The motivation for this paper is the enhanced role of power generation prediction in power plants and power systems in the smart grid paradigm. The proposed approach addresses the impact of the ambient temperature on the performance of an open cycle gas turbine when using the Kalman Filter (KF) technique and the power-temperature (P-T) characteristic of the turbine. Several Kalman Filtering techniques are tested to obtain improved temperature forecasts, which are then used to obtain output power predictions. A typical P-T curve of an open-cycle gas turbine is used to demonstrate the applicability of the proposed method. Nonlinear and linear discrete process models are studied. Extended Kalman Filters are proposed for the nonlinear model. The Time Varying, Time Invariant, and Steady State Kalman Filters are used with the linearized model. Simulation results show that the power generation prediction obtained using the Extended Kalman Filter with the piecewise linear model yields improved forecasts. The linear formulations, though less accurate, are a promising option when a power generation forecast for a small-term and short-term time window is required.

The increasing penetration of electrical vehicles (EVs), on the way to decarbonizing the transportation sector, presents several challenges and opportunities for the end users, the distribution grid, and the electricity markets. Uncontrollable EV charging may increase peak demand and impact the grid stability and reliability, especially in the case of non-interconnected microgrids such as the distribution grids of small islands. On the other hand, if EVs are considered as flexible loads and distributed storage, they may offer Vehicle to Grid (V2G) services and contribute to demand-side management through smart charging and discharging. In this work, we present a study on the penetration of EVs and the flexibility they may offer for services to the grid, using a genetic algorithm for optimum valley filling and peak shaving for the case of a non-interconnected island where the electricity demand is several times higher during the summer due to the influx of tourists. Test cases have been developed for various charging/discharging strategies and mobility patterns. Their results are discussed with respect to the current generating capacity of the island as well as the future case where part of the electricity demand will have to be met by renewable energy sources, such as photovoltaic plants, in order to minimize the island’s carbon footprint. Higher EV penetration, in the range of 20–25%, is enabled through smart charging strategies and V2G services, especially for load profiles with a large difference between the peak and low demands. However, the EV penetration and available flexibility is subject to the mobility needs and limited by the population and the size of the road network of the island itself rather than the grid needs and constraints. Limitations and challenges concerning efficient V2G services on a non-interconnected microgrid are identified. The results will be used in the design of a smart charging controller linked to the microgrid’s energy management system.

The aim of this article is to highlight the impact of a periodic power source, such as a tidal turbine, on the operation and sizing of an autonomous hybrid microgrid with photovoltaic panels and storage. The technique of hill climbing (repeated local search) is used to find the optimum combination of Renewable Energy Sources (RES) and storage units with respect to the required capital cost for various load curves and weather conditions. To model the operation of the microgrid devices, analytical and phenomenological models, have been used, which take into account the specifications of actual commercial devices. Six different case studies are presented, with and without a tidal generator, which are based on six different sets of electrical consumption data corresponding to the Euripus campus of the National & Kapodistrian University of Athens (NKUA) in Psachna, Evia, Greece, and respective meteorological and tidal current data from the region. The results show that tidal energy may be used in a RES microgrid, where applicable, to satisfy the base load requirements, leading to a reduction in installed capacities of intermittent RES and storage, accompanied with cost reduction, especially in cases where a high load factor is observed or may be achieved, through demand response mechanisms. Such a hybrid microgrid configuration may be appropriate for regions where low velocity tidal and marine currents exist along with substantial solar and/or wind energy potential, such as the Mediterranean coast line and islands.

The purpose of this work is the design and the development of a low cost automated storage and retrieval system (AS/RS) appropriate for small and medium size companies. A market research was first carried out and existing systems were analyzed to determine the specifications of the new AS/RS. The motion of the system is based on three AC motors one for each direction of motion X, Y and Z controlled through a PLC. The control of X and Y motors along the length and the height of a row of shelves, respectively, is done with an inverter and an incremental encoder. The control software and the human machine interface have been designed in such a way that they can be customized according to the existing ERP. A prototype of a shelf system has been built and a demo version of the proposed AS/RS has been constructed. Preliminary testing of the system has been carried out with satisfactory results.