The 2012 Power Trading Agent Competition

This is the specification for the Power Trading Agent Competition for 2012 (Power TAC 2012). Power TAC is a competitive simulation that models a “liberalized” retail electrical energy market, where competing business entities or “brokers” offer energy services to customers through tariff contracts, and must then serve those customers by trading in a wholesale market. Brokers are challenged to maximize their profits by buying and selling energy in the wholesale and retail markets, subject to fixed costs and constraints. Costs include fees for publication and withdrawal of tariffs, and distribution fees for transporting energy to their contracted customers. Costs are also incurred whenever there is an imbalance between a broker’s total contracted energy supply and demand within a given time slot. The simulation environment models a wholesale market, a regulated distribution utility, and a population of energy customers, situated in a real location on Earth during a specific period for which weather data is available. The wholesale market is a relatively simple call market, similar to many existing wholesale electric power markets, such as Nord Pool in Scandinavia or FERC markets in North America, but unlike the FERC markets we are modeling a single region, and therefore we do not model location-marginal pricing. Customer models include households and a variety of commercial and industrial entities, many of which have production capacity (such as solar panels or wind turbines) as well as electric vehicles. All have “real-time” metering to support allocation of their hourly supply and demand to their subscribed brokers, and all are approximate utility maximizers with respect to tariff selection, although the factors making up their utility functions may include aversion to change and complexity that can retard uptake of marginally better tariff offers. The distribution utility models the regulated natural monopoly that owns the regional distribution network, and is responsible for maintenance of its infrastructure and for real-time balancing of supply and demand. The balancing process is a market-based mechanism that uses economic incentives to encourage brokers to achieve balance within their portfolios of tariff subscribers and wholesale market positions, in the face of stochastic customer behaviors and weather-dependent renewable energy sources. The broker with the highest bank balance at the end of the simulation wins

The 2015 Power Trading Agent Competition

This is the specification for the Power Trading Agent Competition for 2015 (Power TAC 2015). Power TAC is a competitive simulation that models a “liberalized” retail electrical energy market, where competing business entities or “brokers” offer energy services to customers through tariff contracts, and must then serve those customers by trading in a wholesale market. Brokers are challenged to maximize their profits by buying and selling energy in the wholesale and retail markets, subject to fixed costs and constraints. Costs include fees for publication and withdrawal of tariffs, and distribution fees for transporting energy to their contracted customers. Costs are also incurred whenever there is an imbalance between a broker’s total contracted energy supply and demand within a given time slot. The simulation environment models a wholesale market, a regulated dis

The 2013 Power Trading Agent Competition

This is the specification for the Power Trading Agent Competition for 2013 (Power TAC 2013). Power TAC is a competitive simulation that models a “liberalized” retail electrical energy market, where competing business entities or “brokers” offer energy services to customers through tariff contracts, and must then serve those customers by trading in a wholesale market. Brokers are challenged to maximize their profits by buying and selling energy in the wholesale and retail markets, subject to fixed costs and constraints. Costs include fees for publication and withdrawal of tariffs, and distribution fees for transporting energy to their contracted customers. Costs are also incurred whenever there is an imbalance between a broker’s total contracted energy supply and demand within a given time slot. The simulation environment models a wholesale market, a regulated distribution utility, and a population of energy customers, situated in a real location on Earth during a specific period for which weather data is available. The wholesale market is a relatively simple call market, similar to many existing wholesale electric power markets, such as Nord Pool in Scandinavia or FERC markets in North America, but unlike the FERC markets we are modeling a single region, and therefore we do not model location-marginal pricing. Customer models include households and a variety of commercial and industrial entities, many of which have production capacity (such as solar panels or wind turbines) as well as electric vehicles. All have “real-time” metering to support allocation of their hourly supply and demand to their subscribed brokers, and all are approximate utility maximizers with respect to tariff selection, although the factors making up their utility functions may include aversion to change and complexity that can retard uptake of marginally better tariff offers. The distribution utility models the regulated natural monopoly that owns the regional distribution network, and is responsible for maintenance of its infrastructure and for real-time balancing of supply and demand. The balancing process is a market-based mechanism that uses economic incentives to encourage brokers to achieve balance within their portfolios of tariff subscribers and wholesale market positions, in the face of stochastic customer behaviors and weather-dependent renewable energy sources. The broker with the highest bank balance at the end of the simulation wins

