Search

Nano polymeric micelles (nano PMs) help to increase accessibility to tumor sites, decrease side effects and allow controlled drug dissemination over a long period of time. The aim of this study was to optimize the delivery of the anticancer drug capecitabine (CAP) using nano PMs and cyclodextrin (CD) to allow the treatment of colon cancer. A pH-responsive copolymer was prepared and the variables of loading time, loading temperature, the amount of copolymer and also the ratio of acrylic/maleic copolymer to beta CD and the effect that these variables have on drug loading were investigated, with variable optimization studies carried out following a definitive screening design (DSD). The morphology and structure of the particles were determined by scanning electron microscopy (SEM) and Fourier-transform infrared (FTIR) spectroscopy.

Thermal energy storage (TES) is widely expected to play an important role in facilitating the decarbonization of the future energy system. Although significant work has been done in assessing the values of traditional sensible TES, less is known about the role, impact and value of emerging advanced TES at the system level. This is particularly the case of latent heat thermal energy storage (LHTES) and thermochemical energy storage (TCS). In this context, this paper is dedicated to evaluating the techno-economic values for the whole UK energy system of LHTES and TCS technology using an integrated whole energy system model. First, the key concepts of the whole system modelling framework are introduced. Unique to this work is that the economic benefits delivered by LHTES and TCS to different levels of the UK energy system infrastructure and various energy sectors through the deployment of TES are explicitly analysed, which comprehensively demonstrates the values of selected TES technologies from the whole system perspective. A series of sensitivity studies are implemented to analyse the advantages and disadvantages of LHTES and TCS under different conditions. The simulation results indicate that TES can benefit different sectors of the whole energy system and drive significant cost savings, but the whole system values of TES is closely dependent on the decarbonization requirement. Although LHTES is characterized by relatively low capital costs, when TES penetration is limited and carbon target is tight, the advantage of TCS is outstanding due to its high energy density.

The emissions generated by the space and water heating of UK homes need to be reduced to meet the goal of becoming carbon neutral by 2050. The combination of solar (S) collectors with latent heat thermal energy storage (LHTES) technologies with phase change materials (PCM) can potentially help to achieve this goal. However, there is limited understanding of the environmental sustainability of LHTES technologies from a full life cycle perspective. This study assesses for the first time 18 environmental impacts of a full S-LHTES-PCM system from a cradle to grave perspective and compares the results with the most common sources of heat in UK homes. The results show that the system’s main environmental hotspots are the solar collector, the PCM, the PCM tank, and the heat exchanger. The main cause of most of the impacts is the extensive consumption of electricity and heat during the production of raw materials for these components. The comparison with other sources of household heat (biomass, heat pump, and natural gas) indicates that the S-LHTES-PCM system generates the highest environmental impact in 11 of 18 categories. However, a sensitivity analysis based on the lifetime of the S-LHTES-PCM systems shows that, when the lifetime increases to 40 years, almost all the impacts are significantly reduced. In fact, a 40-year S-LHTES-PCM system has a lower global warming potential than natural gas.

This chapter presents algorithms to enhance the reliability and resiliency in the coordinated operation of gas and electricity networks. For this purpose, first, a comprehensive framework, including a mathematical model for operation of these networks, is introduced in the presence of flexibility options, such as gas and electricity storage systems. Second, the reliability analysis algorithm is introduced, which consists of generating a set of scenarios for availability and unavailability of the components and taking into account the generated scenarios through the stochastic modeling of these networks. Afterward, the resiliency analysis algorithm is introduced, which consists of presenting an approach to find the worst-case scenarios and taking into account these scenarios in a same manner in which stochastic modeling is presented. It should be noticed that, in both reliability analysis and resiliency analysis, the cost of operation and amount of load shedding are calculated and compared for the stochastic model and the original model considering the occurrence of each scenario. In light of this, the role of energy storage systems is also examined in reliability and resiliency of integrated gas and electricity networks.

Renewable energy sources will anticipate significantly in the future energy system paradigm due to their low cost of operation and low pollution. Considering the renewable generation (e.g., wind) intermittency, flexible gas-fired power plants will continue to play their essential role as the main linkage of natural gas and electricity networks, and hence coordinated operation of these networks is beneficial. Furthermore, uncertainty is always found in gas demand prediction, electricity demand prediction, and output power of wind generation. Therefore, in this paper, a two-stage stochastic model for operation of natural gas and electricity networks is implemented. In order to model uncertainty in these networks, Monte Carlo simulation is applied to generate scenarios representing the uncertain parameters. Afterwards, a scenario reduction algorithm based on distances between the scenarios is applied. Stochastic and deterministic models for natural gas and electricity networks are optimized and compared considering integrated and iterative operation strategies. Furthermore, the value of flexibility options (i.e., electricity storage systems) in dealing with uncertainty is quantified. A case study is presented based on a high pressure 15-node gas system and the IEEE 24-bus reliability test system to validate the applicability of the proposed approach. The results demonstrate that applying the stochastic model of gas and electricity networks as well as considering integrated operation strategy in the presence of flexibility provides different benefits (e.g., 14% cost savings) and enhances the system reliability in the case of contingency.

