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    A Fair Risk-Averse Stochastic Transactive Energy Model for 100% Renewable Multi-Microgrids in the Modern Power and Gas Incorporated Network
    (Institute of Electrical and Electronics Engineers, 2023) Daneshvar, Mohammadreza; Mohammadi-Ivatloo, Behnam; Zare, Kazem
    The ever-growing multi-vector systems along with the penetration of renewable energy sources (RESs) entail significant changes for shifting from centralized, isolated, and passive structures to potentially distributed, hybrid, and autonomous modern multi-vector energy grids (MVEGs). This paper proposes a transactive energy (TE) solution for the techno-environmental-economic operation of multi-carrier multi-microgrids (MCMs) with 100% RESs by co-optimizing power and gas grids. Indeed, TE is advanced for making a fair economic model by developing the free multi-energy sharing area (MESA) for MCMs to allow them to exchange energy with the aim of pursuing their technical, environmental, and economic goals. As 100% RESs bring severe uncertainties in the energy production sector, appropriately modeling such stochastic variations is a necessary step for obtaining realistic results in exploring the overall system. Thereby, the stochastic conditional value at risk (CVaR) technique is developed to model the risk of MCMs presence in energy interactions, in which scenario generation and reduction are performed by applying the seasonal autoregressive integrated moving average and fast forward selection methods. The problem is cast into a tractable mixed-integer linear programming by properly linearizing AC power flow and nonlinear gas equations that allows the system to extract confident results. The coupled structure of the modified IEEE 33-bus and 14-node gas systems is used as the test system for verifying the effectiveness of the proposed model. The results show the applicability of the proposed model in reliably integrating 100% RESs as well as procuring a fair condition for MCMs in the hybrid structure of the energy grid.
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    A novel transactive energy trading model for modernizing energy hubs in the coupled heat and electricity network
    (Elsevier Ltd, 2022) Daneshvar, Mohammadreza; Mohammadi-Ivatloo, Behnam; Zare, Kazem
    A high or full contribution of renewable energy resources (RERs) in future modern grids is inevitable due to a great need for developing an environmentally friendly society. In modernizing renewable-based energy hubs, optimal energy management has been rapidly challenged due to intermittences of RERs in multi-vector energy networks (MVENs) over recent years. This paper proposes an innovative peer-to-peer (P2P) energy trading model for energy management of multi-vector energy hubs to consider the unpredictability challenge of RERs. For this purpose, the transactive energy paradigm is used to advance a new sustainable energy sharing environment for creating time-to-time energy balance by enabling energy hubs to exchange energy with each other freely. The uncertainty quantification was conducted by applying an autoregressive integrated moving average for generating multiple scenarios and the fast forward selection method for reducing them to the plausible number in the stochastic programming process. The coupled IEEE 10-bus and 10-node district heating network was designated as the test system for analyzing the optimal energy management of the distributed hub energies. The results designated the effectiveness of the proposed transactive energy-based P2P energy trading model in providing momentous financial and technical benefits for community energy hubs in MVENs.