Waste Recycling for the Eco-friendly Input Use Efficiency in Agriculture and Livestock Feeding

he increasing competition for available resources and inefficient use of those limited resources necessitates the need to improve the use of available resources. If these inefficacies are not corrected, the resource-poor farmers, mainly living in developing countries will be most affected. Yet these resource farmers contribute immensely for food production in developing countries. Smallholder farmers must be proactive and learn to adopt new strategies that can assist them in continuing farming with maximum use of limited agricultural resources and even wastes in agriculture. Several methods are available to improve the use of agricultural wastes, including non-agronomic benefits. Furthermore, we suggest the integration of waste resources, such as from both the trilogy of human– animal–crop wastes. Similarly, inexpensive techniques are encouraged among the farmers, including composting and vermicomposting of human–crop–animal wastes and/or slaughterhouse/abattoir wastes, biocharing of crop and animal wastes as various means of recycling/recovering nutrients in the soil system. Furthermore, the deployment of fungi could also improve the resource use efficiency through mushroom growth and sales, crop residue fermentation to enhance its feed value. Livestock farmers facing nutritional problems can apply microbes through fermentation to reduce antinutritional factors (lignin, tannins) in plants, and improve the safety of kitchen and dairy waste before feeding. Alternatively, farmers are encouraged to raise micro livestock (rabbits, snails, and grasscutters) on their farm to improve the use of resources. On a large scale, nitrogen and phosphorus recovery from cow urine, slurry, human feces, and fermentation of phytate rich plants with phytate on industrial scales is recommended. This chapter aims to provide insight into the methods by which farmers and industries, especially those in developing countries, can improve their available resources for agricuture and as livestock feeds

Changes of intracellular sodium and potassium ion concentrations in frog spinal motoneurons induced by repetitive synaptic stimulation

A post-tetanic membrane hyperpolarization following repetitive neuronal activity is a commonly observed phenomenon in the isolated frog spinal cord as well as in neurons of other nervous tissues. We have now used double-barrelled Na+- and K+-ion-sensitive microelectrodes to measure the intracellular Na+- and K+-concentrations and also the extracellular K+-concentration of lumbar spinal motoneurons during and after repetitive stimulation of a dorsal root. The results show that the posttetanic membrane hyperpolarization occurred at a time when the intracellular [Na+] reached its maximal value, intracellular [K+] had its lowest level and extracellular [K+] was still elevated. The hyperpolarization was blocked by ouabain and reduced by Li+. These data support the previous suggestion that an electrogenic Na+/K+ pump mode may be the mechanism underlying the post-tetanic membrane hyperpolarization

Effects of lithium on electrical activity and potassium ion distribution in the vertebrate central nervous system

Three different regions of the vertebrate central nervous system maintained in vitro (frog spinal cord, guinea pig olfactory cortex and hippocampus) have been used to investigate how Li+ influences membrane potential, membrane resistance, action potentials, synaptic potentials and the transmembrane K+-distribution of neurons and glial cells. In view of the therapeutic action of Li+ in manicdepressive disease, a special effort was made to determine the threshold concentration for the actions of Li+ on the parameters described above. It was observed that Li+ induced a membrane depolarization of both neurons and glial cells, a decrease of action potential amplitudes, a facilitation of monosynaptic excitatory postsynaptic potentials and a depression of polysynaptic reflexes. The membrane resistance of neurons was not altered. Li+ also induced an elevation of the free extracellular potassium concentration and a decrease of the free intracellular potassium concentration. Furthermore, in the presence of Li+ a slowing of the recovery of the membrane potential of neurons and glial cells, and of the extracellular potassium concentration after repetitive synaptic stimulation was observed. The threshold concentrations for the effects of Li+ were below 5 mmol/l in the frog spinal cord and below 2 mmol/l in the guinea pig olfactory cortex and hippocampus. The basic mechanism underlying the action of Li+ may be an interaction with the transport-function of the Na+/K+ pump