Multi-stage optimization for energy management and trading for smart homes considering operational constraints of a distribution network

Abstract

The increase in the uptake of distributed energy resources (DERs) makes the distribution network more complex. Inadequate management of these DERs may lead to escalated power transmission, potentially resulting in challenges within the distribution network and provoking degradation of critical assets like distribution transformers. The smart home has a home energy management system (HEMS) to schedule the DERs at the home level based on the objectives of the end-user. However, HEMS is not coordinated with the distribution network operators, which can cause different network issues at the distribution level. To mitigate this, effective management of DERs across different levels of the distribution network is essential. This paper introduces a four-stage optimization within a three-level coordination framework that aims to maximize benefits for all stakeholders. A mixed integer linear programming (MILP)-based HEMS is formulated in the first stage to perform home energy management effectively. At the aggregator level, in the second stage, a MILP-enabled peer-to-peer (P2P) trading mechanism is designed. At the same level, a third-stage loss of life optimization is performed pertaining to the optimal power status of the HEMS and P2P trading. In the last stage, a three-phase optimal power flow-based optimization is proposed to maintain the operational constraints of the unbalanced distribution network. Optimizing HEMS and P2P trading while addressing transformer limitations, our proposed method reduces peak power by 38.85%. The transformer life loss using P2P is only 0.00059%, while in HEMS, it is 0.62% per day. Additionally, our method substantially lowers electricity costs for P2P prosumers. Thus, our proposed method outperforms other existing mechanisms from both financial and physical network operation suitability perspectives.