Quantifying flexibility of commercial and residential loads for demand response using setpoint changes

Abstract

This paper presents a novel demand response estimation framework for residential and commercial buildings using a combination of EnergyPlus and two-state models for thermostatically controlled loads. Specifically, EnergyPlus models for commercial and multi-dwelling residential units are applied to construct exhaustive datasets (i.e., with more than 300M data points) that capture the detailed load response and complex thermodynamics of several building types. Subsequently, regression models are fit to each dataset to predict DR potential based on key inputs, including hour of day, set point change and outside air temperature. For single residential units, and residential thermostatically controlled loads (i.e. water heaters and refrigerators) a two-state model from the literature is applied. The proposed framework is then validated for commercial buildings through a comparison with a dataset composed of 11 buildings during 12 demand response events. In addition, the use of the proposed simplified DR estimation framework is presented in terms of two cases (1) peak load shed prediction in an individual building and (2) aggregated DR up/down capacity from a large-scale group of different buildings.

A Decentralized Local Flexibility Market Considering the Uncertainty of Demand

“…Other types of industrial factories, such as mechanical wood pulp production and paper machines, are considered shiftable loads. In the tertiary sector, the potential of demand flexibility comes from large-scale commercial loads relying on cooling and heating of water and ventilation [54]. The advantages of such loads are that they constitute a huge portion of the total load of the commercial site and they are mostly controlled with energy management systems, which makes it easier to implement flexibility control actions [55].…”

Harnessing the Flexibility of Thermostatic Loads in Microgrids with Solar Power Generation

“…Although the DR potential is based on arbitrary testing of different temperature setpoints within a certain comfort range and therefore no optimal temperature settings are achieved, this approach is very useful when dealing with large aggregations (in the order of thousands) of homogeneous buildings, but is not applicable in the business-park microgrid domain due to the heterogeneous nature of the buildings located in these types of areas. Another shortcoming of the DR potential assessment in works such as [53,54] is that, although their modeling approaches are very thorough, their DR quantification methods are based on load response scenarios that are neither dynamic nor optimal.…”

“…Bottom-up physical modeling approaches used to determine DR potential from loads' physical constraints are documented in [53]. The authors of [53] use physical models of household appliances to create aggregate profiles of prototypical residential dwellings, which they use, in conjunction with ambient temperature values, to train piecewise linear regression models to represent DR potential as a function of ambient temperature.…”

“…The authors of [53] use physical models of household appliances to create aggregate profiles of prototypical residential dwellings, which they use, in conjunction with ambient temperature values, to train piecewise linear regression models to represent DR potential as a function of ambient temperature. Although the DR potential is based on arbitrary testing of different temperature setpoints within a certain comfort range and therefore no optimal temperature settings are achieved, this approach is very useful when dealing with large aggregations (in the order of thousands) of homogeneous buildings, but is not applicable in the business-park microgrid domain due to the heterogeneous nature of the buildings located in these types of areas.…”

Demand side management in refrigeration applications

“…the floor heating or TABs (thermally activated buildings) [11]: the floor is a large low temperature radiating surface while the concrete acts like a thermal storage heated by air, water or directly by electric resistances. The passive thermal storage due to the building envelope can be easily exploited by means of variable temperature set points, that can be adjusted in a certain range in order to keep the internal comfort and at the same time provide useful flexibility to the power system [12]. Moreover, PCM can be integrated within the building components and used passively, for precooling/heating and for reducing the thermal load request, or alternatively actively by charging and discharging them on the basis of a given strategy.…”