Energy transitionAn energy transition (or energy system transformation) is a significant structural change in an energy system regarding supply and consumption. Currently, a transition to sustainable energy (mostly renewable energy) is underway to limit climate change. It is also called renewable energy transition. The current transition is driven by a recognition that global greenhouse-gas emissions must be drastically reduced. This process involves phasing-down fossil fuels and re-developing whole systems to operate on low carbon electricity.
Low-carbon powerLow-carbon power is electricity produced with substantially lower greenhouse gas emissions than conventional fossil fuel power generation. The energy transition to low-carbon power is one of the most important actions required to limit climate change. Power sector emissions may have peaked in 2018. During the first six months of 2020, scientists observed an 8.8% decrease in global CO2 emissions relative to 2019 due to COVID-19 lockdown measures. The two main sources of the decrease in emissions included ground transportation (40%) and the power sector (22%).
Nuclear energy policyNuclear energy policy is a national and international policy concerning some or all aspects of nuclear energy and the nuclear fuel cycle, such as uranium mining, ore concentration, conversion, enrichment for nuclear fuel, generating electricity by nuclear power, storing and reprocessing spent nuclear fuel, and disposal of radioactive waste. Nuclear energy policies often include the regulation of energy use and standards relating to the nuclear fuel cycle.
Electricity marketIn a broad sense, an electricity market is a system that facilitates the exchange of electricity-related goods and services. During more than a century of evolution of the electric power industry, the economics of the electricity markets had undergone enormous changes for reasons ranging from the technological advances on supply and demand sides to politics and ideology.
Electricity generationElectricity generation is the process of generating electric power from sources of primary energy. For utilities in the electric power industry, it is the stage prior to its delivery (transmission, distribution, etc.) to end users or its storage (using, for example, the pumped-storage method). Usable electricity is not freely available in nature, so it must be "produced" (that is, transforming other forms of energy to electricity). Production is carried out in power stations (also called "power plants").
Electric power distributionElectric power distribution is the final stage in the delivery of electricity. Electricity is carried from the transmission system to individual consumers. Distribution substations connect to the transmission system and lower the transmission voltage to medium voltage ranging between 2kV and 33kV with the use of transformers. Primary distribution lines carry this medium voltage power to distribution transformers located near the customer's premises.
Nuclear powerNuclear power is the use of nuclear reactions to produce electricity. Nuclear power can be obtained from nuclear fission, nuclear decay and nuclear fusion reactions. Presently, the vast majority of electricity from nuclear power is produced by nuclear fission of uranium and plutonium in nuclear power plants. Nuclear decay processes are used in niche applications such as radioisotope thermoelectric generators in some space probes such as Voyager 2. Generating electricity from fusion power remains the focus of international research.
Nuclear power debateThe nuclear power debate is a long-running controversy about the risks and benefits of using nuclear reactors to generate electricity for civilian purposes. The debate about nuclear power peaked during the 1970s and 1980s, as more and more reactors were built and came online, and "reached an intensity unprecedented in the history of technology controversies" in some countries. In the 2010s, with growing public awareness about climate change and the critical role that carbon dioxide and methane emissions plays in causing the heating of the earth's atmosphere, there was a resurgence in the intensity of the nuclear power debate.
Nuclear binding energyNuclear binding energy in experimental physics is the minimum energy that is required to disassemble the nucleus of an atom into its constituent protons and neutrons, known collectively as nucleons. The binding energy for stable nuclei is always a positive number, as the nucleus must gain energy for the nucleons to move apart from each other. Nucleons are attracted to each other by the strong nuclear force. In theoretical nuclear physics, the nuclear binding energy is considered a negative number.
Energy industryThe energy industry is the totality of all of the industries involved in the production and sale of energy, including fuel extraction, manufacturing, refining and distribution. Modern society consumes large amounts of fuel, and the energy industry is a crucial part of the infrastructure and maintenance of society in almost all countries.
