Optimal Scheduling of Energy Storage Using A New Priority-Based Smart Grid Control Method

This paper presents a method to optimally use an energy storage system (such as a battery) on a microgrid with load and photovoltaic generation. The purpose of the method is to employ the photovoltaic generation and energy storage systems to reduce the main grid bill, which includes an energy cost a...

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Bibliographic Details
Published in:Energies (Basel) 2019-02, Vol.12 (4), p.579
Main Authors: Galván, Luis, Navarro, Juan M, Galván, Eduardo, Carrasco, Juan M, Alcántara, Andrés
Format: Article
Language:English
Subjects:
Algorithms
Alternative energy sources
batteries
Computer simulation
Consumers
Consumption
Cost control
Distributed generation
Electric power distribution
Energy industry
Energy management
Energy resources
Energy storage
International conferences
Methods
microgrids
Objective function
optimal scheduling
Optimization
particle swarm optimization
Personal computers
Photovoltaics
power system management
Programmable logic controllers
Renewable resources
Scheduling
smart grid
Smart grid technology
Storage systems
supply and demand
trade agreements
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Summary:This paper presents a method to optimally use an energy storage system (such as a battery) on a microgrid with load and photovoltaic generation. The purpose of the method is to employ the photovoltaic generation and energy storage systems to reduce the main grid bill, which includes an energy cost and a power peak cost. The method predicts the loads and generation power of each day, and then searches for an optimal storage behavior plan for the energy storage system according to these predictions. However, this plan is not followed in an open-loop control structure as in previous publications, but provided to a real-time decision algorithm, which also considers real power measures. This algorithm considers a series of device priorities in addition to the storage plan, which makes it robust enough to comply with unpredicted situations. The whole proposed method is implemented on a real-hardware test bench, with its different steps being distributed between a personal computer and a programmable logic controller according to their time scale. When compared to a different state-of-the-art method, the proposed method is concluded to better adjust the energy storage system usage to the photovoltaic generation and general consumption.
ISSN:1996-1073
1996-1073
DOI:10.3390/en12040579