Frequency Regulation in Smart Microgrids Based on Load Estimation
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Frequency Regulation in Smart Microgrids Based on Load Estimation Alexander Stotsky1 Received: 6 December 2017 / Revised: 26 February 2018 / Accepted: 18 April 2018 © Brazilian Society for Automatics–SBA 2018
Abstract The desired frequency is maintained in Smart Microgrid (SMG) when the generated power matches the grid load. Variability of wind power and fluctuations of the load are the main obstacles for performance improvement of frequency regulation in SMG. Active Power Control (APC) services provided by wind power generators is one of the main sources for performance improvement in frequency regulation. New coordinated APC architecture, which involves simultaneous speed and pitch control actions delivers desired power to the grid despite significant variations of the wind power. A tool-kit with discretetime input estimation algorithms, which estimate input quantity using output measurements is presented. Unmeasurable load fluctuations are estimated with input estimation method using measurements of grid frequency deviation. Desired power for APC is driven by estimated and a priori known loads. This observer-based control method reduces the risk of overshoots and oscillations in frequency regulation loop compared to PID controllers driven directly by the frequency deviation. The stability of the closed loop frequency control system is proved, and simulation results show that observer-based control architecture provides significant improvement of the frequency regulation in SMG. Keywords Smart microgrids · Frequency control · Active power control · Coordinated speed and pitch control of wind turbine · Grid load estimation · Input estimation algorithms
1 Introduction Traditional load frequency control concepts, which are suitable for large centralized power generation, are not suitable for power systems with small decentralized renewable generation units in microgrids due to the lack of large inertias. Frequency control challenges can be addressed within the concept of future Smart Microgrid (SMG), which is a smallscale version of the centralized electricity system (Farhangi 2010). SMG includes interconnection of power generators such as wind turbines, PV units and others; storage devices such as energy capacitors, batteries and others; loads (both uncontrollable and controllable); communication channels and control units, see Fig. 1 for benchmark SMG architecture. SMG has a number of benefits: (a) power is generated and consumed locally (for islanded operation), and transmission losses are reduced; (b) daily load profiles are usually well known for microgrids and can be used as a priory infor-
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Alexander Stotsky [email protected]
mation for frequency control systems; (c) information from smart sensors (which measure frequency deviations, power disturbances and other quantities) transmitted via local communication system with minimal delay can also be used for active control of power generators; (c) and many others. Variability and uncertainty associated with (a) renewable energy sources, such as
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