Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approach

In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competitive market, considering a time horizon of one week. The proposed approach is based on the combination of particle swarm optimization and adaptive-network based fuzzy inference system. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications, to demonstrate its effectiveness regarding forecasting accuracy and computation time. Finally, conclusions are duly drawn. © 2011 Elsevier Ltd. All rights reserved

Risk-Based Decision Support Model for the Optimal Operation of a Smart Energy Distribution Company for Enabling Emerging Resources

In this paper, a risk-based decision support model is developed for a smart energy distribution company, enabling emerging resources like renewable energy sources, electric vehicles and demand response programs in a holistic approach. Because of the inherent uncertainties of these emerging resources, the conditional value-at-risk (CVaR) method is adopted to restrict the distribution company’s risk. A risk aversion parameter sensitivity analysis is also provided on the optimal operation of the smart energy distribution company. The proposed model is thoroughly tested on a 15-bus distribution grid system, and the numerical results prove the effectiveness of the model in risk management

Modeling Local Energy Market for Energy Management of Multi-Microgrids

The diffusion of distributed energy resources (DERs) has changed the supply-demand balance of power systems. One option to modernize the management of the electricity distribution is to operate the distribution system with interconnected micro-grids (MGs). However, the MG participation in wholesale energy and ancillary service markets creates several challenges in the interactions among the energy market managing entities. To solve these problems, local energy markets (LEMs) have been proposed, where the MGs can trade energy with each other under the management of the LEM manager (LEMM) to minimize their operation cost. In this paper, a local energy market is modeled for multi-MGs (MMGs) to minimize the operation cost of MGs individually and their social welfare in cooperation with each other. In such model, the optimal scheduling of the DERs in each MG is done through the market clearing process. To investigate the effectiveness of the proposed approach, the local energy market is applied to a distribution network with three MGs

Energy management strategy in dynamic distribution network reconfiguration considering renewable energy resources and storage

© 2010-2012 IEEE. Penetration of renewable energy sources (RESs) and electrical energy storage (EES) systems in distribution systems is increasing, and it is crucial to investigate their impact on systems' operation scheme, reliability, and security. In this paper, expected energy not supplied (EENS) and voltage stability index (VSI) of distribution networks are investigated in dynamic balanced and unbalanced distribution network reconfiguration, including RESs and EES systems. Furthermore, due to the high investment cost of the EES systems, the number of charge and discharge is limited, and the state-of-health constraint is included in the underlying problem to prolong the lifetime of these facilities. The optimal charging/discharging scheme for EES systems and optimal distribution network topology are presented in order to optimize the operational costs, and reliability and security indices simultaneously. The proposed strategy is applied to a large-scale 119-bus distribution test network in order to show the economic justification of the proposed approach

Electrochemical treatment of leachates from sanitary landfills

The electrochemical treatment of leachate samples from a Portuguese intermunicipal sanitary landfill was carried out using anodic oxidation. The treatment was performed in a pilot plant that possesses an electrochemical cell, with boron-doped diamond electrodes, working in batch mode with recirculation. The influence of the applied current density and the flow rate on the performance of the electrochemical oxidation was investigated. Current density was decreased by steps, during the degradation, in order to study this effect on the efficiency of the process. For the assays run at equal flow rate and initial current intensity, chemical oxygen demand (COD) removal seems to depend mainly on the charge passed and the variation of the current density during the anodic oxidation process can reduce the energetic costs. An increase in the recirculation flow rate leads to an increase in the organic load removal rate and a consequent decrease in the energetic costs, but it decreases the nitrogen removal rate. Also, the bias between dissolved organic carbon and COD removals increases with flow rate, indicating that an increase in recirculation flow rate decreases the mineralization index

Impact of a 1755-like tsunami in Huelva, Spain

Abstract. Coastal areas are highly exposed to natural hazards associated with the sea. In all cases where there is historical evidence for devastating tsunamis, as is the case of the southern coasts of the Iberian Peninsula, there is a need for quantitative hazard tsunami assessment to support spatial planning. Also, local authorities must be able to act towards the population protection in a preemptive way, to inform “what to do” and “where to go” and in an alarm, to make people aware of the incoming danger. With this in mind, we investigated the inundation extent, run-up and water depths, of a 1755-like event on the region of Huelva, located on the Spanish southwestern coast, one of the regions that was affected in the past by several high energy events, as proved by historical documents and sedimentological data. Modelling was made with a slightly modified version of the COMCOT (Cornell Multi-grid Coupled Tsunami Model) code. Sensitivity tests were performed for a single source in order to understand the relevance and influence of the source parameters in the inundation extent and the fundamental impact parameters. We show that a 1755-like event will have a dramatic impact in a large area close to Huelva inundating an area between 82 and 92 km2 and reaching maximum run-up around 5 m. In this sense our results show that small variations on the characteristics of the tsunami source are not too significant for the impact assessment. We show that the maximum flow depth and the maximum run-up increase with the average slip on the source, while the strike of the fault is not a critical factor as Huelva is significantly far away from the potential sources identified up to now. We also show that the maximum flow depth within the inundated area is very dependent on the tidal level, while maximum run-up is less affected, as a consequence of the complex morphology of the area

