A CHANCE-CONSTRAINED APPROACH FOR OPTIMIZATION OF GAS PROCESSING PLANT OPERATION UNDER UNCERTAIN CONDITIONS

Natural gas plant operations contribute hugely to the economies of many developed nations that depend on hydrocarbon resources. The plant operation is usually subjected to continuous variations in upstream conditions, such as flow rate, composition, temperature and pressure, which propagate through the plant and affect its stable operations. As a result, decision making for optimal operating conditions of an in-operation plant is a complex problem and it is exacerbated with the changing product specifications and variations in energy supplies. This work presents a new solution method to the problem, which is based on chance constrained optimization method. A deterministic model is initially developed from process simulation using Aspen HYSYS and later converted to a chance constrained model. The probabilistic model is then relaxed to its equivalent deterministic form and solved for optimum solution using GAMS. The optimum solution is determined probabilistically using chance constraints that are held at a user-defined confidence level. Optimal solution is represented graphically as a trade-off between reliability of holding the process constraints and profitability of the plant. Three case studies are presented to demonstrate the new method. Optimization results show that uncertainty of plant parameters significantly affect the economic performance of the plant operation. The solution approach developed in this work is able to increase the reliability of maintaining the profit by more than 95% confidence level. As a result, the risk of constraints violation is reduced from more than 50% using the typical deterministic optimization to less than 5% with the chance constrained optimization approach. In addition, the results from this study indicate that the variation of material flow from the plant inlet has greater impact by more than 85.5% on profit compared to variation from the plant outlet, which is less than 2%. The variations of energy flow affect on profit is mainly changes with confidence level measurement higher than 95%, although material flow uncertainty is more sensitive to profit changes than uncertainty in energy flow. Final computational results also highlight the advantage of the developed chance constrained approach, which combines both the profit and the vi reliability of the process constraints, over “worst case” and two-stage programming approaches. Decisions from the “worst case” approach may reach to more than 99% confidence level which can drastically decrease the profit while the optimal decision from the two-stage programming does not clearly show to how much extent that the profit has been held. The developed solution approach in this work can aid as guidelines to flexible plant operation decision making for the in-operating plant by satisfying all the process constraints at certain confidence level

Commodity Price Volatility: The Impact of Commodity Index Traders

Over the years, critics have argued that futures market prices have been either too low or too high. Speculators have often been the target for the wrath of those feeling the futures price does not properly reflect market fundamentals. Recently, the criticism has been vented toward a new type of speculator that has been blamed for the dramatic changes in agricultural commodity prices experienced over the last several years. Commodity index traders (CITs) and other large institutional traders are commonly accused of exerting a destabilizing influence on commodity prices. The intensity of the debate over the role of CITs appeared to wane with the reduction in commodity prices since 2008 but the recent release of a well-publicized OECD report on the issue by Irwin and Sanders (2010) along with the doubling of wheat prices and the claim by von Braun (2010) and others that the rise was due to speculative activity has renewed the debate.commodity, index futures, trading, volatility, Agribusiness, Agricultural and Food Policy, Demand and Price Analysis, Marketing,

Commodity Price Volatility: The Impact of Commodity Index Traders

index, traders, commodity, price, volatility, Agricultural and Food Policy, Demand and Price Analysis, Marketing,

The changing egg demand in Canada: do advertising and health message contents matter?

Agricultural and Food Policy, Consumer/Household Economics, Demand and Price Analysis, Food Consumption/Nutrition/Food Safety, Food Security and Poverty, Health Economics and Policy,

