Intelligent controller based energy management for stand‐alone power system using artificial neural network

Abstract

Summary Standalone Power Systems (SPS), formerly known as Micro Power Systems, is an off‐grid electricity system for locations that are not fitted with an electricity generation. Typical SPS include one or more renewable electricity sources, energy storage, and regulation. In this paper, supervision of hybrid Photovoltaic system and battery storage is presented. The power balance of the hybrid system is made on an intelligent supervisor based on Artificial Neural Network Controller (ANNC). The main purpose of this paper is the control of DC/DC Bidirectional Converter (DBC), which connect the Li‐ion battery with the DC_Bus of Stand‐alone Power Systems (SPS). Based on the use of artificial neural network controller, which are effective tools for highly nonlinear system. The proposed technique does not require a pre‐defined model of power DBC only depend on power and voltage system data. Simulation for stand‐alone systems performed at Matlab Simulink. The comparison with PID controller for the result obtained of DC_Bus voltage, and power demanded, demonstrate the robustness, and satisfactory performance of the proposed control strategy.

Real-Time Energy Management for DC Microgrids Using Artificial Intelligence

“…The NARMA L2 controllers are composed of two neural networks: the first neural network is the NARMA model, which is the standard model used to represent general discrete-time nonlinear systems to identify which should be controlled; and the second network aims to generate the control signal, as Figure 12 shows. The mathematic equations of ANNC are well explained in our previous publication [15].…”

“…The battery storage system consisted of a Li-ion battery and a bidirectional DC-DC converter. This converter is responsible for maintaining and stabilizing the DC-Bus voltage through an ANNC controller, as observed in Figure 5 [15]. The PMSG is coupled directly to the wind turbine; a three-phase diode bridge is employed to rectify the generated output voltage.…”

“…The battery storage system consisted of a Li-ion battery and a bidirectional DC-DC converter. This converter is responsible for maintaining and stabilizing the DC-Bus voltage through an ANNC controller, as observed in Figure 5 [15]. As discussed before, lithium-ion batteries are the preferred power source for many storage system applications due to the advantages compared to other battery types.…”

“…The NARMA L2 controllers are composed of two neural networks: the first neural network is the NARMA model, which is the standard model used to represent general discrete-time nonlinear systems to identify which should be controlled; and the second network aims to generate the control signal, as Figure 12 shows. The mathematic equations of ANNC are well explained in our previous publication [15]. The ANNC used in this paper is known by two names: feedback linearization control, when the plant model has a particular form; and NARMA-L2 control, when the plant model is estimated by the same form.…”

Microgrid energy management system for smart home using multi-agent system

“…A microgrid is a medium or low-voltage hybrid power generation system that integrates small-scale energy producers renewable as primary resources to produce high-quality energy to a few consumers. The microgrid can run in mode connected to the main grid high or medium voltage by the common coupling point (PCC) or can also operate totally in an isolated mode [2], [3]. The power grid structure of MG is defined by the application and user specifications.…”