Abstract
As a main fiexible resource, energy storage helps smooth the volatility of renewable generation and reshape the load profile. This paper aims to characterize the impact of energy storage unit on the economic operation of distribution systems in a geometric manner that is convenient for visualization. Posed as a multi-parametric linear programming problem, the optimal operation cost is explicitly expressed as a convex piecewise linear function in the MW/MWh parameter of the energy storage unit. Based on duality theory, a dual linear programming based algorithm is proposed to calculate an approximate optimal value function (OVF) and critical regions, circumventing the difficulty of degeneracy, a common challenge in the existing multi-parametric linear programming solvers. When the uncertainty of renewable generation is considered, the expected OVF can be readily established based on OVFs in the individual scenarios, which is scalable in the number of scenarios. The OVF delivers abundant sensitivity information that is useful in energy storage sizing. Leveraging the OVFs, a robust stochastic optimization model is proposed to determine the optimal MW-MWh size of the storage unit subject to a given budget, which gives rise to a simple linear program. Case study provides a clear sketch of the outcome of the proposed method, and suggests that the optimal energy-power ratio of an energy storage unit is between 5 and 6 from the economical perspective.

Abstract
This paper presents a novel mixed-integer second-order cone programming model to increase the photovoltaic (PV) hosting capacity and optimize the operation of distribution systems. The operational problem considers voltage control through the optimal operation of capacitors banks, substations' on-load tap changers, voltage regulators, and network reconfiguration with radial and closed-loop operation. The proposed formulation considers voltage-dependent models for loads and capacitor banks. The objective function maximizes the PV hosting capacity of the system. Numerical experiments are carried out using the 33-node system and results demonstrate the effectiveness of the proposed formulation to increase the penetration of PV sources, especially when the closed-loop operation is allowed, together with network reconfiguration.

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
Due to technological advances, the growing need for a decarbonized economy, and the desire to reduce urban air pollution, electric vehicles (EVs) are seen as promising developments for the progressive decarbonization of the transport sector. The potential for large scale integration of solar photovoltaic (PV) systems has not been explored fully, compared to other renewable energy uses in power systems. One of the proposed paths for the sustainable integration of EVs and solar exploitation in power systems involves the creation or installation of parking lots fitted with solar PV systems on their rooftops. This concept increases the reliability and robustness of the power system, as studies show that EVs are parked for the vast majority of the time. The EVs can then be optimally managed to assist the network in critical moments. The solar parking lot would then serve as a backup to manage the EVs' state-of-charge (SoC) which would guarantee the owners' comfort and help to accelerate the decarbonization of the economy. The present work presents a comprehensive survey of the state-of-the-art concepts of photovoltaic (PV) panels, EVs and batteries, and how the different associated technologies can be applied in the concept of solar parking lots.

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.