Abstract
Thermostatically controlled loads (TCLs) can effectively support network operation through their intrinsic flexibility and play a pivotal role in delivering cost effective decarbonization. This paper proposes a scalable distributed solution for the operation of large populations of TCLs providing frequency response and performing energy arbitrage. Each TCL is described as a price-responsive rational agent that participates in an integrated energy/frequency response market and schedules its operation in order to minimize its energy costs and maximize the revenues from frequency response provision. A mean field game formulation is used to implement a compact description of the interactions between typical power system characteristics and TCLs flexibility properties. In order to accommodate the heterogeneity of the thermostatic loads into the mean field equations, the whole population of TCLs is clustered into smaller subsets of devices with similar properties, using k-means clustering techniques. This framework is applied to a multi-area power system to study the impact of network congestions and of spatial variation of flexible resources in grids with large penetration of renewable generation sources. Numerical simulations on relevant case studies allow to explicitly quantify the effect of these factors on the value of TCLs flexibility and on the overall efficiency of the power system.
Highlights
The costs of replacing ever larger shares of conventional generation in favor of renewable energy sources are expected to grow if conventional technologies will remain the only source of flexibility [1,2]
The proposed distributed coordination strategy (DCS) was applied to the Base Case (BC), considering the two-area unit commitment (UC) problem in Section 2 and the mean field game formulation in Section 3, where all thermostatically controlled loads (TCLs) are characterized by the same parameters
Results refer to the scenario with C = 8 and show percentage variations compared to the same results obtained in DCS BC, i.e., with C = 1
Summary
The costs of replacing ever larger shares of conventional generation in favor of renewable energy sources are expected to grow if conventional technologies will remain the only source of flexibility [1,2]. Thermostatically controlled loads (TCLs), encompassing refrigerators, air conditioners, heat pumps, represent a promising option to enhance system flexibility (e.g., [5,6,7]). In their standard configuration, these devices are controlled by means of a hysteresis controller with a temperature deadband; relatively small alterations to the regular power consumption pattern can be tolerated, as long as the target temperature is approximately maintained over time. The relevant literature proposes a number of fundamentally different approaches to control the TCL consumption and exploit their intrinsic flexibility to provide ancillary services. Based on the received price signals, the TCL computes its own strategy to minimize the associated operational cost whilst enforcing temperature constraints to preserve their primary cooling/heating function
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