SwitzerlandSwitzerland, officially the Swiss Confederation, is a landlocked country located at the confluence of Western, Central and Southern Europe. It is bordered by Italy to the south, France to the west, Germany to the north and Austria and Liechtenstein to the east. Switzerland is geographically divided among the Swiss Plateau, the Alps and the Jura; the Alps occupy the greater part of the territory, whereas most of the country's population of 8.7 million are concentrated on the plateau, which hosts the largest cities and economic centres, including Zürich, Geneva and Basel.
Normal distributionIn statistics, a normal distribution or Gaussian distribution is a type of continuous probability distribution for a real-valued random variable. The general form of its probability density function is The parameter is the mean or expectation of the distribution (and also its median and mode), while the parameter is its standard deviation. The variance of the distribution is . A random variable with a Gaussian distribution is said to be normally distributed, and is called a normal deviate.
Gamma distributionIn probability theory and statistics, the gamma distribution is a two-parameter family of continuous probability distributions. The exponential distribution, Erlang distribution, and chi-squared distribution are special cases of the gamma distribution. There are two equivalent parameterizations in common use: With a shape parameter and a scale parameter . With a shape parameter and an inverse scale parameter , called a rate parameter. In each of these forms, both parameters are positive real numbers.
Beta distributionIn probability theory and statistics, the beta distribution is a family of continuous probability distributions defined on the interval [0, 1] or (0, 1) in terms of two positive parameters, denoted by alpha (α) and beta (β), that appear as exponents of the variable and its complement to 1, respectively, and control the shape of the distribution. The beta distribution has been applied to model the behavior of random variables limited to intervals of finite length in a wide variety of disciplines.
Exponential distributionIn probability theory and statistics, the exponential distribution or negative exponential distribution is the probability distribution of the time between events in a Poisson point process, i.e., a process in which events occur continuously and independently at a constant average rate. It is a particular case of the gamma distribution. It is the continuous analogue of the geometric distribution, and it has the key property of being memoryless. In addition to being used for the analysis of Poisson point processes it is found in various other contexts.
Probability distributionIn probability theory and statistics, a probability distribution is the mathematical function that gives the probabilities of occurrence of different possible outcomes for an experiment. It is a mathematical description of a random phenomenon in terms of its sample space and the probabilities of events (subsets of the sample space). For instance, if X is used to denote the outcome of a coin toss ("the experiment"), then the probability distribution of X would take the value 0.5 (1 in 2 or 1/2) for X = heads, and 0.
Binomial distributionIn probability theory and statistics, the binomial distribution with parameters n and p is the discrete probability distribution of the number of successes in a sequence of n independent experiments, each asking a yes–no question, and each with its own Boolean-valued outcome: success (with probability p) or failure (with probability ). A single success/failure experiment is also called a Bernoulli trial or Bernoulli experiment, and a sequence of outcomes is called a Bernoulli process; for a single trial, i.
Production (economics)Production is the process of combining various inputs, both material (such as metal, wood, glass, or plastics) and immaterial (such as plans, or knowledge) in order to create output. Ideally this output will be a good or service which has value and contributes to the utility of individuals. The area of economics that focuses on production is called production theory, and it is closely related to the consumption (or consumer) theory of economics. The production process and output directly result from productively utilising the original inputs (or factors of production).
Factors of productionIn economics, factors of production, resources, or inputs are what is used in the production process to produce output—that is, goods and services. The utilized amounts of the various inputs determine the quantity of output according to the relationship called the production function. There are four basic resources or factors of production: land, labour, capital and entrepreneur (or enterprise). The factors are also frequently labeled "producer goods or services" to distinguish them from the goods or services purchased by consumers, which are frequently labeled "consumer goods".
Poisson distributionIn probability theory and statistics, the Poisson distribution is a discrete probability distribution that expresses the probability of a given number of events occurring in a fixed interval of time or space if these events occur with a known constant mean rate and independently of the time since the last event. It is named after French mathematician Siméon Denis Poisson ('pwɑːsɒn; pwasɔ̃). The Poisson distribution can also be used for the number of events in other specified interval types such as distance, area, or volume.