Natural gas consumption and the share of renewable energy in meeting global energy demand has grown dramatically in the recent years. On the other hand, the rapid growth of gas-fired generating units (GFU) (i.e., producing lower carbon dioxide emissions compared to coal-fired generating units), could play a key role in more integration of renewable energy sources (RESs) into the system due to their high flexibility. Therefore, the interaction between the electricity and natural gas networks (ENGN) becomes more challenging. This paper proposes a robust multi objective integrated mixed integer nonlinear optimization model, utilizing information-gap decision theory (IGDT), for secure and optimal operation of ENGN considering security constraints as well as gas and electricity load demand uncertainties. This bi-objective optimization problem is modified using normalization in the weighted sum method in order to ensuring the consistency of the optimal solutions. The proposed framework is validated on the modified IEEE 24-bus power system with a 15-node natural gas system.

The increased interdependencies between electricity and gas systems driven by gas-fired power plants and gas electricity-driven compressors necessitates detailed investigation of such interdependencies, especially in the context of an increased share of renewable energy sources. In this paper, the value of an integrated approach for operating gas and electricity systems is assessed. An outer approximation with equality relaxation (OA/ER) method is used to deal with the optimization class of the mixed-integer non-linear problem of the integrated operation of gas and electricity systems. This method significantly improved the efficiency of the solution algorithm and achieved a nearly 40% reduction in computation time compared to successive linear programming. The value of flexibility technologies, including flexible gas compressors, demand-side response, battery storage, and power-to-gas, is quantified in the operation of integrated gas and electricity systems in GB 2030 energy scenarios for different renewable generation penetration levels. The modeling demonstrates that the flexibility options will enable significant cost savings in the annual operational costs of gas and electricity systems (up to 21%). On the other hand, the analysis carried out indicates that deployment of flexibility technologies appropriately supports the interaction between gas and electricity systems.

The growing interdependencies between natural gas and power systems, driven by gas-fired generators and gas compressors supplied by electricity, necessitates detailed investigation of the interactions between these vectors, particularly in the context of growing penetration of renewable energy sources. In this research, an expansion planning model for integrated natural gas and power systems is proposed. The model investigates optimal investment in flexibility options such as battery storage, demand-side response, and gas-fired generators. The value of these flexibility options is quantified for gas and electricity systems in Great Britain in 2030. The results indicate that the flexibility options could play an important role in meeting the emission targets in the future. However, the investment costs of these options highly impact the future generation mix as well as the type of reinforcements in the natural gas system infrastructure. Through the deployment of the flexibility options up to £ 24 .2 billion annual cost savings in planning and operation of natural gas and power systems could be achieved, compared to the case that no flexibility option is considered.

The power systems in many countries are undergoing a radical transformation through employing a large capacity of renewable generation technologies such as wind turbine and solar photovoltaic. The power generation by wind and solar resources are variable and difficult to predict. Therefore, growing capacities of such technologies is expected to introduce challenges regarding balancing electricity supply and demand. This paper investigates the role of battery storage and power-to-gas systems to accommodate large capacity of intermittent power generation from wind and solar and therefore facilitates matching electricity supply and demand. The Combined Gas and Electricity Networks (CGEN) model was used to optimize the operation of gas and electricity networks in GB for typical weeks in winter and summer in 2030. The role of different capacity of battery storage and power-to-gas systems in reducing the wind curtailment and operating cost of the system were quantified and compared with the annualized cost of these technologies.

A detailed investigation of the interaction between natural gas and power systems is necessary, due to the increasing interdependency of these vectors, especially in the context of renewable generations integration growth into the grid. In this study, an outer approximation with an equality relaxation decomposition method is proposed to solve a mixed-integer non-linear problem representing the operation of coupled natural gas and power systems. The proposed coupled modelling of natural gas and power systems is compared to decoupled operational modelling. It is demonstrated that operating gas and electricity as a coupled system resulted in about 7% of operational cost savings. In addition, the value of gas-related flexibility options, including flexible gas compressors, flexible gas generation plants, and gas interconnections, to the operation of natural gas and power systems is quantified for a 2030 GB energy system. It is shown that if the natural gas and power systems are flexible enough, the operation of the systems in the decoupled approach is almost the same as the coupled model and therefore there is no need to reform the current energy market framework to make the systems fully coupled.

