Energy storage sizing in pv generation systems using the conti-varlet method and disutility optimization

Abstract

Nowadays, the transition from conventional fossil fuel based and centralized energy generation to distributed renewables is increasing rapidly, due to the environmental concerns and political incentives. Wind and solar power generation offer carbon dioxide neutral electricity but also present some integration difficulties for energy system operators and planners due to intermittent power output. A promising way of dealing with the intermittency from renewables is energy storage. Many types of energy storage have been under development and study. Therefore, a battery energy storage system has been implemented mainly in residential applications to utility power grids. Battery energy storage can allow higher amounts of renewable electricity generation to be integrated by smoothening power output, and time shifting generated energy to follow demand and increase hosting capacities through peak shaving. Power quality related issues due to intermittency can be mitigated by controlling the storage’s charging patterns to respond to grid variables. For optimal utilization and maximum storage value, several applications should be within the operational repertoire of the storage unit. Other applications, including arbitrage, grid investment deferral, and load following, are discussed. This thesis proposes a study and analysis of the Conti-Varlet approach or stretchedthread method (STM) a powerful graphical based technique used to partial flow regularization for hydropower plants to provide auxiliary service regularization considering a battery energy storage system (BESS). The proposal is maintaining the power more stable and constant as possible, mitigating the PV intermittence. A one-year analysis is performed for each BESS size, ranging from 10% to 90%. A cost for each scenario and an optimal BESS is presented to reduce the disutility. The changing of the consumption costs is defined as disutility.