The interaction of pulsed electric fields and texturizing ‐ antifreezing agents in quality retention of defrosted potato strips

The combination of pulsed electric fields (PEF) and texturizing and antifreeze agents on quality retention of defrosted potato strips were studied. Potato strips (10 mm thickness, 100 g) were placed in different solutions (1% w/v) of CaCl₂, glycerol, trehalose as well as NaCl and sucrose, treated with PEF (0.5 kV cm^?1, 100 pulses, 4 Hz). Then, all the samples were soaked in the same solutions for 10 min. After draining, samples were packed into polypropylene pouches and stored at ?18 °C for 12 h. Samples were thawed out at room temperature (20 °C) in 3 h. Untreated controls and PEF treated control samples were also frozen and thawed in similar conditions. To assess the potato strip quality, the thawed samples were analysed for moisture content, weight loss, firmness and colour attributes. The results indicate that PEF treatment by itself is not a suitable pre‐treatment method for frozen potato strips and should be assisted by CaCl₂ and trehalose treatment to prevent softening after defrosting. Firmness analyses determined that application of PEF alone results in 2.38 N. However, PEF in combination with CaCl₂ and trehalose result in 2.97 N and 2.99 N, respectively, which are both significantly firmer than the samples solely treated with PEF. CaCl₂ and trehalose were effective in not only maintaining the structural integrity of the cells, but also retaining colour attributes. The L* value was found to be higher (P < 0.05) in CaCl₂ and trehalose treated samples (58.95 and 57.21, respectively), as compared to PEF treated samples (53.97) denoting a darker colour. Application of CaCl₂ and trehalsoe in combination with PEF also resulted in significantly less weight loss after thawing.     

Mixed integer programming of generalized hydro-thermal self-scheduling of generating units

This paper presents the application of mixed-integer programming (MIP) approach for solving the hydro-thermal self scheduling (HTSS) problem of generating units. In the deregulated environment, the generation companies schedule their generators to maximize their profit while satisfying loads is not an obligation. The HTSS is a high dimensional mixed-integer optimization problem. Therefore, in the large-scale power systems, solving the HTSS is very difficult. In this paper, MIP formulation is adopted for precise modeling of dynamic ramp rate limits, prohibited operating zones, operating services, valve loading effects, variable fuel cost, non-linear start-up cost functions of thermal units, fuel and emission limits of thermal units, multi head power-discharge characteristics of hydro plants and spillage of reservoir. The modified IEEE 118-bus system is used to demonstrate the performance of the proposed method.     

Reactive power market development considering power system security

In the new open access environment, in pursuit of profit, power producers tend to operate closer to the security boundaries and consequently, the voltage instability, which is caused by insufficient reactive power support, threats system security and reliability. This paper presents a day-ahead reactive power market based on uniform auction price scheme considering voltage security. First, expected payment function (EPF), identified earlier in the literature to construct a bidding framework for synchronous generators, is modified. Then, the modified EPF is used as the objective function of optimal power flow problem to clear reactive power market. Finally, the OPF, including overload, voltage drop and voltage stability margin in its constraints, is solved by binary coded genetic algorithm. The validity of the proposed reactive power market is studied based on the IEEE 24-bus reliability test system.     

Adrenal responsiveness in lactating holstein cows.

Ten Holstein cows, in second to fifth lactation, received 200 IU adrenocorticotrophin at approximately 4, 8, 16, 24, 32, and 40 wk of lactation. Blood samples were collected from indwelling jugular catheters at -60 and 0 min pre-injection and at 2, 6, 10, 15, 20, 30, 45, 60, 120, 180, 240, 360, 540, and 720 min postinjection. Post-injection concentrations of glucocorticoids were influenced by milk yield, stage of lactation, age, and mean environmental temperature but not by pre-injection concentration of glucocorticoids or days pregnant. As milk yield, cow age, and daily temperature (range 6.4 to 26.9 C) increased, glucocorticoid response decreased whereas it increased with advancing stage of lactation. Curves of adrenal response for the six injection times during lactation were not parallel, and average response adjusted for significant independent variables increased roughly in linear fashion from 15 to 53 ng/ml between 4 and 40 wk of lactation. Adrenal responsiveness was less in cows injected on days when temperatures were above 21.1 C than in those injected below this temperature. There was no evidence that adrenal function or milk production was altered in high producing cows at higher environmental temperatures differently from in low producing cows. The change in adrenal function during advancing lactation was not associated with pre-treatment peripheral plasma glucocorticoid concentrations which did not change. There appears to be a well mainained adrenal potential and sustained adrenocortical activity throughout lactation.     

Joint market clearing in a stochastic framework considering power system security

This paper presents a new stochastic framework for provision of reserve requirements (spinning and non-spinning reserves) as well as energy in day-ahead simultaneous auctions by pool-based aggregated market scheme. The uncertainty of generating units in the form of system contingencies are considered in the market clearing procedure by the stochastic model. The solution methodology consists of two stages, which firstly, employs Monte–Carlo Simulation (MCS) for random scenario generation. Then, the stochastic market clearing procedure is implemented as a series of deterministic optimization problems (scenarios) including non-contingent scenario and different post-contingency states. The objective function of each of these deterministic optimization problems consists of offered cost function (including both energy and reserves offer costs), Lost Opportunity Cost (LOC) and Expected Interruption Cost (EIC). Each optimization problem is solved considering AC power flow and security constraints of the power system. The model is applied to the IEEE 24-bus Reliability Test System (IEEE 24-bus RTS) and simulation studies are carried out to examine the effectiveness of the proposed method.     

