Uncertainty analysis in the form of probabilistic forecasting can provide significant improvements in decision making processes in the smart power gird for better integrating renewable energies such as wind. Whereas point forecasting provides a single expected value, probabilistic forecasts provide more information in the form of quantiles, prediction intervals, or full predictive densities. This paper analyzes the effectiveness of an approach for nonparametric probabilistic forecasting of wind power that combines support vector machines and nonlinear quantile regression with non-crossing constraints. A numerical case study is conducted using publicly available wind data from the Global Energy Forecasting Competition 2014. Multiple quantiles are estimated to form 20%, 40%, 60% and 80% prediction intervals which are evaluated using the pinball loss function and reliability measures. Three benchmark models are used for comparison where results demonstrate the proposed approach leads to significantly better performance while preventing the problem of overlapping quantile estimates.

Demand-side management (DSM) in the smart grid allows customers to make autonomous decisions on their energy consumption, helping energy providers to reduce the peaks in load demand. The automated scheduling of smart devices in residential and commercial buildings plays a key role in DSM. Due to data privacy and user autonomy, such an approach is best implemented through distributed multi-agent systems. This paper makes the following contributions: (i) It introduces the Smart Home Device Scheduling (SHDS) problem, which formalizes the device scheduling and coordination problem across multiple smart homes as a multi-agent system; (ii) It describes a mapping of this problem to a distributed constraint optimization problem; (iii) It proposes a distributed algorithm for the SHDS problem; and (iv) It presents empirical results from a physically distributed system of Raspberry Pis, each capable of controlling smart devices through hardware interfaces.

One of the key information pieces in improving energy efficiency of buildings is the appliance level breakdown of energy consumption. Energy disaggregation is the process of obtaining this breakdown from a building level aggregate data using computational techniques. Most of the current research focuses on residential buildings, obtaining this information from a single smart meter and often relying on high frequency data. This work is directed at commercial buildings equipped with building management and automation systems providing low frequency operational and contextual data. This paper presents a machine learning method to disaggregate energy consumption of the building using this operational data as input features. Experimental results on two publicly available datasets demonstrate the effectiveness of the approach, which surpasses existing methods. For all but one appliance of House 2 of the publicly available REDD dataset, improvements in normalized error in assigned power range between 20% (Lighting) and 220% (Stove). For another dataset from an educational facility in Singapore, disaggregation accuracy of 92% is reported for the facility's cooling system.

Technology has shaped human development since the dawn of time, from cave drawings that allowed stories to be recorded, to combustion engines bringing people closer. The World Economic Forum's Professor Klaus Schwab summed it up this way: "The first Industrial Revolution used steam power to mechanise production. The second used electric power to create mass production. The third used electronics and information technology to automate production. Now a fourth Industrial Revolution is building on the Third. It is characterised by a fusion of technologies that is blurring the lines between the physical, digital and biological spheres."

A recent Conversation piece pointed out that the British electricity mix in 2016 was the cleanest in 60 years, with record capacity from renewable energy, mainly from wind and solar power. But one problem with this great expansion in renewables is they are intermittent, meaning they depend on weather conditions such as the wind blowing or sun shining. Unlike conventional power, this means they can't necessarily meet surges in demand. National Grid, the UK grid operator, has several ways of ensuring supply can always meet demand. For shorter gaps in generation, it asks electricity suppliers to run their conventional power stations at below maximum potential output and ramp up as needed.

The radiation level in the containment vessel of reactor 2 at the crippled Fukushima No. 1 power plant has reached a maximum of 530 sieverts per hour, the highest since the triple core meltdown in March 2011, Tokyo Electric Power Co. Holdings Inc. said. Tepco said on Thursday that the blazing radiation reading was taken near the entrance to the space just below the pressure vessel, which contains the reactor core. The high figure indicates that some of the melted fuel that escaped the pressure vessel is nearby. At 530 sieverts, a person could die from even brief exposure, highlighting the difficulties ahead as the government and Tepco grope their way toward dismantling all three reactors crippled by the March 2011 disaster. Tepco also announced that, based on its analysis of images taken by a remote-controlled camera, that there is a 2-meter hole in the metal grating under the pressure vessel in the reactor's primary containment vessel.

Former ExxonMobil Corp. Chief Executive Rex Tillerson was sworn in only Wednesday, and already Congress is moving to benefit the new secretary of state's former--and only--place of work by shredding two major oil industry regulations. Early Friday morning, the Republican-led Senate voted 52 to 47 on a House resolution scrapping a Securities and Exchange Commission rule requiring companies like Exxon and Chevron Corp. to disclose payments they make to foreign governments for the ability to extract oil, minerals and natural gas from their territory. Known as the "extraction rule," it was meant to curb corruption and boost transparency within the oil industry. Standing before the upper house Thursday night, Sen. Elizabeth Warren of Massachusetts railed against the effort to discard the rule. "One of the Republican Party's first orders of business is a giveaway to ExxonMobil that will help corrupt and repressive foreign regimes and make it easy to funnel money to terrorists around the world," she said, adding that companies like Exxon "regularly pay millions" to "corrupt officials" for the rights to drill on their land, and highlighting the "years" necessary to garner bipartisan and even investor support for the law's passage.

Radiation levels inside the damaged Fukushima nuclear reactor are over 100 times fatal levels, the highest they've been since the triple meltdown in March, 2011, according to operator Tepco. The company recently sent a camera-equipped robot into the reactor, which relayed images showing a meter-wide hole in the pressure vessel (above), with possible melted uranium fuel on a grating below. "It may have ... melted and made a hole in the [containment] vessel, but it is only a hypothesis at this stage," a company spokesperson told the AFP. Since the accident, the highest recorded level in the plant was around 73 sieverts per hour, but a new reading, estimated from a camera that was sent in on Monday, shows an "unimaginable" 530 sieverts per hour, according to an expert. A dose of one sievert can cause radiation sickness, while 10 sieverts would kill you in a few weeks.

Radiation levels inside a stricken reactor at Japan's Fukushima nuclear plant have hit a record high. Levels are now so high that they could kill off robots sent in to probe the reactors. The development casts doubt over how the disaster-hit facility will be safely dismantled in the future. Radiation levels inside a stricken reactor at Japan's Fukushima nuclear plant have hit a record high. Levels are so high that they could kill off robots sent in to probe the reactors.

CalTech and university of Illinois Urbana-Champaign researchers have created a robot that mimics bat flight. Bat wings have intrigued scientists for centuries. And now, engineers have created "Bat Bot," a small aircraft that mimics the flight patterns of the small, rodent-like flyers. Bat Bot exposes the complicated mechanics of bat flight and simultaneously provides clues into how to make better aerial drones. Bat Bot is a remix on an ornithopter, a machine that uses flapping wings to take flight as opposed a propeller or a balloon.