Gas-fired power plants are commonly employed to deal with the intermittency of renewable energy resources due to their flexible characteristics. Therefore, the intermittency in the power system transmits to the gas system through the gas-fired power plants, which makes the operation of these systems even more interdependent. This study proposes a novel possibilistic model for the integrated operation of gas and power systems in the presence of electric vehicles and demand response. The model takes into account uncertainty in demand prediction and output power of wind farms, which is based on possibility and necessity theories in fuzzy logic through modeling uncertain parameters by Gaussian membership function. Moreover, a contingency analysis algorithm based on maximin optimization is developed to enhance the resiliency in the integrated operation of these systems by finding the worst-case scenario for the outage of components. The proposed model is implemented on a Belgium gas network and IEEE 24-bus electricity network. It is demonstrated that the possibilistic model allows the gas network to respond to the demand variations by providing a sufficient level of linepack within the pipelines. As a result, gas-fired power plants are supposed to commit more efficiently to cope with the intermittency of wind farms, which reduce the wind curtailment by 26%. Furthermore, it is quantified that through applying the contingency analysis algorithm in presence of demand response and electrical vehicles, the costs of operation and load shedding is reduced up to 17% and 83%, respectively.

The integration of distributed generations such as photovoltaic and wind as well as large load variations leads to the significant issue of frequency stability problem. This paper presents a multi-stage frequency control for microgrids. Energy storage systems such as BESSs are selected as a flexible and fast-response device for this application. In the first stage, a PI control method based on PSO for the BESS is applied in order to minimize the frequency deviations. Moreover, in contingency modes, in which the BESS with the optimized PI control application cannot stabilize the system due to the unbalanced situation of supply and demand, fast reaction of the central control system operator is necessary in order to protect the network from collapse. Hence, in the second stage of the control, a Fuzzy-logic frequency controller as a smart controller is designed. This controller proposes solutions through power level change such as load shedding in a short time to rescue the network from instability. ...

The interaction between natural gas and electricity networks is becoming more significant due to the projected large penetration of renewables into the energy system to meet the emission targets. This is due to the role of gas-fired plants in providing backup to renewables as the linkage between these networks. Therefore, this paper proposes a deterministic coordinated model for the secure and optimal operation of integrated natural gas and electricity transmission networks by taking into account the N-1 contingency analysis on both networks. In order to reduce the computational burden and time, an iterative algorithm is proposed to select the critical cases and neglect other contingencies, which do not have a significant impact on the energy system. The proposed integrated mixed-integer nonlinear programming operational model is evaluated and compared to another enhanced separated model on the IEEE 24-bus and 15-node gas test systems. The results emphasize the importance and effectiveness of the proposed framework (up to 6.7% operational costs savings are achieved).

The electricity system balancing is becoming increasingly challenging due to the integration of Renewable Energy Sources (RES). At the same time, the dependency of electricity network on gas supply system is expected to increase, as a result of employing flexible gas generators to support the electricity system balancing. Therefore the capability of the gas supply system to deliver gas to generators under a range of supply and demand scenarios is of a great importance. As potential solutions to improve security of gas and electricity supply, this paper investigates benefits of employing flexible multi-directional compressor stations as well as adopting a fully integrated approach to operate gas and electricity networks. A set of case studies for a GB gas and electricity networks in 2030 have been defined to quantify the value of an integrated operation paradigm versus sequential operation of gas and electricity networks. The results indicate there are significant overall system benefits (up to 65% in extreme cases) to be gained from integrated optimization of gas and electricity systems, emphasizing the important role of gas network infrastructure flexibility in efficiently accommodating the expected expansion of intermittent RES in future power systems.

Integration of a large capacity of wind generation in the Great Britain (GB) electricity network is expected to pose a number of operational challenges. The variable nature of wind generation necessitates introduction of technologies that can provid e flexibility to generation portfolios and therefore compensate for intermittency of wind generation. In this paper, the efficacy of three options to address electricity balancing challenges was evaluated: flexible gas - fired plants, electricity storage and Power - to - Gas system. The combined gas and electricity network model (CGEN) was enhanced and th rough adopting a rolling optimis ation approach the model aims at minimi s ing the operational cost of an integrated gas and electricity networks that represents a GB system in 2030. The potential impacts of employing each of the flexibility options on the operation of the integrate d electricity and gas networks we re investigated . The analysis showed that amongst all the flexibility options, the deployment of grid - sc ale electricity storage will achieve the highest reduction in the operational cost of the integrated system ( £12 million reduction in a typical winter week, and £3 million reduction in a typical summer week) . The results of this study provide insights on the system - wide benefits offered by each of the flexibility options and role of the gas network in the energy system with large capacity of wind generation.

