Electrical-energy storage in hybrid ultracapacitors

There are several ways of storing electrical energy in chemical and physical forms and retrieving it on demand, and ultracapacitors are one among them. This article presents the taxonomy of ultracapacitor and describes various types of rechargeable-battery electrodes that can be used to realize the hybrid ultracapacitors in conjunction with a high-surface-area-graphitic-carbon electrode. While the electrical energy is stored in a battery electrode in chemical form, it is stored in physical form as charge in the electrical double-layer formed between the electrolyte and the high-surface-area-carbon electrodes. This article discusses various types of hybrid ultracapacitors along with the possible applications.

Mechanical constraints enhance electrical energy densities of soft dielectrics

Thesis

Transmission loss allocation in a deregulated electrical energy market

This paper presents a new method for transmission loss allocation in a deregulated electrical power market. The proposed method is based on physical flow through transmission lines. The contributions of individual loads to the line flows are used as basis for allocating transmission losses to different loads. With minimum assumptions, that sound to be reasonable and cannot be rejected, a novel loss allocation formula is derived. The assumptions made are: a number of currents sharing a transmission line distribute themselves over the cross section in the same manner; that distribution causes the minimum possible power loss. Application of the proposed method is straightforward. It requires only a solved power flow and any simple algorithm for power flow tracing. Both active and reactive powers are considered in the loss allocation procedure. Results of application show the accuracy of the proposed method compared with the commonly used procedures.

Electrical energy storage and Smart Grid technologies to integrate the next generation of Renewable Power Systems

The growth of renewable power sources, distributed generation and the potential for alternative fuelled modes of transport such as electric vehicles has led to concerns over the ability of existing grid systems to facilitate such diverse portfolio mixes in already congested power systems. Internationally the growth in renewable energy sources is driven by government policy targets associated with the uncertainties of fossil fuel supplies, environmental issues and a move towards energy independence. Power grids were traditionally designed as vertically integrated centrally managed entities with fully dispatchable generating plant. Renewable power sources, distributed generation and alternative fuelled vehicles will place these power systems under additional stresses and strains due to their different operational characteristics. Energy storage and smart grid technologies are widely proposed as the tools to integrate these future diverse portfolio mixes within the more conventional power systems. The choice in these technologies is determined not only by their location on the grid system, but by the diversification in the power portfolio mix, the electricity market and the operational demands. This paper presents a high level technical and economic overview of the role and relevance of electrical energy storage and smart grid technologies in the next generation of renewable power systems.

Demand response in electrical energy supply: an optimal real time pricing approach

In competitive electricity markets with deep concerns for the efficiency level, demand response programs gain considerable significance. As demand response levels have decreased after the introduction of competition in the power industry, new approaches are required to take full advantage of demand response opportunities. This paper presents DemSi, a demand response simulator that allows studying demand response actions and schemes in distribution networks. It undertakes the technical validation of the solution using realistic network simulation based on PSCAD. The use of DemSi by a retailer in a situation of energy shortage, is presented. Load reduction is obtained using a consumer based price elasticity approach supported by real time pricing. Non-linear programming is used to maximize the retailer’s profit, determining the optimal solution for each envisaged load reduction. The solution determines the price variations considering two different approaches, price variations determined for each individual consumer or for each consumer type, allowing to prove that the approach used does not significantly influence the retailer’s profit. The paper presents a case study in a 33 bus distribution network with 5 distinct consumer types. The obtained results and conclusions show the adequacy of the used methodology and its importance for supporting retailers’ decision making.

A new error measure for forecasts of household-level, high resolution electrical energy consumption

As low carbon technologies become more pervasive, distribution network operators are looking to support the expected changes in the demands on the low voltage networks through the smarter control of storage devices. Accurate forecasts of demand at the single household-level, or of small aggregations of households, can improve the peak demand reduction brought about through such devices by helping to plan the appropriate charging and discharging cycles. However, before such methods can be developed, validation measures are required which can assess the accuracy and usefulness of forecasts of volatile and noisy household-level demand. In this paper we introduce a new forecast verification error measure that reduces the so called “double penalty” effect, incurred by forecasts whose features are displaced in space or time, compared to traditional point-wise metrics, such as Mean Absolute Error and p-norms in general. The measure that we propose is based on finding a restricted permutation of the original forecast that minimises the point wise error, according to a given metric. We illustrate the advantages of our error measure using half-hourly domestic household electrical energy usage data recorded by smart meters and discuss the effect of the permutation restriction.

