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Introduction and Terminology
Residual load is an indicator in a power system. It shows how much capacity is left for conventional power plants to operate.
Traditionally, when variable renewable energy sources are small in scale comparing to the demand load, conventional power plants vary their power output in accordance with the demand load curve. As the capacity of VRE grows, its power output begins to affect the load balance of the power system. A new indicator is needed to describe the situation, giving birth to this terminology. The first use of the term "residual load" probably had come from a 2009 German study from Fraunhofer. It used the German term "residuale Last".
The definition of the terminology, however, still varies among different literature. A common definition for residual load is "what is left after substracting those generators who have to produce electricity ('must run') and those that generate with (almost) no marginal costs (variable renewables like wind, solar and hydro)". However, the "must run" capacity (or more formally, the "minimum compliant load") in this definition is controversial; must run capacity exists only if operators are not allowed to shut down inflexible conventional power plants, and the fewer inflexible conventional power plants are online, the less must run capacity would be in the system. Therefore, some sources simply define residual load (or residual demand) as demand load minus renewable power output.
Effects of High VRE Penentration to Residual Load
Applications in Power Systems Analysis
- ↑ Dynamische Simulation der
Stromversorgung in Deutschland nach dem Ausbauszenario der Erneuerbaren-Energien-Branche, https://www.bee-ev.de/fileadmin/Publikationen/Studien/100119_BEE_IWES-Simulation_Stromversorgung2020_Endbericht.pdf
- ↑ Energy transition vocabulary: residual load, https://goo.gl/ac5avj
- ↑ Review of the operational flexibility and emissions of gas- and coal-fired power plants in a future with growing renewables, Miguel Angel Gonzalez-Salazar et al., 2018
- ↑ Demand and residual demand modelling using quantile regression, Linh Phuong Catherine Do et al., 2016