Summary Due to the global concerns regarding the climate change, integration of renewable energy sources is considered as a mitigation approach in electric power generation. This requires advanced frequency and voltage control methodologies to overcome the challenges especially in microgrids. This paper presents a 2-step frequency and voltage control methodology for microgrids with high penetration of variable renewable energy sources. An optimized Proportional-Integral controller is designed for a Superconductor Magnetic Energy Storage System to minimize the transient frequency deviations. In cases that the Superconductor Magnetic Energy Storage System cannot stabilize the microgrid frequency in the isolated mode, the microgrid controller activates the next level of the frequency control. In the second level, an intelligent fuzzy-logic frequency controller is designed to adjust controllable loads, controllable generation units as well as perform load shedding. In the interconnected mode, the microgrid controller is able to activate the second level to contribute to the system frequency control. Finally, an intelligent fuzzy-logic voltage controller, realized through distribution static synchronous compensator, is devised to control the voltage magnitude of the main feeders of the microgrid. In this work, a real-time operation algorithm for frequency as well as voltage control is proposed and has been tested by set of simulations on a low voltage benchmark network.

Background: Course failing and delayed graduation are important concerns in educational systems. The reasons of these educational failures need to be clarified. Objectives: This study was designed to determine the academic failure rate and its predictors in Nursing and Midwifery Students in Kashan University of Medical Sciences. Materials and Methods: In this cross-sectional study, the records of all the students graduated in Nursing and Midwifery faculty during 18 years (1986 - 2003) were evaluated (1174 graduates). The demographic variables and the educational situation were recorded. The frequency of course repetition, probation, and delayed graduation were determined and the data were analyzed using the chi-square and logistic regression tests. Results: The frequency of course repetition, probation, and delayed graduation was reported to be 19.25%, 3.9% and 19.85%, respectively. Gaining Low grade in high school, transferring from other universities, having special quota, and transferring temporarily to other universities were mentioned as the risk factors of academic failure. The major had a significant relationship with academic failure. Day time students had more course failure and night time students stayed longer in the university. Conclusions: The individual characteristics, educational background and admission criteria had showed relation with academic failure. Vulnerable students should be identified and educational supports should be provided for these students.

This paper presents an optimized scheduling method, a planning strategy, and a frequency control method for a hybrid system supplying an isolated network. The hybrid system consists of a wind energy conversion system, a diesel engine generator, and a battery energy storage system. Minimization of the operation cost is the objective of the optimized operation. Consequently, emission of the system is minimized. The presented operation strategy is formulated and implemented in MATLAB using sequential quadratic programming. A planning strategy based on the optimized operation method is developed to choose between limited installed capacities of battery energy storage systems and wind energy conversion systems to minimize cost of electrification of the isolated network. In the last step, a frequency control strategy is developed and implemented in MATLAB Simulink. In addition to transient response of the system, the strategy is taking into account emission reduction of the system. The developed methods are validated by a set of simulations.

Complex segregation analyses were conducted on families of bipolar I and bipolar II probands to delineate the mode of inheritance. The probands were ascertained from consecutive referrals to the Mood Disorder Service, University Hospital, University of British Columbia and diagnosed by DSM-III-R and Research Diagnostic Criteria. Data were available on over 1,500 first-degree relatives of the 186 Caucasian probands. The purpose of the analyses was to determine if, after correcting for age and birth cohort, there was evidence for a single major locus. Five models were fit to the data using the statistical package SAGE: i) dominant, ii) recessive, iii) arbitrary mendelian inheritance, iv) environmental, and v) no major effects. A single dominant, mendelian major locus was the best fitting of these models for the sample of bipolar I and II probands when only bipolar relatives were defined as affected (polygenic inheritance could not be tested). Adding recurrent major depression to the diagnosis "affected" for relatives reduced the evidence for a major locus effect. Our findings support the undertaking of linkage studies and are consistent with the analyses of the National Institutes of Mental Health (NIMH) Collaborative Study data by Rice et al. (Arch Gen Psychiatry 44: 441-447, 1987) and Blangero and Elston (Genet Epidemiol 6:221-227, 1989).