Distributed Transactive Coordination of Residential Communities Aiming at Fulfilling Households’ Preferences

Abstract

Transactive energy (TE) provides joint market and control functionality to manage distributed energy resources (DERs) in distribution networks. This work develops a real-time TE management framework that allows residential customers to actively join in the real-time transactive market with fulfilling households' preferences including comfort, economical energy consumption, and privacy-preserving. In this regard, first, a user-friendly algorithm is developed to calculate the real-time willingness to pay (bid) for electric vehicles (EVs) and heating, ventilation, and air conditioning (HVAC) units considering customers' preferences and concerns. Then, to preserve the privacy of households, the centralized market-clearing problem to maximize social welfare is decomposed into several subproblems using the alternating direction method of multipliers (ADMM) approach. Also, closed-form solutions to all subproblems are derived to simplify implementation and mitigate the computational complexity instead of solving optimization subproblems directly. This model is then implemented in a case study with several numbers of smart homes. The numerical results illustrate that the proposed distributed transactive model not only satisfies households' comfort preferences but also decreases the average charging cost of EV batteries by 40% compared to the uncontrolled charging model. Further, the results show that our proposed model significantly mitigates the computational burden of the transactive market clearing problem compared to the centralized approach and the distributed approach without closed-form solutions.

A scheduling framework for a multi‐agent active distribution network in presence of renewable energy sources

“…In this figure, the maximum amount of imported or exported active and reactive powers between the DN and the UG is determined with "Data Tips." This scheduling is calculated by the DN based FIGURE 5 The hourly price of imported power from the upstream grid, both active and reactive (𝜆 UG t and 𝜅 UG t ).…”

“…Due to the steadily increasing use of renewable energy sources (RESs) such as wind turbine (WT) and photovoltaic (PV), it is expected that MAADN's agents will face some technical problems such as overvoltage and imbalances in supply and demand [3,4]. To benefit from the full capacity of RESs in a network, especially when their penetration level is high, a comprehensive scheduling framework that can model and manage a transactive energy market between RES owners is required [5]. In this regard, several operational scheduling frameworks have been presented till now.…”