Physical Exercise Prescription for Individuals with Kidney Disease

Chronic kidney disease (CKD) is a common condition that has significant implications for patients’ health. CKD is diagnosed if evidence of kidney damage has been present for more than 3 months; it is divided into five stages depending on the glomerular filtration rate (GFR). CKD is asymptomatic and determining its prevalence relies on screening populations, so the reported prevalence depends on the population studied and screening methods used. Risk factors for CKD can be divided into initiating and perpetuating factors, and includes genetic factors, ethnicity, socio-economic factors and age. There are several causes of CKD, the most common being diabetes mellitus. In order to reduce the burden of CKD, it is essential to recognize which patients are at most risks so that they can be screened and treated early. It is hoped that with early recognition and treatment the number of patients with CKD progressing to end-stage kidney disease (ESKD) and the need for renal replacement therapy will be reduced. Exercise testing of individuals with CKD should be supervised by trained medical personnel, with the use of standard test termination criteria and test termination methods. Based on current evidence, exercise is safe for these individuals if performed at moderate intensity and if progression occurs gradually. Keywords: - Chronic kidney disease, dialysis, kidney transplantation, exercise testing, exercise prescription. DOI: 10.7176/JTHS/50-01 Publication date:September 30th 2020

Rate Determination of Nitrogen and Phosphorus Fertilizers for Green Maize Under Irrigation

A study was conducted on a research station at Kobo sub-center of Sirinka Agricultural research Center for two years to determine the optimum rates of N and P fertilizers for green maize production under irrigation in Kobo-Girana irrigation valley. Four levels of N (0, 46, 92 and 138 kg N ha-1) with three levels of P fertilizer (0, 23 and 46 kg P2O5 ha-1) were factorially combined and laid in RCBD design with three replications. A uniform irrigation water depth and interval was applied to all plots based on maize’s irrigation water requirement determined for the area. The crop was irrigated a total amount of 500 mm irrigation water at 7 days interval starting from the development stage. Phosphorus fertilizer was applied all at planting. While, N fertilizer was applied in split, 1/3 at planting, 1/3 at knee height and 1/3 at tasseling stage. The result shows that there was no significant (p>0.05) interaction of N and P fertilizers on the cob yield, cob number, cob length and cob diameter of green maize. However, the main effect of N fertilizer had significant (p<0.05) effect on the cob yield, cob number, cob length and cob diameter of green maize. The main effect of application of P fertilizer had insignificant (p>0.05) effect on the cob yield of green maize, which is attributable to the medium to high levels of Olsen’s extractable available P in bottom valleys of alluvial soils of Kobo where the study site laid. The highest cob number (51556) and cob weight (12.0 t ha-1) was recorded from application of 138 kg N ha-1 followed with statistically insignificant (p>0.05) difference by the cob number (49020) and cob weight (11.1 t ha-1) obtained from application of 92 kg N ha-1. The partial budget and the sensitivity analysis result considering 15% possible price fluctuation show that the highest marginal rate return of 421.7% was obtained from application of 92 kg N ha-1. While, the lowest marginal rate return of 378.8% was recorded from application 138 kg N ha-1. Therefore, application of 92 kg N ha-1 is recommended for maximum and economic return of green maize production under irrigation in Kobo valley. Keywords: Green maize, kobo, irrigation, nitrogen, phosphorus. DOI: 10.7176/JNSR/10-3-03 Publication date: February 29th 202

Seasonal Solar Thermal Energy Storage

Solar intermittency is a major problem, and there is a need and great interest in developing a means of storing solar energy for later use when solar radiation is not available. Thermal energy storage (TES) is a technology that is used to balance the mismatch in demand and supply for heating and/or cooling. Solar thermal energy storage is used in many applications: buildings, concentrating solar power plants and industrial processes. Solar thermal water heaters capable of heating water during the day and storing the heated water for evening use are common. TES improves system performance by smoothing supply and demand and temperature fluctuations. Thermal energy storage has become a fast-growing business. According to a research report, the global thermal energy storage market is expected to reach USD 12.50 billion by 2025. The chapter describes different types of thermal energy storage systems. Brief history, current state of research and the future of thermal storage are presented. Types of thermal storages, classifications, advantages and disadvantages are discussed; important thermal and physical properties are tabulated. Advances in enhancement of thermal properties of materials are briefly discussed. Challenges, opportunities, market outlook, government incentives and polices that support deployment of energy storage systems are outlined