| Title |
Internet-of-things-based optimal smart city energy management considering shiftable loads and energy storage |
| ID_Doc |
41989 |
| Authors |
Golpîra, H; Bahramara, S |
| Title |
Internet-of-things-based optimal smart city energy management considering shiftable loads and energy storage |
| Year |
2020 |
| Published |
|
| DOI |
10.1016/j.jclepro.2020.121620 |
| Abstract |
Formulating a novel mixed integer linear programing problem, this paper introduces an optimal Internet-of-Things-based Energy Management (EM) framework for general distribution networks in Smart Cities (SCs), in the presence of shiftable loads. The system's decisions are optimally shared between its two main designed layers; a "core cloud" and the "edge clouds". The EM of a Microgrid (MG), covered by an edge cloud, is directly done by its operator and the Distribution System Operator (DSO) is responsible for optimising the EM of the core cloud. Changing the load consumption pattern, based on market energy prices, for the edge clouds and their peak load hours, the framework results in decreasing the total operation cost of the edge clouds. Using the optimal trading power of the MGs aggregators as the input parameters of the core cloud optimisation problem, the DSO optimises the network's total operation cost addressing the optimal scheduling of the energy storages. The energy storages are charged in low energy prices through the purchasing power from the market and discharged in high energy prices to meet the demand of the network and to satisfy the energy required by the edge clouds. As a result, the shiftable loads and the energy storages are used by the DSO and the MGs to meet the energy balance with the minimum cost. (C) 2020 Elsevier Ltd. All rights reserved. |
| Author Keywords |
Energy management; Internet-of-Things; Microgrids; Optimal scheduling; Renewable energy sources |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000538390400024 |
| WoS Category |
Green & Sustainable Science & Technology; Engineering, Environmental; Environmental Sciences |
| Research Area |
Science & Technology - Other Topics; Engineering; Environmental Sciences & Ecology |
| PDF |
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