Domestic demand-side management: analysis of microgrid with renewable energy sources using historical load data

Abstract

This paper provides a high accuracy assessment of domestic demand-side management (DSM) approach in the context of distributed renewable energy sources (RES). To determine the potential of domestic DSM for households, a microgrid model of a typical UK residential estate was developed to simulate the impact of RES. The microgrid model comprises of 15 UK households with appropriate allocation of washing machines (WM), tumble dryers (TD) and dishwashers (DW) in accordance to the statistical data. In order to obtain a high accuracy result, the power consumption of the microgrid model utilises real historical high-resolution data of household energy consumption and RES generation. Thereafter, 40% of distributed wind and solar energy are implemented in the model to produce two individual scenarios. The operation of the white appliances in the model is controlled using a domestic DSM based on a load shifting algorithm. The primary criterion of the DSM considered in this paper is the reduction of energy feedback to the grid in order to decrease the utilisation of the grid and to reduce the transmission losses. The results obtained from the model simulation are compared to the baseline model and discussed with respect to the possible benefits of implementation of domestic DSM under the impact of RES. It has been shown that the self-consumption ratio of the microgrid operating under the DSM is increased by 3% for both scenarios. The model analysis provides highly realistic results which can be used for efficiency assessment of various load shifting methods.

Tuning of renewable energy bids based on energy risk management: Enhanced microgrids with pareto‐optimal profits for the utility and prosumers

“…Equation (1) estimates the profit of the utility, which combines the cost of procuring energy from discharging EVs, solar, wind, microturbine, upstream grid, as well as the revenue earned from charging EVs and load demand tariff. The profit of the prosumers is given by Equation (2), which is equivalent to the difference between the revenue earned at the set bid price for solar, wind, and EV discharging, and the levelized cost of energy (LCOE) [31] for solar, wind, and EV charging.…”

“…Microgrids are expected to be reliable, controllable, clean and economical for the distribution of energy in local areas [1,2]. Energy risk management plays a key role in the operation of microgrids, as it is responsible for enabling the system to adapt to the uncertainties expected from various microsources and loads [3,4].…”

Modeling and Simulation of Household Appliances Power Consumption

“…In [16], several regression models were established to analyze the determinants of end-use energy consumption. Further, in [17], a microgrid model was used to estimate the consumption of washing machines, dishwashers and dryers. Moreover, in [18], a model for detecting the behavior of building occupants was developed to estimate building consumption.…”