A stochastic modelling and simulation approach to heating and cooling electricity consumption in the residential sector

• Published in: Energy (Oxford) Vol. 144; pp. 1080 - 1091
• Main Authors: Palacios-Garcia, E.J., Moreno-Munoz, A., Santiago, I., Flores-Arias, J.M., Bellido-Outeirino, F.J., Moreno-Garcia, I.M.
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.02.2018; Elsevier BV
• Subjects: Computer simulation; Cooling; Cooling consumption; Electric appliances; Electric power demand; Electricity; Electricity consumption; Heating; Heating consumption; Household appliances; Households; Occupancy; Power supply; Residential areas; Residential electricity demand; Residential energy; Simulation; Smart grid; Stochastic models; Stochasticity; Temporal resolution; Europe; Residential electricity demand; Stochastic models; Heating consumption; Smart grid; Cooling consumption; Occupancy
• ISSN: 0360-5442; 1873-6785
• DOI: 10.1016/j.energy.2017.12.082

Heating and cooling consumption is one of the most significant terms in the total supply, which may come to represent half of the total demand in European countries. These appliances are supplied by a wide range of sources, being electrical devices of special interest in the Smart Grid. Current tools allow the assessment of the consumption with a high accuracy, nevertheless, they lack the temporal resolution or low-level details to study advanced control techniques. In this context, bottom-up stochastic models are a main tool to simulate high-resolution demand profiles. This paper presents a 1-min resolution model for electricity demand of heating and cooling appliances. The system is based on the simulation of individual households considering variables such as the number of residents, location, type of day (weekday or weekend) and date. It was used to simulate daily profiles which showed two main demand peaks, one during mornings and another during dinner time, for heating, and a high demand during midday for cooling consumption. Moreover, annual simulations depicted the importance of cooling appliances, which despite having a lower annual demand, can overcharge the grid with their concurrent utilisation, highlighting the usefulness of this tool for studying the impact of these devices.