Dear researchers, what are the proposed methods to optimize battery SOC and diesel fuel usage , as an energy management strategy for off-grid microgrids ?
Such system are exposed to uncertainty and high penetrations of renewable resources.
Hi Mohamed Amine Hartani,
There are plenty of methods in the literature such as stochastic optimization, robust optimization, adaptive robust optimization, distributionally robust, chance constraints, risk analysis, model predictive control, information gap theory ...
For an off-grid energy management problem, I recommend model predictive control as the best option in terms of adaptability, computation, and multi-mode operation of microgrids ...
For instance, see:
Article A Two-Stage Model Predictive Control Strategy for Economic D...
Article Mixed-Stage Energy Management for Decentralized Microgrid Cl...
please see this papers
- Optimal adaptive fuzzy management strategy for fuel cell-based DC microgrid
- Optimal control and implementation of energy management strategy for a DC microgrid
- Energy management system for a hybrid PV-Wind-Tidal-Battery-based islanded DC microgrid: Modeling and experimental validation
Dear Mohamed Amine Hartani ,
Thank you very much for raising the interesting question.
As mentioned by other colleagues, there is a wide spectrum of methodology is available when it comes to energy management strategies for off-grid microgrids.
However, it depends on what exactly you want to optimize and up to what extent.
Please find some useful links where you can read about the topic in detail.
- Computational optimization techniques applied to microgrids planning: A review (https://www.sciencedirect.com/science/article/pii/S1364032115002956)
- A compendium of optimization objectives, constraints, tools and algorithms for energy management in microgrids (https://www.sciencedirect.com/science/article/pii/S1364032115016421)
I hope this helps.
Best regards,
Kedar
Optimization methods are used in off-grid DC microgrids to ensure that the system is operating at its most efficient and reliable state. These methods can be used to determine the optimal sizing of components, the optimal control strategy, and the optimal dispatch of generators. There are a number of different optimization methods that can be used in off-grid DC microgrids. Some of the most common methods include:
- Linear programming (LP): LP is a mathematical optimization method that can be used to solve problems with linear constraints and objective functions. LP is a relatively simple method to solve, but it can only be used to solve problems with linear constraints.
- Nonlinear programming (NLP): NLP is a mathematical optimization method that can be used to solve problems with nonlinear constraints and objective functions. NLP is more complex than LP, but it can be used to solve problems with nonlinear constraints.
- Mixed-integer linear programming (MILP): MILP is a mathematical optimization method that can be used to solve problems with linear constraints, integer variables, and objective functions. MILP is more complex than LP and NLP, but it can be used to solve problems with integer variables.
The choice of optimization method will depend on the specific problem that is being solved. For example, if the problem has linear constraints, then LP may be the best choice. If the problem has nonlinear constraints, then NLP may be the best choice. If the problem has integer variables, then MILP may be the best choice.
Optimization methods are a powerful tool that can be used to improve the efficiency and reliability of off-grid DC microgrids. By using optimization methods, system operators can ensure that the system is operating at its best possible state, which can save money and improve the quality of power for the end users.
Here are some additional benefits of using optimization methods in off-grid DC microgrids:
- Reduced cost: Optimization methods can help to reduce the cost of operating an off-grid DC microgrid by optimizing the sizing of components, the control strategy, and the dispatch of generators.
- Improved reliability: Optimization methods can help to improve the reliability of an off-grid DC microgrid by ensuring that the system is operating at its most efficient state.
- Enhanced flexibility: Optimization methods can help to enhance the flexibility of an off-grid DC microgrid by allowing system operators to adapt the system to changing conditions.
Overall, optimization methods are a valuable tool that can be used to improve the efficiency, reliability, and flexibility of off-grid DC microgrids.
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