6533b86cfe1ef96bd12c8aea

RESEARCH PRODUCT

An execution, monitoring and replanning approach for optimal energy management in microgrids

Alessandra De PaolaMariano Giuseppe IppolitoMaria Luisa Di SilvestreEleonora Riva SanseverinoGiuseppe Lo Re

subject

EngineeringOptimization problemEnergy managementbusiness.industryMechanical EngineeringControl (management)Distributed energy resources management Multi-objective evolutionary optimization MicrogridsBuilding and ConstructionInterval (mathematics)PollutionIndustrial and Manufacturing EngineeringScheduling (computing)Reliability engineeringSettore ING-IND/33 - Sistemi Elettrici Per L'EnergiaGeneral EnergyProduction (economics)MinificationElectrical and Electronic EngineeringInterruptbusinessSimulationCivil and Structural Engineering

description

abstract This work develops a new approach for optimal energy management of electrical distribution ‘smart-grids’. Optimality aims at improving sustainability through the minimization of carbon emissions and atreducing production costs and maximizing quality. Input data are the forecasted loads and productionsfrom renewable generation units, output data are a set of control actions for the actuators. Theconsidered electrical distribution system includes storage units that must be considered over a 24 h timeinterval, to consider an entire charge and discharge cycle. The objectives for the optimal management ofdistributed (renewables and not) generation are technical, economical and environmental. It is thusrequired to solve a multi-objective optimization problem over a 24 h time interval considering theuncertainty associated to weather conditions and loads profiles. The novelty of the proposed approachresides in considering the optimal scheduling of generation units an automatic planning process ina dynamic, non-deterministic and not fully observable environment, as it is, getting closer to actualconditions. The system proposed here is a planning and execution scheduler which allows the centralcontroller to monitor the execution of a scheduling plan, interrupt the monitoring to input new infor-mation and repair the plan under execution every time interval. 2011 Elsevier Ltd. All rights reserved.

10.1016/j.energy.2011.03.047http://hdl.handle.net/10447/54083