With the development of smart grid, energy consumption on residence will play an important role in the electricity market, while the Home Energy Management System (HEMS) has huge potential to help energy conservation. In this study, a practical HEMS model with renewable energy, storage devices and plug-in electric vehicles, considering the battery sustainability and the full utilisation of the renewable energy, is first established. Then, according to the combinations of the genetic algorithm (GA) and the multi-constrained integer programming method, an improved GA is proposed, which goal is to minimise the electricity purchase and maximise the renewable energy utilisation. Finally, it is demonstrated by an example that the proposed method is significant in cost saving and reducing energy wastes. To verify the performances of the proposed algorithm, the numerical results indicate that the proposed algorithm has high computational efficiency and good robustness. In addition, it can avoid the disadvantages easy to trap at a local optimal point, and are insensitive to initial solutions. The effect of the storage device on system property and the sensitivity of cost savings versus demand response, size of the battery, and the electricity price sell to the grid are also analysed.

In this paper, we propose a novel optical packet switch (OPS) architecture with input concentrators, which employ multi-input single-output optical buffers to aggregate all the incoming traffic into a small size switching fabric. Accordingly, the physical size, the number of the needed wavelength converters, and the economic cost of the total OPS node are decreased dramatically. However, the deployment of input concentrators introduces additional packet loss and delay, except from the contention at the switch output. A Markov model is presented to study the packet loss ratio (PLR) and average packet delay given by the input concentrators. The corresponding closed form expressions are given. The model also demonstrates that the system performance can be greatly improved by increasing the buffer size when the traffic load is not larger than 0.69315. The analytical values are compared with the simulation results. All the obtained results show that the proposed model provides satisfactory approximations under different network scenarios. Moreover, the economic cost savings of the proposed OPS node at the present time and its evolution as a function of time are also discussed in detail. The proposed architecture can also be applied in a packet enhanced optical transport network (OTN).