International Journal of Power Electronics and Drive Systems (IJPEDS) Vol. 13, No. 1, March 2022, pp. 178~190 ISSN: 2088-8694, DOI: 10.11591/ijpeds.v13.i1.pp178-190  178 Journal homepage: http://ijpeds.iaescore.com A new modular nanogrid energy management system based on multi-agent architecture Meryem Hamidi, Abdelhadi Raihani, Mohamed Youssfi, Omar Bouattane Systèmes Distribués et Intelligence Artificielles (SSDIA) Laboratory of Ecole Normale Supérieure de l’Enseignement Technique (ENSET), Hassan II University of Casablanca, Casablanca, Morocco Article Info ABSTRACT Article history: Received Nov 2, 2021 Revised Jan 18, 2022 Accepted Jan 25, 2022 The emergence of renewable energy sources with controllable loads gave the opportunity to the consumers to build their own Microgrids. However, the intermittence of renewable energy sources such as wind and photovoltaic leads to some challenges in terms of balancing generation and consumption. This paper aims to present a novel multi-agent model based intelligent control scheme to balance the home/building alternative current (AC)-direct current (DC) load demands and renewable energy sources. The new proposed scheme consists of a three-level hierarchical multi agent system based on cooperation, communication and interaction between intelligent agents to fulfill the load's requirements. Then, the proposed multi agent framework is simulated using four different nanogrids to prove its effectiveness using different temporal profiles for loads and generators. The proposed model is designed to be modular, so that it can be considered as a sample from a set of similar modules, assigned to different buildings to allow efficient energy sharing and balancing. The used approach in this concept is inspired from auto-similar systems, which is well suited and easy to implement on multi agent systems. A co-simulation in MATLAB and JAVA/JADE platforms has been performed regarding the production- consumption of the 24 hours baseline period. Keywords: Building Energy saving Microgrid Multi agent system Nanogrid This is an open access article under the CC BY-SA license. Corresponding Author: Meryem Hamidi Systèmes Distribués et Intelligence Artificielles (SSDIA), Laboratory of Ecole Normale Supérieure de l’Enseignement Technique (ENSET), Hassan II University of Casablanca Casablanca, Morocco Email: meryem.ham@gmail.com NOMENCLATURE   : The rated power of the PV module under standard test conditions (kW) PV : Photovoltaic   : The PV derating factor WT : Wind turbine   : Solar radiation (kW/m 2 ) NG : Nanogrid   : Incident radiation at standard test conditions (1kW/m 2 ) MG : Microgrid   : Temperature coefficient (0.004°C -1 ) MAS : Multi agent system   : PV cell operation temperature (°C) ACL : AC Load   : PV cell temperature under standard test conditions (25 °C) DCL : DC Load   : The theoretical maximum value of the wind power coefficient 0.593 BC : Bidirectional converter λ : The function of tip speed ratio BS : Bidirectional switch.  : Pitch angle    : PV output power in NG   : The rotor blades intercepting area (m 2 )    : WT output power in NG   : The wind speed average (m/s)   : Global output power of NG