A Decentralized Energy Trading Framework for Active Distribution Networks with Multiple-Microgrids under Uncertainty

Abstract

The ever-increasing need for more reliable power supply as well as cost-e ective and environmentally friendly utilization of distributed energy resources will result in the formation of Multiple Micro-Grids (MMGs) in the near future of distribution system. To reach this prospect, coordination among MMGs is necessary. Accordingly, this paper proposes a new non-hierarchical multi-level architecture for the optimal scheduling of Active Distribution Network (ADN) with MMGs. The proposed model is a decentralized decision making algorithm to optimally coordinate the mutual interaction between local optimization problems of ADN and MMGs. A non-hierarchical Analytical Target Cascading (ATC) method is presented to solve the local optimization problems in parallel. Also, the underlying risks of energy trading caused by renewable generation uncertainty are re ected in both the objective functions and the constraints of local optimization problem. The numerical results of modi ed IEEE 33-bus distribution test system containing two microgrids demonstrate the e ectiveness and merits of the proposed model.

A receding horizon data‐driven chance‐constrained approach for energy flexibility trading in multi‐microgrid distribution network

“…Each MG can act as a load or power supply that is connected to a node in the ADN. Hence, an ADN that comprises several MGs which can trade energy with each other is seen as a multi-microgrid distribution network [6]. There is a DSO in an ADN that manages energy trading to achieve an energy balance between supply and consumption in our proposed flexibility trading mechanism.…”

“…In such environments in which information privacy is an issue of vital importance, decentralized market mechanisms can act more efficiently than conventional centralized ones [6,7].…”

“…In this study, the flexibility provided by FLs is transacted among the end-users, aggregators and DSO. A fully decentralized energy trading framework based on a non-hierarchical analytical target cascading algorithm was applied in [6] to manage energy trading in ADNs among DSO and MGs. The literature contains several studies investigating uncertainty modelling in power systems as well as those that ignore the probabilistic nature of wind generation and loads which leads to deterministic optimization.…”

“…Furthermore, the great need for reliable, economic, and environmentally friendly energy supply leads to increasing growth in the formation of MicroGrids (MGs). In such environments in which information privacy is an issue of vital importance, decentralized market mechanisms can act more efficiently than conventional centralized ones [6, 7]. Additionally, centralized energy market mechanisms cannot provide energy that procured through flexible behaviour of resources such as FLs [4].…”

Reliability Evaluation of Power Systems Containing Ocean Thermal Energy Conversion Power Plants

“…Variation in the output power of the renewable resources including wind, solar, tidal, wave and so on is the main drawback of these clean energies and so many researches have been devoted to studying the effects of these resources on the different aspects of power systems [13][14][15][16][17][18][19][20]. The reliability evaluation of OTEC systems is not performed so far and so in this regard, the researches associated to the reliability assessment of other renewable resources such as wind, solar, wave, tidal and so on can be utilized.…”