Abstract
This paper proposes an energy hub management model for residential, commercial, and industrial hubs, considering demand response programs (DRPs). The network configuration and AC optimal power flow (ACOPF) constraints have been applied to the model to prevent any unreal power transaction in the system. The cost due to environmental emissions has also been taken into account and the problem is modeled as a dynamic optimization problem, solved using the CPLEX solver in the GAMS software, interfaced with MATLAB/MATPOWER for the power flow analysis. Besides, the problem is studied in two cases as coordinated and uncoordinated operation modes to investigate their impacts on the operating cost, emission, and power losses. The obtained results show that the coordinated operation would lead to reducing the operating cost, power losses, and emission. Moreover, the impacts of the coordinated and uncoordinated operation modes on the load demand-supply under contingent events and disconnection from the upstream grid are assessed. The results derived from the simulation verify the superior performance of the coordinated operation. It is also noted that the DRP leads to mitigating the operating costs.

Abstract
The combination of consumer owned Distributed Energy Resources, new Information and Communication Technologies (ICT), as well as changes to the national electricity regulations have created new opportunities for consumer engagement in the electricity sector. In this paper, this combination of technologies and regulations is examined in the Portuguese context. The new regulations dealing with self-consumption from prosumers are combined with smart contracts and distributed ledger technology to formulate an automated energy trading system for residential end-users in local energy markets. Results show that including prosumers in the local energy market brings significant benefits to all market participants. Additionally, results show that the newly created regulatory role of a Market Facilitator is beneficial to these type of local energy exchanges.

Abstract
Due to recent advances in power electronic systems, direct current (DC) microgrid (MG) topology is considered as a promising solution to unite pollution-free renewable energy sources and DC loads. This paper investigates the issue of finite-time robust adaptive stability and tracking issue of a nonlinear direct current (DC) microgrid (MG) comprising a buck converter, linear resistive loads, and nonlinear constant power loads (CPLs). The developed approach is based on a sliding mode controller (SMC) and a nonlinear and nonsingular sliding surface. It is proved that the tracking error converges to zero in a finite-time in the presence of matched disturbance input and uncertainties. The novel controller manipulates the buck converter of the source side to regulate the DC bus voltage by counteracting the destabilizing effect of CPLs and disturbances. Further, the finite value of the convergence time is presented and the effects of the SMC parameter on the stability and transient performance are evaluated. Lastly, numerical simulations are conducted to illustrate the merits of the developed control approach in the viewpoints of fast reference tracking and robust stability.

Abstract
This paper investigates the issue of robust frequency regulation of single-area alternating current (AC) power applications. The robust stability and disturbance rejection performance criteria are considered in the design procedure of an output feedback controller. Four cases of single-area AC power systems, which comprise the different types of governors and generators, are considered. These components are modeled by first- and second-order transfer functions and exhibit non(minimum) phase behavior. Based on the uncertain linear transfer functions of the governors and generators, the resilient controller against uncertainties and unknown power load demand is designed numerically. Several numerical simulations are carried out to show the merits of the developed controller. Also, the effects of different types of governors and generators on the AC MG frequency deviation are also investigated.

Abstract
Energy hubs are defined as energy systems that receive various energy carriers and convert or store them to serve different types of load demands. Stochastic scheduling methods can be used to optimally manage the energy hubs. However, in the stochastic approach, the main deficiency is that there exists the risk of experiencing the worst scenario, so a viable solution is needed to address this possibility. This paper addresses the two-stage operation scheduling of energy hubs based on the worst scenarios. A novel robust scenario-based approach is proposed and compared to the stochastic approach. A robustness parameter is defined to control the compromise between the expected operating costs and the model robustness. It can be seen that the model is robust against all the realization of worst scenarios.

Abstract
In this paper, an advanced control of a DC Micro Grid (MG)-connected Proton Exchange Membrane (PEM) Fuel Cell connected with a DC/DC boost converter is addressed to achieve an overall appropriate control scheme in the power management system. In this context, a nonlinear PEM Fuel Cell stack, which is the main source of the continuous power to the load, is modelled and controlled by an optimal Linear Parameter Varying (LPV) technique in the presence of uncertainties and variation in its operating parameters i.e. output current and temperature. To this end, a polytopic-LPV model is considered for nonlinear PEM Fuel Cell stack and sufficient conditions for designing a stabilizing continuous time LPV controller based on state feedback controlling law is derived in terms of Linear Matrix Inequality (LMI). On the other hand, a feedback linearization controller is developed simultaneously to control the duty cycle of the DC/DC boost converter, which is connected between the PEM Fuel Cell stack and the load, aiming to regulate the DC output voltage of the grid to an arbitrary and predefined reference value. The performance of the proposed approach and controllers are verified through simulation results.