Experimental Testbed And Optimal Load Scheduling For Demand Response Management In Smart Grid

Despite the potential depletion of fossil fuels,the demand for energy is increasing with the continuous development of the global economy.The energy supply to meet demand is especially in the residential sector.Many countries are beginning to focus on the development of renewable energy.With the gradual penetration of renewable generation,only supply-side control is not able to.Demand Response(DR),as a technical measure for dispatching power demand,can effectively explore the potential of users and increase the flexibility of dispatching.This plays an important role in stabilizing the operation of the power grid.In this thesis,the residential load is taken as a research object,for which the following works are conducted:(1)This paper designs an experimental platform of demand side response management in smart grid.The platform which includes both hardware and software.The core of hardware is a smart plug.By integrating sensors,wireless communication devices and controllers into the processor,it can collect the electrical characteristics of the load and change the working mode of the load.In the software system,an electrical remote monitoring system is developed according to the data collected from the plug.At the same time,this article also tests the overall function of the experimental platform and achieves the expected results.(2)The optimal load scheduling problem under segmented incentives is studied.The segmented incentive mechanism is designed to invoke demand-side effort to offset the shortfall of supply.We target to schedule the user demand to jointly minimize the subsidy for users and the active power loss of the whole network.The problem is formulated as an nonconvex optimization problem with a equality constraint,and then the second-order cone relaxation technique to employed to relaxed the problem into a convex problem which can be solved by off-the-shelf toolboxes.Finally,a simulation experiment is conducted to verify the efficacy of the algorithm.(3)The online load scheduling problem under random environment is studied.In view of the fact that more and more uncertain renewable energy is taken in by the power grid and the residential electricity demand is also turning random,the theoretical study of load scheduling problem in the time domain will be further carried out.This paper designs an online control strategy based on Lyapunov optimization that minimizes the generator's long-term operating costs under the stochastic demand and renewable energy.