Smart City Gnosys
Smart city article details
| Title | A Probabilistic Tool For Modeling Smart Microgrids With Renewable Energy And Demand Side Management |
|---|---|
| ID_Doc | 3824 |
| Authors | Thornburg J.A. |
| Year | 2022 |
| Published | Proceedings of International Conference on Computational Intelligence and Sustainable Engineering Solution, CISES 2022 |
| DOI | http://dx.doi.org/10.1109/CISES54857.2022.9844342 |
| Abstract | Smart meters allow even remote villages to act as smart cities by enabling high-granularity sensing and control of power demand in individual buildings. Recent smart meters equip buildings or specific loads to perform demand side management (DSM) based on signals for electricity consumers to shed load or build load. For emerging contexts serviced by isolated microgrids and limited generation capacity, DSM is an important solution to advancing sustainable energy access. Quantitatively comparing the impact of different microgrid operating strategies and DSM schemes before implementation is needed to ensure dynamic, reliable microgrid service while keeping costs and emissions low. This paper addresses that need by presenting a simulation tool, a software platform that employs probabilistic models to simulate the full range of microgrid scenarios (e.g., occasional power cuts and service reliability). To accurately characterize the range and variability of potential results in a real world microgrid, the modeling software is stochastic, using Monte Carlo methods with a Markov model. The methods are demonstrated in MATLAB to simulate renewable energy installations and loads common in isolated microgrids of rural India and much of Africa. The tool is called the Probabilistic Load-Attenuating Smart Microgrid Simulator (PLASMiS). Users can define probability distributions for loads and supplies while defining control strategies for deploying energy storage and dispatchable generation. This functionality is demonstrated in case studies that use PLASMiS to model a typical isolated microgrid in Rwanda. © 2022 IEEE. |
| Author Keywords | demand side management; energy management; Markov model; microgrids; renewable energy; Smart cities |
Similar Articles
| Id | Similarity | Authors | Title | Published |
|---|---|---|---|---|
43244  | 0.868 | Ye Z.; Luo F. | Probabilistic Distribution Identification For Power Load In Australian "Smart Grid, Smart City" Dataset | BuildSys 2024 - Proceedings of the 2024 11th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (2024) |
| 59953 | 0.865 | Kumar D. | Urban Energy Systems: Modeling And Simulation For Smart Cities | Urban Energy Systems: Modeling and Simulation for Smart Cities (2023) |
| 31862 | 0.863 | Zhao X.; Zhang Y. | Integrated Management Of Urban Resources Toward Net-Zero Smart Cities Considering Renewable Energies Uncertainty And Modeling In Digital Twin | Sustainable Energy Technologies and Assessments, 64 (2024) |
| 26824 | 0.863 | Miyasawa A.; Akira S.; Fujimoto Y.; Hayashi Y. | Forecast Of Area-Scale Behaviours Of Behind-The-Metre Solar Power And Load Based On Smart-Metering Net Demand Data | IET Smart Cities, 5, 1 (2023) |
| 11474 | 0.858 | Özkan E.; Kök I.; Özdemir S. | Autonomous Micro-Grids: A Reinforcement Learning-Based Energy Management Model In Smart Cities | 2023 International Symposium on Networks, Computers and Communications, ISNCC 2023 (2023) |
| 20735 | 0.857 | Sen S.; Kumar M. | Distributed-Mpc Type Optimal Ems For Renewables And Evs Based Grid-Connected Building Integrated Microgrid | IEEE Transactions on Industry Applications, 60, 2 (2023) |
| 3362 | 0.852 | Li B.; Tan W. | A Novel Framework For Integrating Solar Renewable Source Into Smart Cities Through Digital Twin Simulations | Solar Energy, 262 (2023) |
| 15535 | 0.852 | Sekhar D.C.; Rao P.V.V.R.; Kiranmayi R. | Conceptual Review On Demand Side Management, Optimization Techniques For The Improvement Of Power Quality In Smart Grids | Proceedings of the 2nd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2022 (2022) |
| 927 | 0.852 | Alotaibi I.; Abido M.A.; Khalid M.; Savkin A.V. | A Comprehensive Review Of Recent Advances In Smart Grids: A Sustainable Future With Renewable Energy Resources | Energies, 13, 23 (2020) |
| 40845 | 0.851 | Arunkumar A.P.; Kuppusamy S. | Optimizing Microgrid Designs Towards Net-Zero Emissions For Smart Cities: Addressing Energy Disparities And Access Issues In Northern And North-Eastern India | International Journal of Applied Power Engineering, 14, 1 (2025) |