Mixed integer programming of multiobjective hydro-thermal self scheduling

This paper presents a method for hydro-thermal self scheduling (HTSS) problem in a day-ahead joint energy and reserve market. The HTSS is modeled in the form of multiobjective framework to simultaneously maximize GENCOs profit and minimize emissions of thermal units. In the proposed model the valve loading effects which is a nonlinear problem by itself is linearized. Also a dynamic ramp rate of thermal units is used instead of a fix rate leading to more realistic formulation of HTSS. Furthermore, the multi performance curves of hydro units is developed and prohibited operating zones (POZs) of thermal unit are considered in HTSS problem. Also, in the proposed framework, the mixed integer nonlinear programming (MINLP) of HTSS is converted to mixed integer programming (MIP) problem that can be effectively solved by optimization softwares even for real size power systems. The lexicographic optimization and hybrid augmented-weighted ?-constraint technique is implemented to generate Pareto optimal solutions. The best compromised solution is adopted either by using a fuzzy approach or by considering arbitrage opportunities to achieve more profit. Finally, the effectiveness of the proposed method is studied based on the IEEE 118-bus system.     

Modeling of stochastic behavior of plug-in hybrid electric vehicle in a reactive power market

This paper presents a stochastic reactive power market which incorporates plug-in hybrid electric vehicles (PHEVs) in the reactive power market. The uncertainty of PHEVs as well as synchronous generators in the form of system contingencies are explicitly considered in the stochastic market-clearing scheme. The capability curve of PHEV is extracted and after that the expected payment function of PHEV is proposed based on its capability curve. In the proposed stochastic reactive power market, the Monte-Carlo simulation is used to generate random scenarios. The stochastic market-clearing procedure is then implemented as a series of deterministic optimization problems (scenarios) including non-contingent scenario and different post-contingency states. The objective function of each scenario is total payment function of PHEVs and synchronous generators which refers to the payment paid to the generators and PHEV owners for their reactive power compensation. A typical 17-node microgrid is used in the case study.     

Solubility of celecoxib in N-methyl-2-pyrrolidone+water mixtures at various temperatures: Experimental data and thermodynamic analysis

Solubility is one of the most significant physicochemical properties of drugs, and improving the solubility of drugs is still a challenging subject in pharmaceutical sciences due to requirements of enhancing their bioavailability. Celecoxib, according to the biopharmaceutics classification system (BCS), is a class 2 drug, possessing low water solubility (<5 μg·mL^?1) and high permeability. Increasing the solubility of this group can lead to improved bioavailability, dose reduction and subsequently, increased efficiency and reduced side effects. In this study, celecoxib solubility was determined in binary mixtures of N-methyl-2-pyrrolidone (NMP)+water at 293.2, 298.2, 303.2, 308.2 and 313.2 K. The solubility of celecoxib is increased with the addition of NMP to the aqueous solutions and reaches a maximum value in neat NMP. In addition, increased temperature leads to enhanced solubility of celecoxib in a given solvent composition. The solubility data of celecoxib in NMP+water at different temperatures were correlated using different mathematical models including, the Jouyban-Acree model and a combination of the Jouyban-Acree and van’t Hoff models. Thermodynamic parameters, Gibbs energy, enthalpy and entropy of dissolution processes were performed based on Gibbs and van’t Hoff equations. Thermodynamic analysis allowed observing two main entropy or enthalpy-driven dissolution mechanisms, varying according to the composition of aqueous mixtures. Moreover, preferential solvation of celecoxib by water is observed in water-rich mixtures but preferential solvation by NMP was seen in mixtures with similar composition and also in NMP-rich mixtures.     

Stochastic Multiobjective Market Clearing of Joint Energy and Reserves Auctions Ensuring Power System Security

In this paper, a stochastic multiobjective framework is proposed for day-ahead joint market clearing. The proposed multiobjective framework can concurrently optimize competing objective functions including augmented generation offer cost and security indices (overload index, voltage drop index, and voltage stability margin). Besides, system uncertainties including generating units and branches contingencies and load uncertainty are explicitly considered in the stochastic market clearing scheme. The solution methodology consists of two stages, which firstly, employs roulette wheel mechanism and Monte Carlo simulation (MCS) for random adaptive 24-h scenario generation wherein the stochastic multiobjective market clearing procedure is converted into its respective deterministic equivalents (scenarios). In the second stage, for each deterministic scenario, a multiobjective mathematical programming (MMP) formulation based on the epsiv -constrained approach is implemented for provision of spinning reserve (SR) and nonspinning reserve (NSR) as well as energy. The MMP formulation of the market clearing process is optimized while meeting AC power flow constraints and expected interruption cost (EIC). The IEEE 24-bus Reliability Test System (RTS 24-bus) is used to demonstrate the performance of the proposed method.