“There's very little that you can do other than refer them to the doctor if you think they've got postnatal depression”: Scoping the potential for perinatal mental health care by community pharmacists: Community pharmacists and perinatal mental health

Background: Twenty percent of women in the UK develop perinatal mental health (PMH) problems, which have widespread effects on maternal and child health. Community pharmacists are ideally placed to identify PMH problems and refer to other trained healthcare professionals. Objective: This study explored community pharmacists’ attitudes, current counselling practices, and barriers to providing mental health advice to perinatal women. Methods: A qualitative focus group study was performed virtually with community pharmacists (n = 11), working in urban settings across London. A topic guide was used to cover current counselling practice, barriers to and confidence in counselling women, and thoughts on potential pharmacist-led perinatal mental health services. The focus groups were recorded, transcribed, and analysed using thematic analysis. Results: Three themes were identified: Doing Mental Health Care; Willing, but Unable; and Introspection and reflection, which were related through a central organising concept of ‘Perinatal mental health care as a new frontier for community pharmacy’. It was found that while community pharmacists provide mental health advice to perinatal women and their partners, they lacked confidence, which was related to a lack of knowledge and inadequate training opportunities. Organisational barriers were identified including a lack of a formal referral pathway to existing mental health services and other trained healthcare professionals. Perceptions of opportunities and recommendations for service improvement and change were also garnered. Conclusion: This study demonstrates community pharmacists have a potential role within community mental healthcare in identification of PMH problems and providing appropriate advice and support. Upskilling community pharmacists in mental health should be considered to increase knowledge and confidence while formal referral pathways to other trained healthcare professionals and existing services should be established and made available to pharmacists

Short-term wind power prediction based on extreme learning machine with error correction

Introduction: Large-scale integration of wind generation brings great challenges to the secure operation of the power systems due to the intermittence nature of wind. The fluctuation of the wind generation has a great impact on the unit commitment. Thus accurate wind power forecasting plays a key role in dealing with the challenges of power system operation under uncertainties in an economical and technical way. Methods: In this paper, a combined approach based on Extreme Learning Machine (ELM) and an error correction model is proposed to predict wind power in the short-term time scale. Firstly an ELM is utilized to forecast the short-term wind power. Then the ultra-short-term wind power forecasting is acquired based on processing the short-term forecasting error by persistence method. Results: For short-term forecasting, the Extreme Learning Machine (ELM) doesn’t perform well. The overall NRMSE (Normalized Root Mean Square Error) of forecasting results for 66 days is 21.09 %. For the ultra-short term forecasting after error correction, most of forecasting errors lie in the interval of [−10 MW, 10 MW]. The error distribution is concentrated and almost unbiased. The overall NRMSE is 5.76 %. Conclusion: The ultra-short-term wind power forecasting accuracy is further improved by using error correction in terms of normalized root mean squared error (NRMSE)

Inner and minimum constraint adjustment of marine gravity data

A programme for marine gravity data validation and adjustment is presented-VALDAMA. The aim of the programme is to provide a complete user-friendly system for marine gravity data validation and adjustment that enables the user to define all intervening parameters. The programme is written in standard C and has the possibility of solving for three different types of adjustment: inner constraint, constraint and minimum constraint and allows the user to define the stochastic model. It also has the ability to detect and adjust individual sub-networks, which may occur in regional applications, where track network connectivity fails. VALDAMA uses a parameter file in which the validation parameters, adjustment method and stochastic model are defined. The programme calculates the main statistical parameters and presents the results in spreadsheet format compatible with most common computer office tools. A test case is presented for marine gravity data in the North-East Atlantic Ocean. The complete validation and adjustment of more than 190,000 gravity observations are presented and from an analysis of several adjustment possibilities, it was concluded that inner constraint adjustment may give unpredictable results for global gravity data and that minimum constraint would be the preferred solution.Unidad Deptal. de Astronomía y GeodesiaFac. de Ciencias MatemáticasTRUEpu