Analysis of constructed wetland performance for irrigation reuse

Most of the wastewater treatment systems in small rural communities of the Cova da Beira region (Portugal) consist of constructed wetlands (CW) with horizontal subsurface flow (HSSF). It is believed that those systems allow the compliance of discharge standards as well as the production of final effluents with suitability for reuse. Results obtained in a nine-month campaign in an HSSF bed pointed out that COD and TSS removal were lower than expected. A discrete sampling also showed that removal of TC, FC and HE was not enough to fulfill international irrigation goals. However, the bed had a very good response to variation of incoming nitrogen loads presenting high removal of nitrogen forms. A good correlation between mass load and mass removal rate was observed for BOD5, COD, TN, NH4-N, TP and TSS, which shows a satisfactory response of the bed to the variable incoming loads. The entrance of excessive loads of organic matter and solids contributed for the decrease of the effective volume for pollutant uptake and therefore, may have negatively influenced the treatment capability. Primary treatment should be improved in order to decrease the variation of incoming organic and solid loads and to improve the removal of COD, solids and pathogenic. The final effluent presented good physical-chemical quality to be reused for irrigation, which is the most likely application in the area.

Cork industry wastewater characterization assessment of the biodegradability, reuse and of the relationship between BOD, COD and tannins with TOC

Cork processing involves a boiling step to make the cork softer, which consumes a high volume of water and generates a wastewater with a high organic content, rich in tannins. An assessment of the final wastewater characteristics and of the boiling water composition along the boiling process was performed. The parameters studied were pH, color, total organic carbon (TOC), chemical and biochemical oxygen demands (COD, BOD5, BOD20), total suspended solids (TSS), total phenols and tannins (TP, TT). It was observed that the water solutes extraction power is significantly reduced for higher quantities of cork processed. Valid relationships between parameters were established not only envisaging wastewater characterization but also to provide an important tool for wastewater monitoring and for process control/optimization. Boiling water biodegradability presented decreasing values with the increase of cork processed and for the final wastewater its value is always lower than 0.5, indicating that these wastewaters are very difficult to treat by biological processes. The biodegradability was associated with the increase of tannin content that can rise up to 0.7 g/L. These compounds can be used by other industries when concentrated and the clarified wastewater can be reused, which is a potential asset in this wastewater treatment.

Distributed MPC for Thermal Comfort and Load Allocation with Energy Auction

This paper presents a distributed predictive control methodology for indoor thermal comfort that optimizes the consumption of a limited shared energy resource using an integrated demand-side management approach that involves a power price auction and an appliance loads allocation scheme. The control objective for each subsystem (house or building) aims to minimize the energy cost while maintaining the indoor temperature inside comfort limits. In a distributed coordinated multi-agent ecosystem, each house or building control agent achieves its objectives while sharing, among them, the available energy through the introduction of particular coupling constraints in their underlying optimization problem. Coordination is maintained by a daily green energy auction bring in a demand-side management approach. Also the implemented distributed MPC algorithm is described and validated with simulation studies.

Metaheuristic approach to the Holt-Winters optimal short term load forecast

Electricity short-term load forecast is very important for the operation of power systems. In this work a classical exponential smoothing model, the Holt-Winters with double seasonality was used to test for accurate predictions applied to the Portuguese demand time series. Some metaheuristic algorithms for the optimal selection of the smoothing parameters of the Holt-Winters forecast function were used and the results after testing in the time series showed little differences among methods, so the use of the simple local search algorithms is recommended as they are easier to implement.

Metaheuristhic approach to the Holt-Winters optimal short term load forecast

Electricity short-term load forecast is very important for the operation of power systems. In this work a classical exponential smoothing model, the Holt-Winters with double seasonality was used to test for accurate predictions applied to the Portuguese demand time series. Some metaheuristic algorithms for the optimal selection of the smoothing parameters of the Holt-Winters forecast function were used and the results after testing in the time series showed little differences among methods, so the use of the simple local search algorithms is recommended as they are easier to implement.

The daily and hourly energy consumption and load forecasting using artifitial neural network method: a case study using a set of 93 households in Portugal

It is important to understand and forecast a typical or a particularly household daily consumption in order to design and size suitable renewable energy systems and energy storage. In this research for Short Term Load Forecasting (STLF) it has been used Artificial Neural Networks (ANN) and, despite the consumption unpredictability, it has been shown the possibility to forecast the electricity consumption of a household with certainty. The ANNs are recognized to be a potential methodology for modeling hourly and daily energy consumption and load forecasting. Input variables such as apartment area, numbers of occupants, electrical appliance consumption and Boolean inputs as hourly meter system were considered. Furthermore, the investigation carried out aims to define an ANN architecture and a training algorithm in order to achieve a robust model to be used in forecasting energy consumption in a typical household. It was observed that a feed-forward ANN and the Levenberg-Marquardt algorithm provided a good performance. For this research it was used a database with consumption records, logged in 93 real households, in Lisbon, Portugal, between February 2000 and July 2001, including both weekdays and weekend. The results show that the ANN approach provides a reliable model for forecasting household electric energy consumption and load profile. © 2014 The Author.