Effect of electrospinning parameters and polymer concentrations on mechanical-to-electrical energy conversion of randomly-oriented electrospun poly(vinylidene fluoride) nanofiber mats

Poly(vinylidene fluoride) (PVDF) nanofiber mats prepared by an electrospinning technique were used as an active layer for making mechanical-to-electric energy conversion devices. The effects of PVDF concentration and electrospinning parameters (e.g. applied voltage, spinning distance), as well as nanofiber mat thickness on the fiber diameter, PVDF β crystal phase content, and mechanical-to-electrical energy conversion properties of the electrospun PVDF nanofiber mats were examined. It was interesting to find that finer uniform PVDF fibers showed higher β crystal phase content and hence, the energy harvesting devices had higher electrical outputs, regardless of changing the electrospinning parameters and PVDF concentration. The voltage output always changed in the same trend to the change of current output whatever the change trend was caused by the operating parameters or polymer concentration. Both voltage and current output changes followed a similar trend to the change of the β crystal phase content in the nanofibers. The nanofiber mat thickness influenced the device electrical output, and the maximum output was found on the 70 μm thick nanofiber mat. These results suggest that uniform PVDF nanofibers with smaller diameters and high β crystal phase content facilitate mechanical-to-electric energy conversion. The understanding obtained from this study may benefit the development of novel piezoelectric nanofibrous materials and devices for various energy uses.

Robust mechanical-to-electrical energy conversion from short-distance electrospun poly(vinylidene fluoride) fiber webs

Electrospun polyvinylidene fluoride (PVDF) nanofiber webs have shown great potential in making mechanical-to-electrical energy conversion devices. Previously, polyvinylidene fluoride (PVDF) nanofibers were produced either using near-field electrospinning (spinning distance < 1 cm) or conventional electrospinning (spinning distance > 8 cm). PVDF fibers produced by an electrospinning at a spinning distance between 1 and 8 cm (referred to as "short-distance" electrospinning in this paper) has received little attention. In this study, we have found that PVDF electrospun in such a distance range can still be fibers, although interfiber connection is formed throughout the web. The interconnected PVDF fibers can have a comparable β crystal phase content and mechanical-to-electrical energy conversion property to those produced by conventional electrospinning. However, the interfiber connection was found to considerably stabilize the fibrous structure during repeated compression and decompression for electrical conversion. More interestingly, the short-distance electrospun PVDF fiber webs have higher delamination resistance and tensile strength than those of PVDF nanofiber webs produced by conventional electrospinning. Short-distance electrospun PVDF nanofibers could be more suitable for the development of robust energy harvesters than conventionally electrospun PVDF nanofibers.

Urban heat islands and electrical energy consumption

This study proposes the development of thermal and energy consumption maps to generate useful planning information. A residential neighbourhood in a medium-sized city was selected as the study area. In this area, 40 points were taken as urban reference points where air temperatures at the pedestrian level were collected. At the same time, rural temperatures made available by the city meteorological station were registered. Data of electrical energy consumption of the building units (houses and apartments) were collected through a household survey that was also designed to identify the users' income levels. Then, maps were developed so that the configuration of urban heat islands and electrical energy consumption could be visualised, compared and analysed. The results showed that the income level was the most important variable influencing electrical energy consumption. However, a strong relationship of the consumption with the thermal environment was also observed.

A Time-domain Harmonic Power-Flow Analysis in Electrical Energy Distribution Networks, Using Norton Models for Non-linear Loading

The purpose of this paper is to present the application of a three-phase harmonic propagation analysis time-domain tool, using the Norton model to approach the modeling of non-linear loads, making the harmonics currents flow more appropriate to the operation analysis and to the influence of mitigation elements analysis. This software makes it possible to obtain results closer to the real distribution network, considering voltages unbalances, currents imbalances and the application of mitigation elements for harmonic distortions. In this scenario, a real case study with network data and equipments connected to the network will be presented, as well as the modeling of non-linear loads based on real data obtained from some PCCs (Points of Common Coupling) of interests for a distribution company.

Mathematical Optimization Applied to Thermal and Electrical Energy Systems

This Thesis aims at building and discussing mathematical models applications focused on Energy problems, both on the thermal and electrical side. The objective is to show how mathematical programming techniques developed within Operational Research can give useful answers in the Energy Sector, how they can provide tools to support decision making processes of Companies operating in the Energy production and distribution and how they can be successfully used to make simulations and sensitivity analyses to better understand the state of the art and convenience of a particular technology by comparing it with the available alternatives. The first part discusses the fundamental mathematical background followed by a comprehensive literature review about mathematical modelling in the Energy Sector. The second part presents mathematical models for the District Heating strategic network design and incremental network design. The objective is the selection of an optimal set of new users to be connected to an existing thermal network, maximizing revenues, minimizing infrastructure and operational costs and taking into account the main technical requirements of the real world application. Results on real and randomly generated benchmark networks are discussed with particular attention to instances characterized by big networks dimensions. The third part is devoted to the development of linear programming models for optimal battery operation in off-grid solar power schemes, with consideration of battery degradation. The key contribution of this work is the inclusion of battery degradation costs in the optimisation models. As available data on relating degradation costs to the nature of charge/discharge cycles are limited, we concentrate on investigating the sensitivity of operational patterns to the degradation cost structure. The objective is to investigate the combination of battery costs and performance at which such systems become economic. We also investigate how the system design should change when battery degradation is taken into account.