Ocean thermal energy conversionOcean Thermal Energy Conversion (OTEC) uses the ocean thermal gradient between cooler deep and warmer shallow or surface seawaters to run a heat engine and produce useful work, usually in the form of electricity. OTEC can operate with a very high capacity factor and so can operate in base load mode. The denser cold water masses, formed by ocean surface water interaction with cold atmosphere in quite specific areas of the North Atlantic and the Southern Ocean, sink into the deep sea basins and spread in entire deep ocean by the thermohaline circulation.
Electric carAn electric car or electric vehicle (EV) is an automobile that is propelled by one or more electric traction motors, using only energy stored in batteries. Compared to conventional internal combustion engine (ICE) vehicles, electric cars are quieter, more responsive, have superior energy conversion efficiency and no exhaust emissions and lower overall vehicle emissions (however the power plant supplying the electricity might generate its own emissions).
Distributed generationDistributed generation, also distributed energy, on-site generation (OSG), or district/decentralized energy, is electrical generation and storage performed by a variety of small, grid-connected or distribution system-connected devices referred to as distributed energy resources (DER). Conventional power stations, such as coal-fired, gas, and nuclear powered plants, as well as hydroelectric dams and large-scale solar power stations, are centralized and often require electric energy to be transmitted over long distances.
Cadmium telluride photovoltaicsCadmium telluride (CdTe) photovoltaics is a photovoltaic (PV) technology based on the use of cadmium telluride in a thin semiconductor layer designed to absorb and convert sunlight into electricity. Cadmium telluride PV is the only thin film technology with lower costs than conventional solar cells made of crystalline silicon in multi-kilowatt systems. On a lifecycle basis, CdTe PV has the smallest carbon footprint, lowest water use and shortest energy payback time of any current photovoltaic technology.
Energy policyEnergy policy is the manner in which a given entity (often governmental) has decided to address issues of energy development including energy conversion, distribution and use as well as reduction of greenhouse gas emissions in order to contribute to climate change mitigation. The attributes of energy policy may include legislation, international treaties, incentives to investment, guidelines for energy conservation, taxation and other public policy techniques. Energy is a core component of modern economies.
Survey methodologySurvey methodology is "the study of survey methods". As a field of applied statistics concentrating on human-research surveys, survey methodology studies the sampling of individual units from a population and associated techniques of survey data collection, such as questionnaire construction and methods for improving the number and accuracy of responses to surveys. Survey methodology targets instruments or procedures that ask one or more questions that may or may not be answered.
Bayesian networkA Bayesian network (also known as a Bayes network, Bayes net, belief network, or decision network) is a probabilistic graphical model that represents a set of variables and their conditional dependencies via a directed acyclic graph (DAG). It is one of several forms of causal notation. Bayesian networks are ideal for taking an event that occurred and predicting the likelihood that any one of several possible known causes was the contributing factor. For example, a Bayesian network could represent the probabilistic relationships between diseases and symptoms.
Feature learningIn machine learning, feature learning or representation learning is a set of techniques that allows a system to automatically discover the representations needed for feature detection or classification from raw data. This replaces manual feature engineering and allows a machine to both learn the features and use them to perform a specific task. Feature learning is motivated by the fact that machine learning tasks such as classification often require input that is mathematically and computationally convenient to process.
EnergiewendeThe Energiewende (ʔɛnɐˈɡiːˌvɛndə) is the ongoing transition by Germany to a low carbon, environmentally sound, reliable, and affordable energy supply. The new system intends to rely heavily on renewable energy (particularly wind, photovoltaics, and hydroelectricity), energy efficiency, and energy demand management. The last nuclear power plants were shut down in 2023; all existing coal-fired generation will be retired by 2038.
Soft energy pathIn 1976, energy policy analyst Amory Lovins coined the term soft energy path to describe an alternative future where energy efficiency and appropriate renewable energy sources steadily replace a centralized energy system based on fossil and nuclear fuels. Amory Lovins came to prominence in 1976 when he published an article in Foreign Affairs called "Energy Strategy: The Road Not Taken?". Lovins argued that the United States had arrived at an important crossroads and could take one of two paths.
Reinforcement learningReinforcement learning (RL) is an area of machine learning concerned with how intelligent agents ought to take actions in an environment in order to maximize the notion of cumulative reward. Reinforcement learning is one of three basic machine learning paradigms, alongside supervised learning and unsupervised learning. Reinforcement learning differs from supervised learning in not needing labelled input/output pairs to be presented, and in not needing sub-optimal actions to be explicitly corrected.
Machine learningMachine learning (ML) is an umbrella term for solving problems for which development of algorithms by human programmers would be cost-prohibitive, and instead the problems are solved by helping machines 'discover' their 'own' algorithms, without needing to be explicitly told what to do by any human-developed algorithms. Recently, generative artificial neural networks have been able to surpass results of many previous approaches.
