Date of Award

May 2019

Degree Type


Degree Name

Master of Science



First Advisor

Lingfeng Wang

Committee Members

Lingfeng Wang, Chiu Tai Law, Guangwu Xu




Most community systems with large commercial buildings have heating, ventilation and air conditioning systems. In this case, EHs (energy hubs) can be formed in these communities in order to maximize the utilization of energy. The concept of energy hub was proposed to facilitate the synergies among different forms of energy carriers. Under the new electricity market environment, it is of great significance to build a win-win situation for prosumer and the hub manager at the community level without bringing extra burden to the utility grid. A set of economic and control mechanisms that allows the dynamic balance of supply and demand across the entire electrical infrastructure using value as a key operational parameter. With the increasing penetration of distributed generators and flexible loads in our communities, they are also bringing great intermittency and stochasticity to the power grid. It is very important to maintain the balance between the energy resources and loads to maximize the social welfare. To address the negative impacts of intermittent renewable energy sources, a bilevel programming method to make a day-ahead optimization has been proposed in this thesis. For the upper layer, hub manager seeks ways to minimize their transactive cost of buying electricity and gas from the utility to satisfy load demand, it gives buying prices of electricity and heat of load after optimization to every prosumer in this energy hub. On the other hand, the prosumer using the given prices to do the optimized dispatch of their own then get their outputs in each hour while keeping the profits maximized. Ultimately, the optimized prices of this community are formed. We use Karush–Kuhn–Tucker (KKT) condition to transfer the proposed problem into a mixed integer linear problem, and it is solved by MATLAB software with intlinprog solver. The results validate the effectiveness and feasibility of this solution.

Available for download on Friday, June 12, 2020