Abstract-This paper introduces a scalable framework to coordinate the net load scheduling, sharing, and matching in a neighborhood of residential prosumers connected to the grid. As the prosumers are equipped with smart appliances, photovoltaic panels, and battery energy storage systems, they take advantage of their consumption, generation, and storage flexibilities to exchange energy with neighboring prosumers through negotiating on the amount of energy and its price with an aggregator. The proposed framework comprises two separate multi-objective mixed integer nonlinear programming optimization models for prosumers and the aggregator. Prosumers' objective is to maximize the comfort level and minimize the electricity cost at each instant of time, while aggregator intends to maximize its profit and minimize the grid burden by matching prosumers' supply and demand. The evolutionary nondominated sorting genetic algorithm-III (NSGA-III) is employed to generate a set of feasible nondominated solutions to the optimization problem of each individual prosumer and the aggregator. As a bilateral negotiation between each prosumer and the aggregator results in significant computational and communication overhead, a virtual power plant is introduced as an intermediator on behalf of all prosumers to proceed the negotiation with the aggregator in a privacy-preserving noncooperative environment, where no private information is shared. Hence, an automated negotiation approach is embedded in the framework, which enables the negotiators to reactively negotiate on concurrent power and price using private utility functions and preferences. To converge to an acceptable agreement, the negotiation approach follows an alternating-offer production protocol and a reactive utility value concession A. G. Azar was with the Department of Engineering, Aarhus University, 8000 Aarhus, Denmark, and is now with the Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby 2800, Denmark (e-mail:, agaz@dtu.dk). H. Nazaripouya is with the Winston Chung Global Energy Center, University of California, Riverside, CA 95251 USA (e-mail:, hamidn@ ucr.edu). B. Khaki, C.-C. Chu, and R. Gadh are with the Department of Mechanical Engineering, University of California, Los Angeles, CA 90095 USA (e-mail:, behnamkhaki@ucla.edu; peterchu@ucla.edu; gadh@ucla. edu). R. H. Jacobsen is with the Department of Engineering, Aarhus University, 8000 Aarhus, Denmark (e-mail:, rhj@eng.au.dk). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TII.2018.2867748 strategy. The effectiveness of the framework is evaluated by several economic and environmental assessment metrics through a variety of numerical simulations.
Azar et al. REF proposed a virtual power plant as an intermediary on behalf of a group of neighborhood prosumers to negotiate with the aggregator, where no private information of the prosumers was shared.
A Non-Cooperative Framework for Coordinating a Neighborhood of Distributed Prosumers
IEEE Transactions on Industrial Informatics
IEEE Transactions on Industrial Informatics
Computer Science