## 4 Performance Evaluation
However, it is clear that the proposed solution obtains the best performance. This may be explained considering that the algorithm proposed by [PERSON] _et al._ is quite different compared to the one introduced in this paper; on the contrary, in the algorithm proposed by [PERSON] _et al._, different threshold values for \(P_{thr}\) and \(D_{thr}\) are used, and as a consequence, the performances are different from those obtained with the algorithm proposed in this work. The contribution of the appliances to the average peak load is depicted in Figure 8. As it is possible to see, without an energy management approach, almost 0.3 of the load generated by the appliances takes place during peak periods. On the contrary, [PERSON] _et al._'s approach shifts those loads from peak times, and almost 0.12 of the total load is left in the peak hours, while [PERSON] _et al._'s approach obtains a value of about 0.13. On the contrary, using the proposed solution, the peak load is reduced to 0.05. Even in this case, the best performances are those obtained with the proposed HEM solution. Figure 7: Peak load reduction comparison. The average delay experienced by the consumer is shown in Figure 9. It is necessary to note that without an energy management scheme, an appliance starts as soon as the consumer turns it on, and as a consequence, the delay is almost zero. For this reason, this case has not been included in the plot. For [PERSON] _et al._'s scheme, the delay fluctuates from 3-4 h, while using [PERSON] _et al._'s approach, the delay is almost equal, since it fluctuates from 3-4.5 h. On the contrary, in using the proposed solution, the delay is less than 3 h in most of the simulation. In fact, in the HEM algorithm introduced in this work, the consumer's feedback is taken into account in the FLC in order to improve the calculation of the delay. As a consequence, the delay can be updated if the consumer has already given one or more feedbacks in the past on the same appliance. The consumer's feedback represents clear indicators of his or her desired comfort level. It is useful to highlight that the delays shown in Figure 9 can be tolerable for several appliances, such as washers or dishwashers. On the contrary, for other appliances, such as coffeemakers, the consumer wants to start them immediately. For this reason, in the proposed approach, the consumer may deny or accept the schedule proposed by the EMU. Figure 8: Load of the appliances ratio during peak hours. Figure 9: Average delay experienced by the consumer in HEM schemes. After evaluating the performance of the HEM solution proposed in this paper, it is useful to analyze what could be the economic benefits in its application. Regarding the monetary cost reduction, it is necessary to note that across the world, the electricity distributors have implemented various tariff schemes for peak load management. In this paper, the proposed scheme is based on a time-of-use tariff, and as a consequence, tariff pricing rates are different for different hours. In detail, the considered tariff is the one proposed by the Italian Enel [36], a multinational manufacturer and distributor of electricity and gas, whose costs are 0.0365 EUR/kWh in off peak hours and 0.1725 EUR/kWh in peak hours (from 8 a.m.-7 p.m.). The electricity consumption cost of a single home has been simulated both when no energy management is applied and when the approaches of [PERSON] _et al._ and [PERSON] _et al._ and the proposed solution are applied. The simulation results for a seven month electricity bill is shown in Figure 10. It is useful to note that the electricity bill increases with increasing months, because the bill is calculated cumulatively. Even in this case, the best results are obtained with the solution proposed in this paper that allows one to achieve a higher monetary cost reduction. The performance of the proposed WN, in terms of the packet delivery ratio, end-to-end delay and jitter, has been evaluated in the simulations.