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    A home energy management system with an integrated smart thermostat for demand response in smart grids
    (Elsevier Ltd, 2021) Duman, Anıl Can; Erden, Hamza Salih; Gönül, Ömer; Güler, Önder
    Smart thermostats and home energy management systems (HEMSs) are generally studied separately. However, their joint use can provide a greater benefit. Therefore, this study primarily aims to combine a smart thermostat with a HEMS. The mixed-integer linear programming (MILP)-based HEMS performs day-ahead load scheduling for cost-minimization and provides optimal demand response (DR) and photovoltaic (PV) self-consumption, and the fuzzy logic-based thermostat aims efficient DR of air-conditioning and maintenance of thermal comfort. In the first stage, unlike conventional fixed set-point thermostats, the proposed thermostat defines different set-points for each time interval, by fuzzifying input parameters of electricity prices, solar radiation, and occupant presence, to be used by HEMS. In the second stage, the HEMS schedules the operation of time-shiftable, thermostatically controlled, and power-shiftable (battery energy storage system (BESS), electric vehicle (EV)) loads. The HEMS considers bi-directional power flow between home, BESS, EV, and grid, as well as battery degradation to avoid unnecessary energy arbitrage. The simulation results show that a daily cost reduction of 53.2 % is achieved under time-of-use (TOU) and feed-in tariff rates of Turkey. AC cost is reduced by 24 % compared to conventional thermostats. In a future scenario of real-time pricing (RTP) and dynamic feed-in tariff, vehicle-to-grid (V2G) becomes possible. © 2020 Elsevier Ltd
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    Optimal sizing of PV-BESS units for home energy management system-equipped households considering day-ahead load scheduling for demand response and self-consumption
    (Elsevier, 2022) Duman, Anıl Can; Erden, Hamza Salih; Gönül, Ömer; Güler, Önder
    Today, selling electricity to the grid has lost its former profitability with reduced feed-in tariff (FiT) rates. This makes it crucial for prosumers to increase self-consumption and size their photovoltaic (PV) and battery energy storage system (BESS) units accordingly. Self-consumption can be increased through demand-side management (DSM) and an efficient DSM can be achieved using home energy management systems (HEMSs). Therefore, as its main contribution, this study proposes an optimal PV-BESS sizing model for HEMS-equipped prosumers considering day-ahead load scheduling-based DSM. Unlike other studies in the literature, the proposed model takes into account the determination of optimal PV tilt angle, load scheduling of all types of controllable appliances (time-shiftable, thermostatically controllable, power-shiftable), consideration of battery degradation, and vehicle-to-home (V2H) availability in the sizing procedure. First, the mixed-integer linear programming (MILP)-based model performs demand response (DR) and increased self-consumption to minimize the daily bill. Second, it simulates one year of HEMS operation and determines the net present value (NPV) of a PV-BESS configuration over the system lifetime. Finally, it repeats the same process for each combination of PV capacity-PV tilt angle-battery number and chooses the combination with the highest NPV as the optimal design. The simulations were conducted to find the required PV-BESS capacity for a HEMS-equipped household with average daily electricity consumption of 37.5 kWh in Istanbul, Turkey. The optimal configuration was found to be 3 kW PV without BESS at the tilt angle of 10 degrees. A techno-economic sizing comparison was made between households using and not using HEMS. The NPV of PV-BESS was found to be significantly higher with HEMS use ($2273) compared with that without HEMS use ($920). Lastly, a sensitivity analysis was performed based on rising electricity prices (+25%, +50%, +75%, +100%) and declining battery prices (-25%). The use of BESS became viable in Turkey even with +25% electricity prices or -25% battery prices. (c) 2022 Elsevier B.V. All rights reserved.
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    Survey- and simulation-based analysis of residential demand response: Appliance use behavior, electricity tariffs, home energy management systems
    (Sustainable Cities and Society, 2023) Duman, A. Can; Gönül, Ömer; Erden, Hamza Salih; Güler, Önder
    Residential demand response (DR) aims to stabilize the electricity grid by utilizing the flexibility of end-users. To this end, end-users are offered time-varying electricity prices and incentivized for load shifting. End-users can maximize bill reduction through automated load shifting using home energy management systems (HEMSs). Since HEMS is a new technology, the future DR potential of its mass use is unknown. Here, surveys can be very useful for gaining insight into future behaviour and preferences in using HEMS. Therefore, the objective of this study is twofold: (1) to understand appliance use behaviour, electricity tariff perception, and tendency towards HEMS-based DR participation, through a survey. And then, (2) to simulate the DR potential by entering survey responses into a HEMS optimization tool. The results show that 78% of the respondents are willing to engage in HEMS-based DR. This provides the potential to reduce the peak period consumption by 33%. However, the average bill savings achieved by HEMS owners is only 6.7%, which can hinder reaching this potential. Still, 21% of the HEMS owners save more than 10% on their bills. 8% save over 15%, and 3% over 20%. These can be the target audience of the future HEMS market and DR campaigns.