During the past few years, due to the growth of electric power consumption, generation costs as well as rises in the level of greenhouse gases efficiency bring special focus on distributed generation. Developing distributed generation resources, especially renewable energy resources, is one of the safest ways to solve such problem. These resources have been decentralised by being installed close to the houses producing few kilowatts. Therefore, there are no losses in transmission lines and provide response for demand. Based on their benefits, the use of such energy resources should be developed in the future, but its management and optimal use is a major challenge. This has become one of the main concerns ofenergy systems researchers. In the current study, an innovative model is provided as a strategic management. It is intended to optimise the operation in smart homes consisting of generation units such as a wind turbine, solar panels, storages, and un/controllable loads. The main objective of this optimisation management is to maximise microgrid profitability for 24 h. The overall results of the model proved that the profit of microgrid increased significantly.

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The increased greenhouse gas emissions and the global warming from fossil fuels to produce electrical power generation and transportation, they become the most critical concern of governments to find an alternative source to fossil fuels such as renewable energies like wind and solar; Additionally, transportation is one of the main sources of environmental pollution, to this end, PHEV grid is presented, but the widespread use of PHEV will be creating a significant load on the grid. For this reasons in this paper, a model for the optimal application of green house, was studied in 24 hours. Energy management issue is considered in zero energy buildings with solar hybrid power sources, fuel cell, electrolyzer, hydrogen tank, compressor, reformer, anaerobic reactors and converters as well as plug-in hybrid electric vehicle (PHEV) must be provided, designed and implemented. The green house serves bilateral energy exchange with the upstream distribution network and if the surplus energy provided, can be sold to the network. Daily house trashes use to decline the bioenvironmental contaminations and also heat of house and hot water is supplied using fuel cell heat and if necessary we should purchase gas from network. In order to optimize this house, an objective function is extracted and aggregation Swarm algorithm to minimizing costs was carried out using MATLAB program. Finally, optimal operation is presented for the green house and results have been analyzed.