Assessment of Domestic Load Suitable for Smart Consumer Load Participation

This study characterizes the domestic loads suitable to participate in the load participation scheme to make the power system more carbon and economically efficient by shifting the electricity demand profile towards periods when there is plentiful renewable in-feed.

A series of experiments have been performed on a common fridge-freezer, both completely empty and half full. The results presented are ambient temperature, temperature inside the fridge, temperature inside the drawer of the fridge, temperature inside the freezer, thermal time constants, power consumption and electric energy consumed.

The thermal time constants obtained clearly demonstrate the potential of such refrigeration load for Smart Customer Load Participation.

A smart load appliance application using a single compressor fridge-freezer to support grid operations

This paper describes a fridge-freezer smart load model, which responds to external signals from the wholesale electricity market to support grid operations while switching the fridge-freezer on and off to maintain optimum operations for the owner. The key parameters of the model are the appliance dimensions, thermal mass, the fridge and freezer thermal time constants and the compressor power consumption. The model demonstrates that control strategies help to minimise load at times when the grid is under stress from high demand, and shift some load to a lower wholesale price or when there is excess renewable power. Three control strategies are proposed, based on peak shaving and valley filling, price signals and wind availability.

Short-Term Multinodal Load Forecasting Using a Modified General Regression Neural Network

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Short-term multinodal load forecasting in distribution systems using general regression neural networks

Multinodal load forecasting deals with the loads of several interest nodes in an electrical network system, which is also known as bus load forecasting. To perform this demand, it is necessary a technique that is precise, trustable and has a short-time processing. This paper proposes two methodologies based on general regression neural networks for short-term multinodal load forecasting. The first individually forecast the local loads and the second forecast the global load and individually forecast the load participation factors to estimate the local loads. To design the forecasters it wasn't necessary the previous study of the local loads. Tests were made using a New Zealand distribution subsystem and the results obtained are compatible with the ones founded in the specialized literature. © 2011 IEEE.

A Smart Grid Information System for Demand Side Participation: Remote Control of Domestic Appliances to Balance Demand

Due to the intermittent nature of renewable generation it is desirable to consider the potential of controlling the demand-side load to smooth overall system demand. The architecture and control methodologies of such a system on a large scale would require careful consideration. Some of these considerations are discussed in this paper; such as communications infrastructure, systems architecture, control methodologies and security. A domestic fridge is used in this paper as an example of a controllable appliance. A layered approach to smart-grid is introduced and it can be observed how each smart-grid component from physical cables, to the end-devices (or smart-applications) can be mapped to these set layers. It is clear how security plays an integral part in each component of the smart-grid so this is also an integral part of each layer. The controllable fridge is described in detail and as one potential smart-grid application which maps to the layered approach. A demonstration system is presented which involves a Raspberry Pi (a low-power, low-cost device representing the appliance controller).

Domestic fridge-freezer load aggregation to support ancillary services

Grid operators and electricity retailers in Ireland manage peak demand, power system balancing and grid congestion by offering relevant incentives to consumers to reduce or shift their load. The need for active consumers in the home using smart appliances has never been greater, due to increased variable renewable generation and grid constraints. In this paper an aggregated model of a single compressor fridge-freezer population is developed. A price control strategy is examined to quantify and value demand response savings during a representative winter and summer week for Ireland in 2020. The results show an average reduction in fridge-freezer operating cost of 8.2% during winter and significantly lower during summer in Ireland. A peak reduction of at least 68% of the average winter refrigeration load is achieved consistently during the week analysed using a staggering control mode. An analysis of the current ancillary service payments confirms that these are insufficient to ensure widespread uptake by the small consumer, and new mechanisms need to be developed to make becoming an active consumer attractive. Demand response is proposed as a new ancillary service called ramping capability, as the need for this service will increase with more renewable energy penetration on the power system.

Determining the Adjustment Baseline Parameters to Define an Accurate Customer Baseline Load

Demand response is an energy resource that has gained increasing importance in the context of competitive electricity markets and of smart grids. New business models and methods designed to integrate demand response in electricity markets and of smart grids have been published, reporting the need of additional work in this field. In order to adequately remunerate the participation of the consumers in demand response programs, improved consumers’ performance evaluation methods are needed. The methodology proposed in the present paper determines the characterization of the baseline approach that better fits the consumer historic consumption, in order to determine the expected consumption in absent of participation in a demand response event and then determine the actual consumption reduction. The defined baseline can then be used to better determine the remuneration of the consumer. The paper includes a case study with real data to illustrate the application of the proposed methodology.

