access icon free Stochastic approach to represent distributed energy resources in the form of a virtual power plant in energy and reserve markets

Today, traditional networks are changing to active grids due to the burgeoning growth of distributed energy resources (DER), which demands scrupulous attention to technical infrastructures, as well as economic aspects. In this study, from economic point of view, the aggregation of DERs in a distribution network to participate in joint energy and reserve markets is investigated. This approach, which is predicated upon price-based unit commitment method, has considered virtually all the technical data in the proposed model. It is worth to mention that uncertainties of loads and market prices, as an inherent characteristic of the electricity markets, are treated in this study, and their effect on the operation of virtual power plants in energy and reserve markets has been thoroughly discussed. To this end, for both uncertain parameters, a good number of scenarios are generated and using the backward reduction method the number of these scenarios is reduced. The problem is formulated as a MINLP model and is implemented in GAMS software, while its authenticity is validated using particle swarm optimisation method.

Inspec keywords: power generation scheduling; uncertain systems; power markets; load (electric); particle swarm optimisation; distributed power generation; stochastic processes; power generation economics; power engineering computing; nonlinear programming; integer programming; power distribution economics

Other keywords: distribution network; technical infrastructures; GAMS software; DER; distributed energy resources; reserve markets; uncertain parameters; virtual power plant; particle swarm optimisation method; load uncertainties; MINLP model; price-based unit commitment method; backward reduction method; economic aspects; stochastic approach; electricity markets; active grids; market prices; energy markets

Subjects: Optimisation techniques; Power system management, operation and economics; Distribution networks; Other topics in statistics; Distributed power generation; Optimisation techniques; Other topics in statistics; Power engineering computing

http://iet.metastore.ingenta.com/content/journals/10.1049/iet-gtd.2015.0715
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