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Effects of Glucose and Amino Acids on Free ADP in βHC9 Insulin-Secreting Cells Peter Ronner , C. Maik Naumann and Edward Friel From the Department of Biochemistry and Molecular Pharmacology, Thomas Jefferson University College of Medicine, Philadelphia, Pennsylvania. Address correspondence and reprint requests to Dr. Peter Ronner, Department of Biochemistry and Molecular Pharmacology, 233 South 10th St., 245 BLSB, Thomas Jefferson University, Philadelphia, PA 19107-5541. E-mail: peter.ronner{at}mail.tju.edu . Abstract Stimulation of insulin release by glucose is widely thought to be coupled to a decrease in the activity of ATP-sensitive K + channels (K ATP channels) that is caused by a decreased concentration of free ADP. To date, most other investigators have reported only on total cellular ADP concentrations, even though only a small fraction of all ADP is free and only the free ADP affects K ATP channels. We tested the hypothesis that amino acids elicit insulin release via a decrease in the activity of K ATP channels owing to a decrease in the level of free ADP. We estimated the concentration of free ADP in βHC9 hyperplastic insulin-secreting cells based on the cell diameter and on luminometric measurements of ATP, phosphocreatine, and total creatine. The concentration of free ADP fell exponentially as the concentration of glucose increased. A physiological mixture of amino acids greatly stimulated insulin release at 0-30 mmol/l glucose but affected the concentration of free ADP only to a minor degree and significantly so only at ≤2 mmol/l glucose. In the presence of 2-deoxyglucose and NaN 3 , amino acids were unable to stimulate insulin release. When K ATP channels were held open with diazoxide (and the plasma membrane partially depolarized with high extracellular KCl), amino acids still stimulated insulin release. We conclude that amino acid—induced insulin release depends on two components: a yet-unknown amino acid sensor and K ATP channels, which serve to attenuate hormone release when cellular energy stores are low. We propose that glucose-induced insulin release may be regulated similarly by two components: glucokinase and K ATP channels. Footnotes GLP, glucagon-like peptide; IBMX, isobutyl methyl xanthine; K ATP channel, ATP-sensitive K + channel. Accepted October 11, 2000. Received February 23, 2000. by the American Diabetes Association, Inc.

Stimulation of insulin release by glucose is widely thought to be coupled to a decrease in the activity of ATP-sensitive K+ channels (KATP channels) that is caused by a decreased concentration of free ADP. To date, most other investigators have reported only on total cellular ADP concentrations, even though only a small fraction of all ADP is free and only the free ADP affects KATP channels. We tested the hypothesis that amino acids elicit insulin release via a decrease in the activity of KATP channels owing to a decrease in the level of free ADP. We estimated the concentration of free ADP in betaHC9 hyperplastic insulin-secreting cells based on the cell diameter and on luminometric measurements of ATP, phosphocreatine, and total creatine. The concentration of free ADP fell exponentially as the concentration of glucose increased. A physiological mixture of amino acids greatly stimulated insulin release at 0-30 mmol/l glucose but affected the concentration of free ADP only to a minor degree and significantly so only at < or = 2 mmol/l glucose. In the presence of 2-deoxyglucose and NaN3, amino acids were unable to stimulate insulin release. When KATP channels were held open with diazoxide (and the plasma membrane partially depolarized with high extracellular KCl), amino acids still stimulated insulin release. We conclude that amino acid-induced insulin release depends on two components: a yet-unknown amino acid sensor and KATP channels, which serve to attenuate hormone release when cellular energy stores are low. We propose that glucose-induced insulin release may be regulated similarly by two components: glucokinase and KATP channels.

