Multi-objective strategic offering of networked energy hubs in the day-ahead energy market according to uncertainty modelling

This paper presents the bidding strategy of networked flexible energy hubs in the energy market to consider the market clearing price layout. In this plan, the hubs present or offer their electrical, thermal and gas energy to the energy market. Then the market operator implements the market clearing price model in coordination with the network operator in different buses of energy networks. In other words, it determines the price of energy according to the offer of hubs and the amount of load in different buses. This model contains two-objective optimization models, where an objective function accounts for minimization of the expected operational cost of centralized generators in electrical, gas, and heating grids. Another objective function has been attended to maximize the desired profits of hubs in the mentioned market. The problem has been bounded to the optimum power flow scheme of the aforementioned systems, formulation of resource utilization, responsive loads, and storage units in the energy hub model, and limitation of hub flexibility. The ε-constraint scheme extracts the single-objective problem, and the fuzzy decision extracts a compromise solution. The penalty function method has been applied to simultaneously compute the energy price and the main variables of the problem. This scheme has been modelled on the basis of stochastic optimization and included uncertainties of load and renewable energy resources. Numerical outcomes indicate the performance of the offered layout in ameliorating economic, operational, and flexibility statuses in energy hubs and networks. A 32 % increase in the pressure drop is compared with the power flow studies, and it can diminish the energy losses of the entire system, voltage drop, and temperature via nearly 21 %, 18 %, and 7 %, respectively. The scheme can extract 100 % flexibility status for hubs.