Energy Management Strategy for an Autonomous Hybrid Power Plant Destined to Supply Controllable Loads

Abstract

This paper proposes an energy management strategy (EMS) for a hybrid stand-alone plant destined to supply controllable loads. The plant is composed of photovoltaic panels (PV), a wind turbine, a diesel generator, and a battery bank. The set of the power sources supplies controllable electrical loads. The proposed EMS aims to ensure the power supply of the loads by providing the required electrical power. Moreover, the EMS ensures the maximum use of the power generated by the renewable sources and therefore minimizes the use of the genset, and it ensures that the batteries bank operates into the prefixed values of state of charge to ensure their safe operation. The EMS provides the switching control of the switches that link the plant components and decides on the loads’ operation. The simulation of the system using measured climatic data of Mostoles (Madrid, Spain) shows that the proposed EMS fulfills the designed objectives.

Current Status, Sizing Methodologies, Optimization Techniques, and Energy Management and Control Strategies for Co-Located Utility-Scale Wind–Solar-Based Hybrid Power Plants: A Review

“…Fuzzy logic has been used to manage energy flux in hybrid systems with solar, wind, and battery components, demonstrating successful control of energy flux [73]. Yahyaoui and De La Peña [74] used fuzzy logic to enhance energy management systems for wind, solar, battery, and diesel generator systems. Ammari et al [34] identified various fuzzy logic algorithms, such as the adaptive neuro-fuzzy inference system (ANFIS), the fuzzy analytic hierarchy process (FAHP), ANP, fuzzy clustering, the genetic algorithm, fuzzy particle swarm optimization, fuzzy honeybee optimization, and quantum-behaved particle swarm optimization.…”

Review of Efficiency Improvement Technologies of Wind Diesel Hybrid Systems for Decreasing Fuel Consumption

“…The EMS is focused on the maximum use of RES power, reducing DG penetration and maintaining the charge of ESS within an allowable range. The EMS produces signals to connect the necessary power supply source depending on the load and using fuzzy logic [133]. Phan et al (2022) presented an EMS based on deep Q network (DQN) for an island hybrid power plant with energy storage based on batteries and electrolyzed hydrogen.…”

Energy management strategies of hybrid renewable energy systems: A review

“…In addition, various energy storage technologies (including supercapacitors, vanadium redox flow, pump storage and lithium-ion) were taken into account. For a hybrid off-grid system intended to power controllable loads, a different energy management strategy (EMS) is suggested by Yahyaoui and de la Peña (2022) the necessary electrical power while ‘ensuring the maximum use of energy produced by renewable sources, and ensuring that the battery bank operates at no cost and in the specified state values to ensure their safe operation’ in order to reduce the use of the genset. Using machine learning, predictive energy management for the grid is demonstrated (Refaai et al, 2022) to optimise the energy exchange with the supply network by means of logistic regression.…”