Battery energy storage systems (BESS) coupled with rooftop-mounted residential photovoltaic (PV) generation, designated as PV-BESS, draw increasing attention and market penetration as more and more such systems become available. The manifold BESS deployed to date rely on a variety of different battery technologies, show a great variation of battery size, and power electronics dimensioning. However, given today’s high investment costs of BESS, a well-matched design and adequate sizing of the storage systems are prerequisites to allow profitability for the end-user. The economic viability of a PV-BESS depends also on the battery operation, storage technology, and aging of the system. In this paper, a general method for comprehensive PV-BESS techno-economic analysis and optimization is presented and applied to the state-of-art PV-BESS to determine its optimal parameters. Using a linear optimization method, a cost-optimal sizing of the battery and power electronics is derived based on solar energy availability and local demand. At the same time, the power flow optimization reveals the best storage operation patterns considering a trade-off between energy purchase, feed-in remuneration, and battery aging. Using up to date technology-specific aging information and the investment cost of battery and inverter systems, three mature battery chemistries are compared; a lead-acid (PbA) system and two lithium-ion systems, one with lithium-iron-phosphate (LFP) and another with lithium-nickel-manganese-cobalt (NMC) cathode. The results show that different storage technology and component sizing provide the best economic performances, depending on the scenario of load demand and PV generation.

The application of stationary battery storage systems to German electrical grids can help with various storage services. This application requires controlling the charge and discharge power of such a system. For example, photovoltaic (PV) home storage, uninterruptible power supply, and storage systems for providing ancillary services such as primary control reserves (PCRs) represent battery applications with positive profitability. Because PCRs are essential for stabilizing grid frequency and maintaining a robust electrical grid, German transmission system operators (TSOs) released strict regulations in August 2015 for providing PCRs with battery storage systems as part of regulating the International Grid Control Cooperation (IGCC) region in Europe. These regulations focused on the permissible state of charge (SoC) of the battery during nominal and extreme conditions. The concomitant increased capacity demand oversizing may result in a significant profitability reduction, which can be attenuated only by using an optimal parameterization of the control algorithm for energy management of the storage systems. In this paper, the sizing optimization is achieved and a recommendation for a control algorithm that includes the appropriate parameters for the requirements in the German market is given. Furthermore, the storage cost is estimated, including battery aging simulations for different aging parameter sets to allow for a realistic profitability calculation.

Self-consumption of household photovoltaic (PV) storage systems has become profitable for residential owners under the trends of limited feed-in power and decreasing PV feed-in tariffs. For individual PV-storage systems, the challenge mainly lies in managing surplus generation of battery and grid power flow, ideally without relying on error-prone forecasts for both generation and consumption. Considering the large variation in power profiles of different houses in a neighborhood, the strategy is also supposed to be beneficial and applicable for the entire community. In this study, an adaptable battery charging control strategy is designed in order to obtain minimum costs for houses without any meteorological or load forecasts. Based on fuzzy logic control (FLC), battery state-of-charge (SOC) and the variation of SOC (∆SOC) are taken as input variables to dynamically determine output charging power with minimum costs. The proposed FLC-based algorithm benefits from the charging battery as much as possible during the daytime, and meanwhile properly preserves the capacity at midday when there is high possibility of curtailment loss. In addition, due to distinct power profiles in each individual house, input membership functions of FLC are improved by particle swarm optimization (PSO) to achieve better overall performance. A neighborhood with 74 houses in Germany is set up as a scenario for comparison to prior studies. Without forecasts of generation and consumption power, the proposed method leads to minimum costs in 98.6% of houses in the community, and attains the lowest average expenses for a single house each year.

Residential photovoltaic (PV) battery systems increase households’ electricity self-consumption using rooftop PV systems and thus reduce the electricity bill. High investment costs of battery systems, however, prevent positive financial returns for most present residential battery installations in Germany. Tesla Motors, Inc. (Palo Alto, CA, USA) announced a novel battery system—the Powerwall—for only about 25% of the current German average market price. According to Tesla’s CEO Elon Musk, Germany is one of the key markets for their product. He has, however, not given numbers to support his statement. In this paper, we analyze the economic benefit of the Powerwall for end-users with respect to various influencing parameters: electricity price, aging characteristics of the batteries, topology of battery system coupling, subsidy schemes, and retrofitting of existing PV systems. Simulations show that three key-factors strongly influence economics: the price gap between electricity price and remuneration rate, the battery system’s investment cost, and the usable battery capacity. We reveal under which conditions a positive return on invest can be achieved and outline that the Powerwall could be a worthwhile investment in multiple, but not all, scenarios investigated. Resulting trends are generally transferrable to other home storage products.