Operating mechanism for profit improvement of a smart microgrid based on dynamic demand response

Abstract

A microgrid helps to reduce the consumption of fossil fuel by utilising distributed renewable energies (DREs). However, the stochastic nature of renewable energy makes it a big challenge for the microgrid operators to maximise the consumption of DREs while ensuring the balance between supply and demand. In order to improve the consumption of DREs and the profit of a microgrid efficiently, an operating mechanism consisting of two stages is proposed to dispatch DREs, responsive loads and plug-in hybrid electric vehicles (PHEVs) in a smart microgrid. In the first stage, we formulate the optimal unit commitment and the day-ahead time of use, which the operator concerns as a decentralised model. To address the model, the particle swarm optimisation algorithm and the interior point method are used, respectively, to minimise the operating cost and the electricity import. In the second stage, a dynamic incentive signal-based demand response for PHEVs is proposed to maximise the electricity export in the intra-day. Simulation studies are conducted on a smart microgrid, and the results have demonstrated that the proposed operating mechanism improves the consumption of DREs while satisfying the demand, meanwhile improves the average daily profit of the smart microgrid.

Coordinated integration of distributed energy resources in unit commitment

“…UC is a mixed-integer programming model. Methods have been developed to solve UC models, such as Lagrangian relaxation [62], particle swarm optimization [63][64][65] and genetic algorithm [66,67]. Now, we present the discussion on most of the optimization problems briefly in order to comprehend the advantages and disadvantages of UC methods.…”

Profit maximization in hybrid microgrid system incorporating demand response and plug in EV

“…8 The prosumers, who consume and generate energy, can generate their own profits by trading electricity at optimal level through demand response program. 9 Augmenting this, incorporating electric vehicle (EV) also maximizes the profit by intelligent scheduling 10 of charging/discharging period through which EV owner is also benefited. 11,12 Therefore, to attain a maximized profit, it is necessary to incorporate optimal operation of distributed generation (DG) resources 13,14 along with most suitable DR program where EV is effectively scheduled considering profit of grid operator and EV owner.…”

“…To promote the benefits is DR techniques among consumers and make them participate in this initiative, incentives are awarded to the consumers by the grid operators 8 . The prosumers, who consume and generate energy, can generate their own profits by trading electricity at optimal level through demand response program 9 . Augmenting this, incorporating electric vehicle (EV) also maximizes the profit by intelligent scheduling 10 of charging/discharging period through which EV owner is also benefited 11,12 .…”

Bi‐level equilibrium of energy retailer–smart energy hub game in integrated energy market

“…To investigate the performance index of a system through a real‐time electricity pricing scheme, an optimal control approach was formulated under a closed‐loop algorithm based on the DDESS. A two‐stage operating mechanism was proposed in [13] to improve the utilisation of distributed renewable energies and the profit of a microgrid. Ref.…”