues introduced by variable renewable sources as well as the attempts made to address them. Finally, we identify important future research directions

Analysis of the United States Computer Emergency Readiness Team's (U.S. CERT) Einstein III intrusion detection system, and its impact on privacy

To secure information technology and telecommunications systems, the U.S Department of Homeland Security created the United States Computer Emergency Readiness Team (U.S. CERT) to provide 24-hour early warning and detection for the federal governments Internet infrastructure. A leading program in this effort, EINSTEIN, was developed by U.S. CERT in partnership with the National Security Agency (NSA) and private industry. EINSTEIN is an intrusion detection program that monitors network traffic and searches for signatures of known malicious code. Now in its third generation, EINSTEIN now generates alerts that have the possibility of including Personal Identifying Information, monitors live traffic on networks in real-time, and also has the ability to counter the intrusion as it takes place. By reviewing current privacy policy and past privacy case studies, in addition to careful analysis of federal court cases and statutes, this thesis establishes the fundamental and constitutional right to privacy. Through secondary research, this thesis identifies elements and exemptions of current communications legislation that can be used in the development of a comprehensive cyberspace monitoring policy. The result is a recommendation that a new Einstein III Privacy Impact Assessment, as well a new legal opinion document, be drafted to balance the trade-off between privacy rights and the objectives of securing cyberspace, and that establishes a proper legal foundation for the implementation of the controversial technology.http://archive.org/details/analysisofunited1094532877Outstanding ThesisLieutenant, United States NavyApproved for public release; distribution is unlimited

Microwave heating in high pressure reaction vessels

We report the use of microwave -hydrothermal processing to synthesize various ceramic powders. Microwave-hydrothermal processing is compared with conventional hydrothermal processing in the crystallisation of MoO2. The presence of microwave field leads to accelerated kinetics of crystallization of the finely divided molybdenum dioxide particles. Existing microwave heated pressure vessels for chemical synthesis cannot be used above 250 MPa and 270°C because they contain parts made of polymeric materials. The objective of this work is to associate a microwave source to a high pressure vessel in a way such that it might be used to carry out reactions in aqueous media at pressures around 100 MPa and temperatures above the critical point of water

Impact of decomposition and kriging models on the solar irradiance downscaling accuracy in regions with complex topography

International audienceMany small island states are planning to invest heavily in solar photovoltaics in an attempt to curb their overreliance on fossil fuels for electricity generation. In order to efficiently exploit the abundant solar energy resource, these islands need reliable solar irradiance data. However, the orographic effects arising from their volcanic origins often result in strong variability and uncertainty in the solar resource. In this context, satellite-based models present an effective alternative to ground-based measurements. Different downscaling approaches have been applied that compensate for the large spatial resolution of satellite images and the terrain-related effects that they disregard. Nevertheless, the accuracy of these methods is influenced by the solar radiation decomposition model used. Moreover, the variogram model used in the kriging process to characterize the spatial dependence of the solar radiation has a significant effect on the results. In this study, we compare the performances of seven radiation decomposition models for the anisotropy analysis and seven variogram models for the spatial interpolation of the solar irradiance. A dense network of ground measurements at 43 stations is used to evaluate the accuracy of the different models. Results reveal that the Yao radiation model coupled with the Matern variogram provide the best results

Low-cost bus seating information technology system

Public transport operators often struggle to provide a reliable and efficient transport service. A lack of comprehensive real-time operational data is often cited as a major cause for this state of things. In this study, the authors report on the design, implementation and testing of an Internet of Things-based system, named Bus Seating Information Technology system, which dynamically determines vehicle occupancy while the bus is in service. It uses an array of sensors for detecting events in the vehicle: infrared sensors ascertain whether passengers are entering or leaving the bus; force-sensitive resistors facilitate seat-occupancy detection; a Global Positioning System shield in conjunction with a Raspberry Pi microcomputer enables real-time tracking of the bus; and a USB camera connected to the same Raspberry Pi assist in cross-checking and validating the preceding information. The data collected is uploaded to an online IoT platform (thinger.io), through 3G or 4G if available, and can be visualised via an android app as well as through a desktop computer user interface. The planned functions of the system were tested in a 20-seater bus. Results showed that the system can track the vehicle location, as well as vehicle occupancy in real-time in most cases