Abstract
The smart grid approach is envisioned to take advantage of all available modern technologies in transforming the current power system to provide benefits to all stakeholders in the fields of efficient energy utilisation and of wide integration of renewable sources. Energy storage systems could help to solve some issues that stem from renewable energy usage in terms of stabilizing the intermittent energy production, power quality and power peak mitigation. With the integration of energy storage systems into the smart grids, their accurate modeling becomes a necessity, in order to gain robust real-time control on the network, in terms of stability and energy supply forecasting. In this framework, this paper proposes a procedure to identify the values of the battery model parameters in order to best fit experimental data and integrate it, along with models of energy sources and electrical loads, in a complete framework which represents a real time smart grid management system. The proposed method is based on a hybrid optimisation technique, which makes combined use of a stochastic and a deterministic algorithm, with low computational burden and can therefore be repeated over time in order to account for parameter variations due to the battery’s age and usage.
Highlights
The Smart Grid was envisioned to take advantage of all available modern technologies so as to transform the current grid into a “smarter” grid
Some papers propose the identification of the parameter values of the battery model based on an optimisation algorithm
In [23], a method for the parameter extraction for the runtime-based circuit-oriented battery model is presented. It is based on a strategy of minimizing the RMS error between measured and equivalent-circuit-estimated battery terminal voltages; the estimated battery voltage is considered as a function of the battery circuit parameter
Summary
The Smart Grid was envisioned to take advantage of all available modern technologies so as to transform the current grid into a “smarter” grid. (ii) all types of energy storage and other resources such as plug-in electric vehicles (PEVs) to counter the variability of renewable resources and demand. Battery storage appears to be the most promising due to improvements in technology as well as its economy of scale. Most battery storage devices can respond in millisecond time scales. They can be valuable as enablers of fast controls in a Smart Grid. Storages of various sizes can be distributed throughout the grid, ranging from end-user customer premises to major substations and central power stations. This can alleviate congestion in terms of both transmission as well as distribution
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