A Smartbox as a low-cost home automation solution for prosumers with a battery storage system in a demand response program G. Brusco, G. Barone, A. Burgio, D. Menniti, A. Pinnarelli, L. Scarcello and N. Sorrentino Department of Mechanical, Energy and Management Engineering University of Calabria, Italy This paper presents an electronic device named Smartbox as a low-cost solution for those prosumers operating in a demand response program. Given processing resource in the cloud which optimally calculates the loads scheduling one day-ahead on the basis of the electricity prices and the load and weather forecasting, the aim of the Smartbox is to receive and to act the loads scheduling. A prototype of a Smartbox using an Arduino MEGA 2560 has been realized and tested in the laboratory, in combination with a demonstration panel which represents a private household equipped with a Schneider Electric home automation system based on Konnex communication protocol (KNX). 1 2 3 Fig. 1 – User input form Fig. 2 – Prosumer problem solver Fig. 3 – Prosumer problem solution Fig. 4 – The Smartbox prototype 1. USER INPUT FORM and DEMAND RESPONSE Demand response is an articulated program of actions that allows end-users to modify their load profiles by time-shifting local loads; the loads scheduling is determined in response to price signals, financial incentives, environmental conditions and a reliability signals. There is a large literature on the demand response program for domestic users: a focus is set on the decentralized scheme, where each prosumer autonomously takes decisions based on own requirements and aims. In order to define the optimal load scheduling, a service for load scheduling is offered to all those prosumers operating in the demand response program; data required are the preferential start and end time for each schedulable loads. In Fig.1 an user input form is showed; it refers to the case study in which eleven electrical loads are considered: seven of them are non-schedulable loads and include internal and external lightings, personal computers, TVs, a refrigerator, air conditioning; four of them are schedulable loads and include a washing machine, an electric oven, a dish washer and a charging station for electric vehicles. 2. PROSUMER PROBLEM SOLVER An optimization problem has been used to solve the prosumer problem, returning the optimal scheduling for the day ahead, so to minimizing the following objective function: subject to: The prosumer problem solver knows the hourly energy price, the non-schedulable load profiles forecast, the local solar and wind forecasts and the RES production forecast: with this data, the solver calculates the optimal scheduling so to minimize the electricity bill. 3. THE SMARTBOX Given the optimal daily scheduling which minimizes the electricity bill, the question is: how to act the loads scheduling? The Smartbox is a feasible home automation solution for prosumers operating in a demand response program. The Smartbox is a low-cost electronic device, web connected to the local area network; the aim of the Smartbox is to receive the solution of the prosumer problem and to act the optimal scheduling of electrical loads. A laboratory prototype of a Smartbox has been realized with an Arduino Mega 2560 equipped with a LCD display 4x20, an Ethernet Shield and a SIM Tapko KNX. When a solution is received, the Smartbox manages the switching-on and switching-off of schedulable loads; in particular, Arduino sends commands to the SIM Tapko KNX which converts them into KNX control frames, using the konnex protocol. In order to implement the optimal scheduling, the SIM Tapko KNX sends control frames to schedulable loads through the communication bus of the KNX home automation system. THE CASE STUDY and LABORATORY PROTOTYPE The case study is a private household equipped with a home automation system, situated in a rural area of Southern Italy. The electrical energy demand of local loads is satisfied by: 2kW photovoltaic plant; 2kW wind turbine; 1kWe/3kWt biomass boiler with Stirling Engine; 6kW 230V/50Hz connection to distribution grid; 3kW/4kWh lithium-ion battery energy storage system. The contract that the end user has subscribed with the local retailer ratifies an electricity cost from 8am to 7pm equals to 0.159€/kWh and from 7pm to 8am equals to 0.152€/kWh. The rated power, the work cycle duration, the period during which the work cycle must be executed and the option interruptible/non-interruptible for all schedulable loads have been obtained by statistical surveys about the preferential habits of typical end users. In order to demonstrate the effectiveness and the feasibility of the proposed Smartbox, a prototype has been realized and tested in the laboratory. Such a prototype has been tested in combination with: a software application which provides the user input form (see Fig. 1) ; a prosumer problem solver consisting in a personal computer with Matlab (see Fig. 2) which returns the prosumer problem solution (see Fig.3); a demonstration panel which represents a private household equipped with a Smartbox prototype (see Fig. 4) and a home automation system (see Fig. 5). The optimal scheduling calculated by Matlab is sent via the local area network to the Smartbox; the Smartbox is WIFI connected to the local area network. NUMERICAL RESULTS An example of prosumer problem solution is illustrated in Fig. 6: the red circle is the user habit, the green circle is the optimal scheduling, the blu circle is the coincidence of the user habit and the optimal scheduling. The schedulable loads are time-shifted according to the user input data. For example, the user habits schedule the dish washer as a unique time-slot long two hours; it starts at 20:00 and ends at 22:00; on the contrary, the optimal solution schedules the dish washer in two separate time-slots where the first time-slot starts at 20:00 and ends at 21:00 while the second starts at 23:00 and ends at 24:00. Similarly, the user habits schedule the washing machine from 21:00 to 23:00 and the electric oven from 18:00 to 19:00; on the contrary, the optimal solution schedules the washing machine from 9:00 to 10:00 and from 12:00 to 13:00 whereas the electric oven from 13:00 to 14:00. Fig. 7 shows the previous load profile and the new load profile, by the grid point of view. In particular, when adopting the user habits, the electric energy absorbed from the grid is 10.43kWh and the electricity cost is 1.60€; when adopting the optimal solution, the electric energy absorbed from the grid decreases to 6.76kWh and the cost reduces to 1.04€. Fig. 7 also shows a relevant load peak shaving. Fig. 7 also illustrates the new load profile with storage that is the user profile obtained when the 3kW/4kWh battery energy storage is adopted; due to the higher rate of self-consumption, the bill further reduces of 0.12€. Fig. 6 – Prosumer problem solver Fig. 5 – Demonstration panel (front side in top, back side in bottom) Fig. 7 – Prosumer problem solver