Microgrid and participant-centric residential demand response program and photovoltaic with battery-storage P2P energy trading for optimum energy management using MDULPS and PPBSD-ADMM

An innovative decentralized Residential Demand Response (DR) program offers an effective solution for efficient energy management to save cost for both the participants and the community Microgrid (MG) and facilitate peerto-peer (P2P) trading of excess energy of photovoltaic (PV) with battery energy storage system (BESS) between prosumers and consumers residing within a community. This study aims to optimally schedule home appliances, mitigate the detrimental externality effect on tariff rates among participants, select participants for demand reduction, select prosumers for buying energy in P2P energy trading, and protect the privacy of participants. This study aims to optimally schedule home appliances, mitigate the detrimental externality effect on tariff rates among participants, select participants for demand reduction, select prosumers for buying energy in P2P energy trading, and protect the privacy of participants. This novel approach combines the advantages of demand response under the multi-time of use (TOU) pricing and the incentive-driven demand reduction bidding mechanism under direct load control (DLC) to reduce electricity demand, minimize electricity costs for enrolled participants, and save cost for the community MG by offering a minimum incentive to participants. The integration of the Home Energy Management System (HEMS) and Advanced Metering Infrastructure (AMI) enables a dynamic and responsive energy management system, fostering a more active role for participants in optimizing their individual energy usage patterns and incentivizing participants to adjust their energy consumption based on a demand reduction bidding strategy. The detrimental externality effect on tariff rates is managed among participants with varying utilization levels through a multi-dynamic utilization level pricing scheme (MDULPS). This study utilizes a novel non-cooperative game design strategy, incorporating a Nash equilibrium approach to achieve the optimum schedule of smart home appliances and the selection of participants for demand reduction with the lowest possible demand reduction bids. The economically selection of preferred prosumer for buying energy considering consumer utility in P2P energy trading scheme is accomplished using Prosumer Preference Based Segmented Distributed Alternating Direction Method of Multipliers (PPBSD-ADMM). The proposed approaches for energy management and energy trading are more feasible in terms of preserving participants' privacy compared to other state-of-the-art strategies. Finally, analytical and simulation results show that the proposed demand response and P2P energy trading schemes are suitable and effective and have benefits with regards to prosumer cost savings of up to 54.55 %, consumer cost savings of up to 33.28 %, and MG cost savings of up to 34.65 %.