Recent decentralization of electricity systems together with the decarbonization and several changing societal demands are giving rise to different application scenarios such as microgrids. A microgrid is a small-scale electrical system which consists of several loads and sources (conventional and renewables) that can either operate autonomously in a stand-alone mode or interconnected with the main grid. The design and development of such a smart microgrid in a university campus is proposed within the 3DMicroGrid project (funded through the ERANETMED European Union's initiative). This paper reviews the main components and characteristics of similar microgrids developed around the world. Furthermore, this study provides the design guidelines, the main functionalities, the key components and the control architecture for developing the microgrid proposed by the 3DMicroGrid project. A simulation model has been developed and initial results are demonstrated for the operation of this microgrid. The recommendations and insights are replicable to any solar priority country for future microgrids pilots.

This paper presents a fault-tolerant secondary and adaptive primary microgrid control scheme using a hybrid multiagent system (MAS), capable of operating either in a semi-centralised or distributed manner. The proposed scheme includes a droop-based primary level that considers the microgrid energy reserves in production and storage. The secondary level is responsible for: a) the microgrid units' coordination, b) voltage and frequency restoration and c) calculation of the droop/ reversed-droop coefficients. The suggested architecture is arranged upon a group of dedicated asset agents that collect local measurements, take decisions independently and, collaborate in order to achieve more complex control objectives. Additionally, a supervising agent is added to fulfill secondary level objectives. The hybrid MAS can operate either with or without the supervising agent operational, manifesting fast redistribution of the supervising agent tasks. The proposed hybrid scheme is tested in simulation upon two separate physical microgrids using three scenarios. Additionally, a comparison with conventional control methodologies is performed in order to illustrate further the operation of a hybrid approach. Overall, results show that the proposed control framework exhibits unique characteristics regarding reconfigurability and fault-tolerance, while power quality and improved load sharing are ensured even in case of critical component failure. PF min minimum power factor (-) m f-P droop coefficient (Hz/W) n V-Q droop coefficient (Hz/VAr) v ocd compensating d-axis voltage by virtual impedance (V) v ocq compensating q-axis voltage by virtual impedance (V) i od inverter output inductor current on the d-axis (A) i oq inverter output inductor current on the q-axis (A) R v resistive part of the virtual impedance (Ω) L v inductive part of the virtual impedance (H) M on exchanged agent messages during one operation cycle-MGCC operational (-) M off exchanged agent messages during one operation cycle-MGCC inactive (-) N ESS total number of ESSs in a microgrid (-) N PV total number of PVs in a microgrid (-) N Load total number of load buses in a microgrid (-) E nom Nominal Battery Capacity (Wh)

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Power plants have bad impacts on the environment. One of these impacts is Carbon Dioxide (CO2) emission resulted from power plants that depend on fossil fuel, oil and natural gas. Renewable energy is considered as an important solution for this problem since it is classified as clean and environmentally friendly source of energy and helps reducing the dependency on conventional power plants. High renewable energy penetration into power systems is a big challenge that can be solved by deploying the concept of smart Micro-Grids. This paper presents a study on how much reduction of CO2 emission can be resulted from deploying smart micro-grid concept on a university campus, German Jordanian University (GJU) campus was taken as a pilot. The micro-grid is meant to operate according to an optimum resource scheduling framework that guarantee a minimum operational cost while achieving high local power availability.