Domestic demand-side management: Analysis of microgrid with renewable energy sources using historical load data
Hecht, Christian, Sprake, David, Vagapov, Yuriy and Anuchin, Alecksey (2021) Domestic demand-side management: Analysis of microgrid with renewable energy sources using historical load data. Electrical Engineering. ISSN 1432-0487
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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 15 UK households with appropriate allocation of washing machines, tumble dryers and dishwashers in accordance with 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 is 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 in 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.
| Item Type: | Article |
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| Keywords: | Microgrid, Renewable energy, Demand-side management, Load shifting |
| Divisions: | Applied Science, Computing and Engineering |
| Depositing User: | Hayley Dennis |
| Date Deposited: | 25 Jan 2021 13:57 |
| Last Modified: | 10 Jan 2022 04:10 |
| URI: | https://glyndwr.repository.guildhe.ac.uk/id/eprint/17714 |
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