Abstract
With constant population growth and the rise in technology use, the demand for electrical energy has increased significantly. Increasing fossil-fuel-based electricity generation has serious impacts on environment. As a result, interest in renewable resources has risen, as they are environmentally friendly and may prove to be economical in the long run. However, the intermittent character of renewable energy sources is a major disadvantage. It is important to integrate them with the rest of the grid so that their benefits can be reaped while their negative impacts can be mitigated. In this article, an energy management algorithm is recommended for a grid-connected microgrid consisting of loads, a photovoltaic (PV) system and a battery for efficient use of energy. A model predictive control-inspired approach for energy management is developed using the PV power and consumption estimation obtained from daylight solar irradiation and temperature estimation of the same area. An energy management algorithm, which is based on a neuro-fuzzy inference system, is designed by determining the possible operating states of the system. The proposed system is compared with a rule-based control strategy. Results show that the developed control algorithm ensures that microgrid is supplied with reliable energy while the renewable energy use is maximized.
Highlights
Owing to the considerably increasing population and use of technology, the share of electricity in energy consumption is expected to reach 50–20% more than it is today [1]
In order to cope with these changes, energy management systems have become indispensable for most applications
mean absolute percent error (MAPE) is the average of the sum of absolute values of percentile errors
Summary
Owing to the considerably increasing population and use of technology, the share of electricity in energy consumption is expected to reach 50–20% more than it is today [1]. By using renewable energy systems with storage units, generated energy can be stored, and the energy continuity can be provided for the users. One of the most important solutions to the instability problem in renewable energy sources is energy storage By storing energy, it can exchange power in a planned manner in energy management so that the storage unit can act as a separate active and reactive power source, providing greater flexibility in energy management. It can exchange power in a planned manner in energy management so that the storage unit can act as a separate active and reactive power source, providing greater flexibility in energy management This autonomy offers the ability to manage their own warehouses, manage their own generation and manage and control the power flow to benefit from the grid according to various criteria. There are technical reasons such as managing the negative impacts of novel technologies, e.g., electric vehicles (EVs) and smart inverters, on the traditional grid structure [5,9,10]
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