Abstract
The European Union aims to achieve a nearly zero energy balance in buildings by 2020. The present study takes into consideration the passive systems of the building, energy demand, and energy generated by the on-site photovoltaic and storage system, and how they interact in different scenarios. The study also considers the energy demand from the grid and the surplus of renewable energy. The software EnergyPlus was used and the parametric sensitivity simulation method was applied, taking into account blinds operation, ventilation strategies, HVAC operation schemes and battery storage capacity, in 96 scenarios. The results highlight that there is great variability between the considered scenarios, highlighting the importance of sizing methodologies for the passive systems and the use of optimized home management algorithms. It was found that the use of batteries with higher storage capacity increases the demand-supply from the on-site PV energy but decreases the amount of energy injected into the grid. The design of the PV and battery system based on yearly integrated simulations allows for an optimized solution. This study also emphasizes the importance of knowing the expected occupancy during the design phase, as a significant input to the sizing methodologies of the storage capacity and on-site generation.

Abstract
Accounting for the increasing uncertainties related to forecast of renewables is becoming an essential requirement while assessing the security of future power system scenarios. Project iTesla in the Seventh Framework Program (FP7) of the European Union (EU) tackles these needs and reaches several major objectives, including the development of a security platform architecture. In particular, the platform implements a stochastic dependence model to simulate a reasonable cloud of plausible 'future' states - due to renewable forecast - around the expected state, and evaluates the security on relevant states after sampling the cloud of uncertainty. The paper focuses on the proposed model for the uncertainty and its exploitation in power system security assessment process and it reports the relevant validation results. Copyright © 2019 Inderscience Enterprises Ltd.

Abstract
This paper presents a generic framework to evaluate and compare the quality of the uncertainties provided by probabilistic forecasts of power system state when used to perform security assessment for branch overloads. Besides exploiting advanced univariate and multivariate metrics that are traditionally used in weather prediction, the evaluation is complemented by assessing the benefits from exploiting probabilistic forecasts over the current practices of using deterministic forecasts of the system operating conditions. Another important feature of this framework is the provision of parameters tuning when applying flow probabilistic forecasts to perform security assessment for branch overloads. The quality and scalability of this framework is demonstrated and validated on recent historical data of the French transmission system. Although being developed to address branch overload problems, with proper adaptations, this work can be extended to other power system security problems.

Abstract
In this paper, a validation framework is proposed to evaluate the quality of uncertainty forecasts, when used to perform branch flow security assessment. The consistency between probabilistic forecasts and observations and the sharpness of the uncertainty forecasts is verified with advanced metrics widely used in weather prediction. The evaluation is completed by assessing the added value of exploiting uncertainty forecasts over the TSO current practices of using deterministic forecasts. For electric power industry, this proposed validation framework provides a way to compare the performance among alternative uncertainty models, when used to perform security assessment in power systems. The quality of the proposed metrics is illustrated and validated on historical data of the French transmission system.

Abstract
Variable-speed pump power storage is an innovative large-scale technology that is being deployed across the world. In addition to price arbitrage and provision of downward replacement reserve, its operational flexibility enables the provision of frequency restoration reserve (FRR) both in turbine and pump modes. This work proposes a bidding optimization strategy for the participation in the FRR market. The proposed framework encompasses a medium-term module to optimally allocate the yearly natural water inflows, representation of electrical and hydraulic losses in the water inflow/power curves, as well as forecasting techniques to predict market prices and natural water inflows. Moreover, it does not assume prior knowledge of the amount of activated FRR capacity band. An evaluation module is also proposed to replicate the real operation of the power plant and enables an accurate calculation of the revenue. A comparison between fixed and variable-speed Pump storage power (PSP) units participating in the Iberian electricity market presented an increase in revenue of almost 12%. Due to the low liquidity of the FRR market in Portugal, and the considerable capacity of the PSP unit, under some specific situations, it might be necessary to cap the size of the FRR bid to decrease the difference between the expected and realized revenue.

Abstract
This paper presents a multi-temporal approach for the energy scheduling and voltage/var control problem in a microgrid (MG) system with photovoltaic (PV) generation and energy storage devices (PV-battery MG) during islanded operation conditions. A MG is often defined as a low voltage (LV) distribution grid that encompasses distributed energy resources and loads that operate in a coordinated way, either connected to the upstream distribution grid or autonomously (islanded from the main grid). Considering the islanded operation of the MG during a given period, it is necessary to develop proper tools that allow the effective coordination of the existing resources. Such tools should be incorporated in the MG control system hierarchy in order to assure proper conditions for the operation of the autonomous MG in terms of active power, voltage and reactive power management. Energy storage devices are essential components for the successful operation of islanded MG. These devices have a very fast response and are able to absorb/inject the right amount of power. For the operation of the MG in islanding conditions during a longer period, it is necessary to integrate information related to the forecasting of loads and PV-based generation for the upcoming hours for which is intended to maintain MG in islanded operation. Therefore, this paper presents a tool to be integrated in the Microgrid Central Controller (MGCC) that is responsible to perform a multi-temporal optimal power flow (OPF) in order to schedule the active and reactive power within the MG for the next time intervals. © 2019, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.