Microgrids are energy systems that aggregate distributed energy resources, loads, and power electronics devices in a stable and balanced way. They rely on energy management systems to schedule optimally the distributed energy resources. Conventionally, many scheduling problems have been solved by using complex algorithms that, even so, do not consider the operation of the distributed energy resources. This paper presents the modeling and design of a modular energy management system and its integration to a grid-connected battery-based microgrid. The scheduling model is a power generation-side strategy, defined as a general mixed-integer linear programming by taking into account two stages for proper charging of the storage units. This model is considered as a deterministic problem that aims to minimize operating costs and promote self-consumption based on 24-hour ahead forecast data. The operation of the microgrid is complemented with a supervisory control stage that compensates any mismatch between the offline scheduling process and the real time microgrid operation. The proposal has been tested experimentally in a hybrid microgrid at the Microgrid Research Laboratory, Aalborg University.

The coordinated operation of distributed energy resources such as storage and generation units and also loads is required for the reliable operation of an islanded microgrid. Since in islanded microgrids the storage units are commonly responsible for regulating the voltage amplitude and frequency in the local power system, the coordination should consider safe operating limits for the stored energy, which prevents fast degradation or damage to the storage units. This paper proposes a centralized control architecture, applicable for local area power systems such as a small-scale microgrid. The centralized architecture is based on three supervisory control tasks which consider: active power curtailment of generation for avoiding overcharge of the storage units, load shedding actions for preventing deep discharge of the storage units, and equalization of the state of charge among distributed storage systems for avoiding uneven degradation. The proposed equalization method has proved to be effective for equalizing the state of charge of distributed energy storage systems and for ensuring uniform charge/discharge ratios regardless of differences in the capacity of the storage units. Additionally, the strategy is complemented with an optimal scheduling of load connection, which minimizes the connection and disconnection cycles of the loads within a time horizon of 24 hours. The proposed architecture is verified experimentally in a lab-scale prototype of a microgrid, which has real communication between the microgrid and the central controller.

Due to the decreasing revenues from the surplus renewable energy injected into the grid, mechanisms promoting self-consumption of this energy are becoming increasingly important. Demand response (DR) and local storage are among the widely used mechanisms for reaching higher self-consumption levels. Deploying a shared storage unit in a residential microgrid is an alternative scenario that allows households to store their surplus renewable energy for a later use. However, this creates some challenges in managing the battery and the available energy resource in a fair way. In this paper, a reputation-based centralized energy management system (EMS) is proposed to deal with these issues by considering households’ reputations in the reallocation of available energy in the shared storage unit. This framework is used in an optimization problem, in which the EMS jointly schedules households’ appliances power consumption and the energy that each household can receive from the storage unit. The scheduling problem is formulated as a Mixed Integer Linear Programming (MILP) with the objective of minimizing the amount and price of energy absorbed from the main grid. The MILP problem is coded in GAMS and solved using CPLEX. Numerical analysis is conducted using real data of renewable energy production and appliances’ demand profiles for different classes of households and different annual periods in Spain. Simulation results of the different scenarios show that by using the proposed framework higher cost savings can be achieved, in comparison with the classical scheduling scenario. The saving can reach up to 68% when different classes of households exist in the microgrid. The results also show that the fairness in energy allocation is guaranteed by the reputation-based policy, and that the total power absorbed from the main grid by the whole microgrid is significantly decreased.Peer ReviewedPostprint (author's final draft

Microgrids are energy systems that can work independently from the main grid in a stable and self-sustainable way. They rely on energy management systems to schedule optimally the distributed energy resources. Conventionally, the main research in this field is focused on scheduling problems applicable for specific case studies rather than in generic architectures that can deal with the uncertainties of the renewable energy sources. This paper contributes a design and experimental validation of an adaptable energy management system implemented in an online scheme, as well as an evaluation framework to quantitatively assess the enhancement attained by different online energy management strategies. The proposed architecture allows the interaction of measurement, forecasting and optimization modules, in which a generic generation-side mathematical problem is modeled, aiming to minimize operating costs and load disconnections. The whole energy management system has been tested experimentally in a test bench under both grid-connected and islanded mode. Also, its performance has been proved considering severe mismatches in forecast generation and load. Several experimental results have demonstrated the effectiveness of the proposed EMS, assessed by the corresponding average gap with respect to a selected benchmark strategy and ideal boundaries of the best and worst known solutions.

The increment of electrical and electronic appliances for improving the lifestyle of residential consumers had led to a larger demand of energy. In order to supply their energy requirements, the consumers have changed the paradigm by integrating renewable energy sources to their power grid. Therefore, consumers become prosumers in which they internally generate and consume energy looking for an autonomous operation. This paper proposes an energy management system for coordinating the operation of distributed household prosumers. It was found that better performance is achieved when cooperative operation with other prosumers in a neighborhood environment is achieved. Simulation and experimental results validate the proposed strategy by comparing the performance of islanded prosumers with the operation in cooperative mode¹.