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Efficiency of energy resource use is a key factor for a sustainable energy future. By matching the exergy levels of supply and demand, Energy Quality Management (EQM) of building energy supply systems may achieve more efficient use of energy resources. Beyond this, environmental impact of energy supply systems is another essential issue. This work addresses the influence of EQM on CO 2 emissions in the operation optimization of a Distributed Energy System (DES). A multi-objective linear programming problem is formulated to reduce energy costs and increase the overall exergy efficiency. Total CO 2 emissions are evaluated for the optimized operation strategies of the DES. The operators of the DES can choose the operation strategy from the Pareto front, based on their priorities and also aware of effects on CO 2 emissions. Results demonstrate more efficient use of energy resources and reduction in CO 2 emissions through EQM, as compared with conventional energy supply systems.

Dolomite-based binders are characterised by interesting technical and environmental features. For their synthesis, sources of both CaO and MgO are required. The idea developed in this work is to couple the synthesis of dolomite-based binders, starting from a natural dolomite, through the concept of concentrated solar energy (needed to drive the endothermal dolomite calcination process) in fluidised bed reactors. To this end, a fluidised bed system, where the concentrated solar radiation is mimicked by the use of Xe-lamps (short-arc), has been set up and operated. Natural dolomite (sieved in the 420-590 ?m size range) was calcined at a nominal temperature of 850 °C, and bed temperature profiles during solar-driven calcination were investigated. Then, four binders were prepared by mixing slaked dolomite (obtained from the hydration of solar calcined dolomite) with either blast furnace slag or coal fly ash as supplementary cementitious materials. The binders were hydrated for curing times ranging from 7 to 56 days. X-ray fluorescence, X-ray diffraction and combined differential thermal and thermogravimetric analyses were employed as characterisation techniques both to analyse the chemical composition of starting materials and to investigate the evolution of the hydration in the four systems.

Cogeneration of heat and electricity is an important pillar of energy and climate policy. To plan the production and distribution system of combined heat and power (CHP) systems for residential heating, suitable methods for decision support are needed. For a comprehensive feasibility analysis, the integration of the location and capacity planning of the power plants, the choice of customers, and the network planning of the heating network into one optimization model are necessary. Thus, we develop an optimization model for electricity generation and heat supply. This mixed integer linear program (MILP) is based on graph theory for network flow problems. We apply the network location model for the optimization of district heating systems in the City of Osorno in Chile, which exhibits the “checkerboard layout” typically found in many South American cities. The network location model can support the strategic planning of investments in renewable energy projects because it permits the analysis of changing energy prices, calculation of break-even prices for heat and electricity, and estimation of greenhouse gas emission savings.

The influence of compost on the growth of bean plants irrigated with As-contaminated waters and its influence on the mobility of As in the soils and the uptake of As (as NaAs(III)O2) by plant components was studied at various compost application rates (3·10(4) and 6·10(4) kg ha(-1)) and at three As concentrations (1, 2 and 3 mg kg(-1)). The biomass and As and P concentrations of the roots, shoots and beans were determined at harvest time, as well as the chlorophyll content of the leaves and nonspecific and specifically bound As in the soil. The bean plants exposed to As showed typical phytotoxicity symptoms; no plants however died over the study. The biomass of the bean plants increased with the increasing amounts of compost added to the soil, attributed to the phytonutritive capacity of compost. Biomass decreased with increasing As concentrations, however, the reduction in the biomass was significantly lower with the addition of compost, indicating that the As phytotoxicity was alleviated by the compost. For the same As concentration, the As content of the roots, shoots and beans decreased with increasing compost added compared to the Control. This is due to partial immobilization of the As by the organic functional groups on the compost, either directly or through cation bridging. Most of the As adsorbed by the bean plants accumulated in the roots, while a scant allocation of As occurred in the beans. Hence, the addition of compost to soils could be used as an effective means to limit As accumulation in crops from As-contaminated waters.

In this paper a grid-tied photovoltaic (PV) cascaded H-bridge (CHB) inverter with embedded storage units is proposed. The multi-input single-output inverter architecture allows a distributed maximum power point tracking (DMPPT) approach, thus mitigating the mismatch effects. The energy storage units (ESUs) embedded at each dc-link provides more flexibility to the power circuit compensating for the inherent variability of the PV sources. The proposed power system ensures a continuous power supply to the grid also in case of PV power fluctuations due to irradiance conditions as well as to the MPPT. In particular, the presence of a storage element allows a voltage sweep on the PV source to be implemented, thus guaranteeing the maximization of PV energy harvesting, with no detrimental effect on the power delivery to the utility network. The numerical results, carried out on a single-phase nineteen-level PV CHB inverter, reveal the improved performance of the proposed design and control technique.

The safeguard of power equipments is assuming a major role in the deregulated electricity market, where a malfunctioning power system could be responsible for serious damages to a large number of system operators having access to the shared energy resource. In this context thermal monitoring of power cables represents a key issue in evaluating the risks associated with a given load management policy especially during emergency conditions. In particular this demands for reliable assessment models that should be able to predict the transient thermal behaviour when the load exceeds the nameplate value. In this connection the application of both simplified and detailed power cable thermal models is often complicated by the presence of uncertainties affecting the tolerances of the input data. The effect of these uncertainties could influence the final solution to a considerable extent. A comprehensive tolerance analysis is therefore required in order to incorporate the effect of data uncertainties into the thermal modelling process. To address this problem, in the paper the employment of interval mathematic is proposed. Several numerical results are presented and discussed in order to assess the effectiveness of the proposed methodology which offer a rough qualitative insight of the solution in a very short time, comparable to the time required for a deterministic numerical simulation.

This paper presents an optimal control strategy for a district heating power plant with thermal energy storage. The main goal of the control strategy is to reduce the operation costs of the power plant, by scheduling the boilers, the operation of the thermal energy storage and the curtailment on the loads. The problem is stated as a constrained optimization in the form of a Mixed Integer Linear Program (MILP), embedded on an Model Predictive Control (MPC) framework. Particular attention is paid to modeling of boilers operating constraints, including the outlet water flow temperature, to the energy exchanged with the thermal energy storage and to the operating modes of the power plant layout, including the constraints related to the supply water temperature needed from the network. The results are performed using the data and the layout of the power plant located in the city of Ylivieska, in Finland. The cost analysis performed shows the advantages of using the predictive control strategy.