Load Control Timescales Simulation in a Multi-Agent Smart Grid Platform

Environmental concerns and the shortage in the fossil fuel reserves have been potentiating the growth and globalization of distributed generation. Another resource that has been increasing its importance is the demand response, which is used to change consumers’ consumption profile, helping to reduce peak demand. Aiming to support small players’ participation in demand response events, the Curtailment Service Provider emerged. This player works as an aggregator for demand response events. The control of small and medium players which act in smart grid and micro grid environments is enhanced with a multi-agent system with artificial intelligence techniques – the MASGriP (Multi-Agent Smart Grid Platform). Using strategic behaviours in each player, this system simulates the profile of real players by using software agents. This paper shows the importance of modeling these behaviours for studying this type of scenarios. A case study with three examples shows the differences between each player and the best behaviour in order to achieve the higher profit in each situation.

'A load too heavy': Critical reflections on the child labor problem in Africa's small-scale mining sector

This paper provides an extended analysis of the child labor problem in the artisanal and small-scale mining (ASM) sector, focusing specifically on the situation in sub-Saharan Africa. In recent years, the issue of child labor in ASM has garnered significant attention from the International Labor Organization (ILO), which has been particularly active in raising public awareness of the problem; and, has proceeded to implement policies and collaborative project work aimed at Curtailing children's participation in ASM activities in a number of African countries. The analysis concludes with a critical appraisal of an ILO project recently launched in the Talensi-Nabdam District in the Upper East Region of Ghana, which sheds light on how the child labor problem is being tackled in practice in ASM communities in sub-Saharan Africa. (c) 2008 Elsevier Ltd. All rights reserved.

Nitric oxide participation in granulomatous response induced by Paracoccidioides brasiliensis infection in mice

The role of nitric oxide (NO) in granulomas of Paracoccidioides brasiliensis-infected inducible NO synthase-deficient C57BL/6 mice (iNOS KO) and their wild-type counterparts and its association with osteopontin (OPN) and matrix metalloproteinases (MMPs) was studied. At 15 days after infection (DAI), iNOS KO mice showed compact and necrotic granulomas with OPN+ macrophages and multinucleated giant cells, whereas wild-type mice developed loose granulomas with many fungi and OPN+ cells distributed throughout the tissue. In addition, high OPN levels and fungal load were observed in iNOS KO mice. Both experimental groups had MMP-9 activity. At 120 DAI, iNOS KO had smaller granulomas with OPN+ cells, lower OPN levels, lower fungal load and decreased MMP-9 activity compared with wild-type mice. These findings suggest that NO has an important role in granuloma modulation, by controlling OPN and MMP production, as well as by inducing loose granulomas formation and fungal dissemination, resulting, at later phases, in progression of paracoccidioidomycosis.

Variables affecting government debt: A comparison of certificates of participation, tax -exempt revenue bonds and tax -exempt general obligation bonds

This dissertation analyzed and compared variables affecting interest rate and yield of certificates of participation, tax-exempt revenue bonds and tax-exempt general obligation bonds. The study employed qualitative and quantitative analysis methods. ^ Qualitative research methods included surveys, interviews and focus groups. The survey solicited debt load information from 67 Florida school districts (21 responded) and addressed the question which districts used certificates of participation and why. Eight individuals with experience dealing with all three debt instruments were interviewed. A follow-up focus group of six school district financial officers gathered additional data. Results from the qualitative methods revealed school districts used certificates of participation based on millage authority amount available relative to overall tax base. Also identified was the belief of a significant difference in certificates of participation costs and the other two debt instrument types. ^ The study's quantitative methods analyzed 1998 and 1999 initial issues of Moody's AAA rated certificates of participation, tax-exempt revenue bonds and tax-exempt general obligation bonds. Through an analysis of covariance (ANCOVA), the study examined interest rates and yields while controlling for the covariates of credit enhancement, issue size, and maturity date. The analysis identified no significant difference between interest rates of certificates of participation and tax-exempt general obligation bonds (p < 0.05). There was a significant difference between interest rates of tax-exempt revenue bonds and tax-exempt general obligation bonds. This study discerned no significant difference between yield on certificates of participation and tax-exempt general obligation bonds. It identified a difference in yield between both certificates of participation and tax-exempt general obligation bonds compared with tax-exempt revenue bonds. ^ The study found COPs to have lesser overall costs than RV bonds. COPs also have a quicker entry into the market resulting in construction cost savings. The study found policy implications such as investment portfolio limitations and public choice issues about using COPs as a mechanism to grow government. ^