Wind power forecasting using historical data and artificial neural networks modeling

One of the main parameters affecting the reliability of the renewable energy sources (RES) system, compared to the local conventional power station, is the ability to forecast the RES availability for a few hours ahead. To this end, the main objective of this work is the prognosis of the mean, maximum and minimum hourly wind power (WP) 8hours ahead. For this purpose, Artificial Neural Networks (ANN) modeling is applied. For the appropriate training of the developed ANN models hourly meteorological data are used. These data have been recorded by a meteorological mast in Tilos Island, Greece. For the evaluation of the developed ANN forecasting models proper statistical evaluation indices are used. According to the results, the coefficient of the determination ranges from 0.285 up to 0.768 (mean hourly WP), from 0.227 up to 0.798 (maximum hourly WP) and from 0.025 up to 0.398 (minimum hourly WP). Furthermore, the proposed forecasting methodology shows that is able to give sufficient and adequate prognosis of WP by a wind turbine in a specific location 8 hours ahead. This will be a useful tool for the operator of a RES system in order to achieve a better monitoring and a better management of the whole system

Minimum long-term cost solution for remote telecommunication stations on the basis of photovoltaic-based hybrid power systems

In the case of the telecommunication (T/C) services' expansion to rural and remote areas, the market generally responds with the minimum investments required. Considering the existing situation, cost-effective operation of the T/C infrastructure installed in these regions (i.e. remote T/C stations) becomes critical. However, since in most cases grid-connection is not feasible, the up-to-now electrification solution for remote T/C stations is based on the operation of costly, oil consuming and heavy polluting diesel engines. Instead, the use of photovoltaic (PV)-based hybrid power stations is currently examined, using as a case study a representative remote T/C station of the Greek territory. In this context, the present study is concentrated on the detailed cost-benefit analysis of the proposed solution. More precisely, the main part of the analysis is devoted to develop a complete electricity production cost model, accordingly applied for numerous oil consumption and service period scenarios. Note that in all cases examined, zero load rejections is a prerequisite while minimum long-term cost solutions designated are favorably compared with the diesel-only solution. Finally, a sensitivity analysis, demonstrating the impact of the main economic parameters on the energy production cost of optimum sized PV-diesel hybrid power stations, is also provided.Telecommunication station Photovoltaic-based hybrid system Cost-benefit analysis

Techno-economic comparison of energy storage systems for island autonomous electrical networks

The oil-dependent electricity generation situation met in the Aegean Archipelago Islands is in great deal determined by increased rates of fuel consumption and analogous electricity production costs, this being also the case for other island autonomous electrical networks worldwide. Meanwhile, the contribution of renewable energy sources (RES) to the constant increase recorded in both the Aegean islands' annual electricity generation and the corresponding peak load demand is very limited. To compensate the unfavorable situation encountered, the implementation of energy storage systems (ESS) that can both utilize the excess/rejected energy produced from RES plants and improve the operation of existing thermal power units is recommended. In the present study, a techno-economic comparison of various RES-ESS configurations supported by the supplementary or back-up use of existing thermal units is undertaken. From the results obtained, the shift of direction from the existing oil-dependent status to a RES-based alternative in collaboration with certain storage technologies entails - apart from the clear environmental benefits - financial advantages as well.Techno-economic comparison Electricity generation Energy storage Autonomous electrical network Renewable energy sources

TILOS –Technology Innovation for the Local Scale Optimum Integration of Battery Energy Storage –The Project Experience So Far

<p>TILOS is an Innovation Action EU-funded project under the Local/Small Scale Storage Call of Horizon 2020, engaging a total of 15 partners. The project aims to demonstrate the optimal integration of local scale energy storage in a fully-operated, smart island microgrid that will also communicate with a main electricity grid.</p> <p>The main objective of the project will be the development and operation of a prototype battery storage system, based on NaNiCl2 batteries, provided with an optimum, real-environment smart grid control system and coping with the challenge of supporting multiple tasks, ranging from microgrid energy management, maximization of RES penetration and grid stability, to export of guaranteed energy amounts and provision of ancillary services to the main grid. The battery system will support both stand-alone and grid-connected operation, while proving its interoperability with the rest of microgrid components, including demand side management aspects and distributed, residential heat storage in the form of domestic hot water.</p> <p>TILOS project addresses the high-priority area of island regions. In doing so, apart from Tilos island, TILOS also engages Pellworm, La Graciosa and Corsica, aiming to create an island platform that will enable transfer of technological experience. Finally, by also addressing social issues, through public engagement, and by developing novel business models and policy instruments, TILOS puts emphasis on the market diffusion of both battery storage systems and the integrated energy solution implemented on the island of Tilos.</p> <p>Having already covered the fist year of project implementation, the aim of this paper is to give an overall presentation of the TILOS project and at the same time illustrate the main accomplishments and issues arising during this early stage. Furthermore, the current work aims to also reflect upon the realization of an actual, demonstration project and elaborate on the application prospects deriving from the project successful implementation.  </p

Topical 2.0% dorzolamide vs oral acetazolamide for prevention of intraocular pressure rise after neodymium:YAG laser posterior capsulotomy

Objective: To compare the efficacy and safety of topical 2.0% dorzolamide hydrochloride with oral acetazolamide in preventing intraocular pressure (IOP) rise following neodymium:YAG (Nd:YAG) laser posterior capsulotomy. Design: A prospective,randomized, double-masked, placebo-controlled study. Patients: Two hundred ten patients undergoing Nd: YAG laser posterior capsulotomy. Intervention: Pretreatment with dorzolamide, acetazolamide, or placebo. Dorzolamide administration as a single drop (1 drop approximate to 20 mu L) 1 hour before capsulotomy. Acetazolamide administration as a single dose of 125 mg orally 1 hour before capsulotomy. Results: At first and third hour postoperatively, IOPs and IOP changes from baseline were significantly (P&lt;.001) higher in the placebo group than in the dorzolamide or acetazolamide group. At the same time, IOPs and IOP changes from baseline were similar (P&gt;.50) in the dorzolamide and acetazolamide groups. No patient treated with dorzolamide or acetazolamide experienced an IOP higher than 30 mm Hg after capsulotomy, but 15.7% of patients receiving placebo had an IOP above this level (P&lt;.001). Of patients receiving placebo, 5.7% experienced IOP higher than 35 mm Hg. No serious side effects were recorded in any of the studied patients. Conclusion: Topical 2.0% dorzolamide and oral acetazolamide, given prophylactically as a single administration 1 hour before Nd:YAG laser posterior capsulotomy, have comparable high efficacy and safety in preventing IOP elevation following this procedure