Optimal Pricing Algorithm in the Electricity Market with Battery and Accumulator and Demand–Supply Balancing

This paper considers the day‐ahead market with batteries and accumulators to level power generation. First, we model consumers with batteries, generators with batteries, and accumulators, all of whom strive to maximize their own profit. An optimal pricing algorithm based on dual decomposition and the steepest descent method is derived and shown to be stable. Finally, the effectiveness of the algorithm is demonstrated by means of numerical simulations which indicate that it achieves demand–supply balance.     

Optimal siting and sizing of demand response in a transmission constrained system with high wind penetration

This paper describes algorithms that use demand-side management to address large-scale integration of wind power. In particular, demand response (DR) is used to manage wind power intermittency by shifting the time that electrical power system loads occur in response to real-time prices and wind availability. An economic dispatch with transmission, DR capacity and operational constraints is used to model the operation of a transmission constrained system with a high penetration of wind power. This optimization model is used to determine the optimal sizing and distribution of DR given a fixed budget for customer incentives and the installation of enabling technology. We demonstrate the effectiveness of the operational model based on a simple PJM 5-bus system and an IEEE 118-bus system. Simulation results show that transmission constraints have a greater effect on sizing of DR capacity than the location of wind power, which means that buses electrically close to congested lines tend to have higher incentives to deploy DR resources than other buses. The second part of the work examines optimal siting of technology that enables DR based on the frequency of DR based load changes, which are generally a function of the network location.     

模拟3种有机膦系阻垢剂与方解石(104)面的相互作用

通过pH曲线实验研究了乙二胺四亚甲基膦酸(EDTMP),己二胺四亚甲基膦酸(HDTMP)和二乙烯三胺五亚甲基膦酸(DTPMP)对碳酸钙垢的阻垢性能,在相同的加药浓度下阻垢性能强弱顺序为:DTPMPEDTMPHDTPM。同时采用周期性边界条件下的分子动力学方法,模拟研究了在水分子存在条件下各阻垢剂与方解石(104)面的相互作用,得到了相应的结合能和原子间距离等参数。结果表明:阻垢分子膦酸基团中的双键氧与碳酸钙中的Ca~(2+)形成的强静电相互作用力对吸附起了主导作用,同时膦酸基团中的氢与晶面中的氧形成了氢键,加强了吸附效果。综合考虑各分子在晶面(104)上的吸附效果,其结果与实验相符合;从分子中膦酸基团作用个数也可看出,HDTMP只有一个膦酸基团靠近晶面,因此作用力也是最弱的。     

Optimisation of process parameters to develop nutritionally rich spray‐dried honey powder with vitamin C content and antioxidant properties

The aim of present research was to optimise the conditions to develop nutritionally rich honey powder using honey, whey protein concentrate (WPC), aonla (Emblica officinalis. Gaertn) and basil (Ocimum sanctum) extract with the help of co‐current spray drier. Response surface methodology was applied to study the effects of inlet temperature (160–180 °C), whey protein concentrate (25–35%), feed flow rate (0.08–0.13 mL s^?1), aonla extract (6–8%) and basil extract (6–8%) on product responses, viz. bulk density, hygroscopicity, antioxidant activity (AOA), total phenolic content (TPC) and vitamin C. Statistical analysis revealed that independent variables significantly affected all the responses. The results demonstrated that increasing inlet temperature lowered the bulk density, hygroscopicity, AOA, TPC and vitamin C, whereas addition of aonla extract and basil extract increased the AOA (82.73%), TPC (63.27%) and total vitamin C content (94.89%) as these functional compounds were encapsulated by WPC. Similarly, with increase in feed flow rate and WPC, there was increase and decrease in the bulk density and hygroscopicity, respectively. The recommended optimum spray‐drying conditions were inlet air temperature (170 °C), feed rate (0.11 mL s^?1), whey protein concentrate (35%), aonla (8%) and basil extract (6%).     

Rogowski coil current transducer compensation method for harmonic active power error

In the harmonic active power measurement, the highest uncertainties are generally introduced by the current and voltage transducers. In a previous paper, the authors showed that the current transformer (CT) can introduce significant errors in such measurement, especially if the phase shift between voltage and current is close to ±90°. In such condition the errors on harmonic power measurement are mainly due to the CT phase displacement. This paper shows that better results can be achieved with more linear transducers, such as the Rogowski coil current transducers (RCCTs), whose metrological performance in distorted condition can be improved, by means of a proper compensation method. The proposed method for RCCTs compensation is based on the frequency response and it allows to reduce the errors on harmonic power measurement, also for phase shift close to ±90°. The study is supported by several experimental tests.     

