Genetic algorithmIn computer science and operations research, a genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA). Genetic algorithms are commonly used to generate high-quality solutions to optimization and search problems by relying on biologically inspired operators such as mutation, crossover and selection. Some examples of GA applications include optimizing decision trees for better performance, solving sudoku puzzles, hyperparameter optimization, causal inference, etc.
Small hydroSmall hydro is the development of hydroelectric power on a scale suitable for local community and industry, or to contribute to distributed generation in a regional electricity grid. Exact definitions vary, but a "small hydro" project is less than 50 megawatts (MW), and can be further subdivide by scale into "mini" (
Small wind turbineSmall wind turbines, also known as micro wind turbines, generate electricity for small-scale use. These turbines are typically smaller than those found in wind farms. Small wind turbines often have passive yaw systems as opposed to active ones. They use a direct drive generator and use a tail fin to point into the wind, whereas larger turbines have geared powertrains that are actively pointed into the wind. They usually produce between 500 W and 10 kW, with some as small as 50 W.
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").
Unconventional wind turbinesUnconventional wind turbines are those that differ significantly from the most common types in use. the most common type of wind turbine is the three-bladed upwind horizontal-axis wind turbine (HAWT), where the turbine rotor is at the front of the nacelle and facing the wind upstream of its supporting turbine tower. A second major unit type is the vertical-axis wind turbine (VAWT), with blades extending upwards, supported by a rotating framework.
HydroelectricityHydroelectricity, or hydroelectric power, is electricity generated from hydropower (water power). Hydropower supplies one sixth of the world's electricity, almost 4500 TWh in 2020, which is more than all other renewable sources combined and also more than nuclear power. Hydropower can provide large amounts of low-carbon electricity on demand, making it a key element for creating secure and clean electricity supply systems.
Multi-objective optimizationMulti-objective optimization or Pareto optimization (also known as multi-objective programming, vector optimization, multicriteria optimization, or multiattribute optimization) is an area of multiple-criteria decision making that is concerned with mathematical optimization problems involving more than one objective function to be optimized simultaneously. Multi-objective is a type of vector optimization that has been applied in many fields of science, including engineering, economics and logistics where optimal decisions need to be taken in the presence of trade-offs between two or more conflicting objectives.
Combinatorial optimizationCombinatorial optimization is a subfield of mathematical optimization that consists of finding an optimal object from a finite set of objects, where the set of feasible solutions is discrete or can be reduced to a discrete set. Typical combinatorial optimization problems are the travelling salesman problem ("TSP"), the minimum spanning tree problem ("MST"), and the knapsack problem. In many such problems, such as the ones previously mentioned, exhaustive search is not tractable, and so specialized algorithms that quickly rule out large parts of the search space or approximation algorithms must be resorted to instead.
Hill climbingIn numerical analysis, hill climbing is a mathematical optimization technique which belongs to the family of local search. It is an iterative algorithm that starts with an arbitrary solution to a problem, then attempts to find a better solution by making an incremental change to the solution. If the change produces a better solution, another incremental change is made to the new solution, and so on until no further improvements can be found. For example, hill climbing can be applied to the travelling salesman problem.