Fuzzy Efficient Energy Smart Home Management System for Renewable Energy Resources

Round 1

Reviewer 1 Report

The manuscript reports on the novel phenomenon of the formation of a The Renewable Energy Sources integration based on an effective way to deliver RE training to the neighboring customer and to the power grid at the right time to increase the efficiency and the power system revenue. The
Renewable Energy Sources alternating nature makes it inefficient to change the power generation.
ESS is one of the effective ways to smooth these trade surpluses is another way of neighboring customer needs clarification on renewable energy sources integration model.

Give an explanation for this somewhat “unexpected” effect for the reader who is not an expert for Bi
(volume change?). Why is there a difference to hydrostatic conditions for Renewable Energy
Resources?

Grid Energy Consumer (GEC) does not have RES and depends on micro grid energy. Here the parameter units are the Grid Energy Consumer energy demand per time slot, since The energy demand of Grid Energy Consumer is not controlled as classify the procedure for the High energy usage and power cost for off-peak to on-peak hours.

To use real data experiments as a further test case of our method. Rebalance the discussion of the real data experiment in Section 4 to make it clear that it was intended as a proof-of-concept of the
approach.

The Energy Storage System model for Trading Energy Consumption is not harvested properly and to accomplish the issue in Renewable Energy Fluctuation Trading Energy Consumption, clarify how it has been installed by Trading Energy Consumption that simplifies the integration of RES effective
energy for the removal of waste energy and enlargement of the revenue.

 

Author Response

ESS is one of the effective ways to smooth these variations. The production of trade surpluses is another way of neighboring customers. Based on the generation trading residential consumer and power RES energy is divided into three modules: smart energy consumer (SEC), Grid energy consumer (GEC), and Trading energy consumer (TEC). Smart energy consumer (SEC) accomplishes their energy demand form ESS, smart grid station, RES.  units are the Smart energy consumer demand for energy demand per slot of time should not reach beyond the extreme claim. Using own Renewable Energy, the Smart Energy Consumption satisfies their demand. if the Smart energy consumer demand maximizes the available energy from RES ,Where  represents the power got at each timeslot from the power grid,    denotes neighbor TEC borrowed energy at each timeslot from,  denotes the original energy stored of Smart Energy Consumption in Energy Storage System. The proposed FES-EESHM can efficiently decrease the peak to average ratio and cost of electricity with minimum peak load value. For this reason, the fuzzy expert system with a controller is suggested to control the consumption of energy, energy storage, and production, scheduling energy trading and loads to reduce the power flow and cost of electricity.  ESS is used to reduce the fluctuation and to effectively use Renewable Energy and enhance the strength of the power system. To simplify the integration of RES energy efficient, Trading Energy Consumption and Smart Energy Consumption have formed in ESS locations

Author Response File: Author Response.docx

Reviewer 2 Report

Well written, this is a novel approach and as stated "the controller works on a continuous modification of the input data in real-time, some of which can be predicted for the future to predict the system's future behaviors," which is what we need for future energy access.

Author Response

Thank you very much for your positive feedback. Energy Storage System model for Smart Energy Consumption: The Energy Storage System importantly includes in the RES effective energy integration that improves assist, reliability, and security in the pollution-free atmosphere. The goal is to satisfy the house's energy demand sustainably with the local photovoltaic energy generation while retaining the user's comfort by  solar photovoltaics in the residential sector. An efficient Home Energy Management System (HEMS) is needed for this. The proposed scheme in this paper is based on a tariff time-of-use, which results in different tariff pricing rates for different hours. the appliances contribution to average peak loads and the average consumer delay, together with the advantages of a fuzzy approach that seeks to achieve the best balance between demand and energy usage.

Reviewer 3 Report

 This work presents interesting results pertaining to the creation of reflective decision on energy generated, controllable loads and own consumption based on picosecond pulses results in the formation by the expert system and the output is not de-fuzzfied properly.
 What is the main question addressed by the research? Is it relevant and interesting? How original is the topic? What does it add to the subject area compared with other published material?
 Gives a clear idea of the target readership, why the research was carried out and the novelty and topicality of the manuscript
 Is the paper well written? Is the text clear and easy to read? Justify based on mathematical proof since from Eq (7 to 10), it is more unclear.
 Discussion should always, at some point, gather all the information together into a single whole. It is mandatory to describe and discuss the overall gaps or inconsistencies in the research perspective and they should address future research standpoint findings.
 Are the conclusions consistent with the evidence and arguments presented? Do they address the main question posed? Because Drawing a conclusion that is contradicted by the author's own statistical or qualitative evidence

Author Response

Energy Storage System model for Smart Energy Consumption: The Energy Storage System importantly includes in the RES effective energy integration that improves assist, reliability, and security in the pollution-free atmosphere. The goal is to satisfy the house's energy demand sustainably with the local photovoltaic energy generation while retaining the user's comfort by  solar photovoltaics in the residential sector. An efficient Home Energy Management System (HEMS) is needed for this. 

The proposed scheme in this paper is based on a tariff time-of-use, which results in different tariff pricing rates for different hours. the appliances contribution to average peak loads and the average consumer delay, together with the advantages of a fuzzy approach that seeks to achieve the best balance between demand and energy usage. 

The amount of power occupied from neighboring Trading Energy Consumption, electricity grid station and Energy Storage System should fulfill the demand of residue. 

Home Management System (FES-EESHM) has been proposed for renewable energy resources. Concurrent decision making with modified input data is possible through the implementation of the fuzzy logic. The fuzzy logic provides users to change the rules and to change the function of their controller because of the relation with linguistic expressions. 

With this method, renewable energy can be spread to charging a battery and feeding a heat pump that generates thermal energy. The result shows that for the first case (the discharged battery is not charged during the vibration) the battery charged is around 96 % and for the second, the thermal energy level from renewables is around 89 % and for that case around 83 % (the sound battery is discharged). The remaining energy needed must be provided by the grid.