Elitist clonal selection algorithm for optimal choice of free knots in B-spline data fitting

Data fitting with B-splines is a challenging problem in reverse engineering for CAD/CAM, virtual reality, data visualization, and many other fields. It is well-known that the fitting improves greatly if knots are considered as free variables. This leads, however, to a very difficult multimodal and multivariate continuous nonlinear optimization problem, the so-called knot adjustment problem. In this context, the present paper introduces an adapted elitist clonal selection algorithm for automatic knot adjustment of B-spline curves. Given a set of noisy data points, our method determines the number and location of knots automatically in order to obtain an extremely accurate fitting of data. In addition, our method minimizes the number of parameters required for this task. Our approach performs very well and in a fully automatic way even for the cases of underlying functions requiring identical multiple knots, such as functions with discontinuities and cusps. To evaluate its performance, it has been applied to three challenging test functions, and results have been compared with those from other alternative methods based on AIS and genetic algorithms. Our experimental results show that our proposal outperforms previous approaches in terms of accuracy and flexibility. Some other issues such as the parameter tuning, the complexity of the algorithm, and the CPU runtime are also discussed.     

Reactive Oxygen and Nitrogen Species in Defense/Stress Responses Activated by Chitosan in Sycamore Cultured Cells

Chitosan (CHT) is a non-toxic and inexpensive compound obtained by deacetylation of chitin, the main component of the exoskeleton of arthropods as well as of the cell walls of many fungi. In agriculture CHT is used to control numerous diseases on various horticultural commodities but, although different mechanisms have been proposed, the exact mode of action of CHT is still unknown. In sycamore (Acer pseudoplatanus L.) cultured cells, CHT induces a set of defense/stress responses that includes production of H₂O₂ and nitric oxide (NO). We investigated the possible signaling role of these reactive molecules in some CHT-induced responses by means of inhibitors of production and/or scavengers. The results show that both reactive nitrogen and oxygen species are not only a mere symptom of stress conditions but are involved in the responses induced by CHT in sycamore cells. In particular, NO appears to be involved in a cell death form induced by CHT that shows apoptotic features like DNA fragmentation, increase in caspase-3-like activity and release of cytochrome c from the mitochondrion. On the contrary, reactive oxygen species (ROS) appear involved in a cell death form induced by CHT that does not show these apoptotic features but presents increase in lipid peroxidation.     

Prediction of Long-Term Treatment Response to Selective Serotonin Reuptake Inhibitors (SSRIs) Using Scalp and Source Loudness Dependence of Auditory Evoked Potentials (LDAEP) Analysis in Patients with Major Depressive Disorder

Background: Animal and clinical studies have demonstrated that the loudness dependence of auditory evoked potentials (LDAEP) is inversely related to central serotonergic activity, with a high LDAEP reflecting weak serotonergic neurotransmission and vice versa, though the findings in humans have been less consistent. In addition, a high pretreatment LDAEP appears to predict a favorable response to antidepressant treatments that augment the actions of serotonin. The aim of this study was to test whether the baseline LDAEP is correlated with response to long-term maintenance treatment in patients with major depressive disorder (MDD). Methods: Scalp N1, P2 and N1/P2 LDAEP and standardized low resolution brain electromagnetic tomography-localized N1, P2, and N1/P2 LDAEP were evaluated in 41 MDD patients before and after they received antidepressant treatment (escitalopram (n = 32, 10.0 ± 4.0 mg/day), sertraline (n = 7, 78.6 ± 26.7 mg/day), and paroxetine controlled-release formulation (n = 2, 18.8 ± 8.8 mg/day)) for more than 12 weeks. A treatment response was defined as a reduction in the Beck Depression Inventory (BDI) score of >50% between baseline and follow-up. Results: The responders had higher baseline scalp P2 and N1/P2 LDAEP than nonresponders (p = 0.017; p = 0.036). In addition, changes in total BDI score between baseline and follow-up were larger in subjects with a high baseline N1/P2 LDAEP than those with a low baseline N1/P2 LDAEP (p = 0.009). There were significantly more responders in the high-LDAEP group than in the low-LDAEP group (p = 0.041). Conclusions: The findings of this study reveal that a high baseline LDAEP is associated with a clinical response to long-term antidepressant treatment.     

Demand response for home energy management system

The optimization of energy consumption, with consequent cost reduction, is one of the main challenges for the present and future smart grid. Demand response (DR) program is expected to be vital in home energy management system (HEMS) which aims to schedule the operation of appliances to save energy costs by considering customer convenience as well as characteristics of electric appliances. The DR program is a challenging optimization problem especially when the formulations are non-convex or NP-hard problems. In order to solve this challenging optimization problem efficiently, an effective heuristic approach is proposed to achieve a near optimal solution with low computational costs. Different from previously proposed methods in literatures which are not suitable to be run in embedded devices such as a smart meter. The proposed algorithm can be implemented in an embedded device which has severe limitations on memory size and computational power, and can get an optimal value in real-time. Numerical studies were carried out with the data simulating practical scenarios are provided to demonstrate the effectiveness of the proposed method.