Management of public water supply to reduce power cost and improve wind power uptake

This paper presents a study on the implementation of Real-Time Pricing (RTP) based Demand Side Management (DSM) of water pumping at a clean water pumping station in Northern Ireland, with the intention of minimising electricity costs and maximising the usage of electricity from wind generation. A Genetic Algorithm (GA) was used to create pumping schedules based on system constraints and electricity tariff scenarios. Implementation of this method would allow the water network operator to make significant savings on electricity costs while also helping to mitigate the variability of wind generation.

Management of public water supply to reduce energy cost and improve wind power uptake

This paper presents a study on the implementation of Real-Time Pricing (RTP) based Demand Side Management (DSM) of water pumping at a clean water pumping station in Northern Ireland, with the intention of minimising electricity costs and maximising the usage of electricity from wind generation. A Genetic Algorithm (GA) was used to create pumping schedules based on system constraints and electricity tariff scenarios. Implementation of this method would allow the water network operator to make significant savings on electricity costs while also helping to mitigate the variability of wind generation.

Management of public water supply to reduce energy cost and improve wind power uptake

This paper presents a study on the implementation of Real-Time Pricing (RTP) based Demand Side Management (DSM) of water pumping at a clean water pumping station in Northern Ireland, with the intention of minimising electricity costs and maximising the usage of electricity from wind generation. A Genetic Algorithm (GA) was used to create pumping schedules based on system constraints and electricity tariff scenarios. Implementation of this method would allow the water network operator to make significant savings on electricity costs while also helping to mitigate the variability of wind generation.

Design and characterization of wideband Hall current sensors in BCD technology for smart power and metering applications

Power electronic circuits are moving towards higher switching frequencies, exploiting the capabilities of novel devices to shrink the dimension of passive components. This trend demands sensors capable enough to operate at such high frequencies. This thesis aims to demonstrate through experimental characterization, the broadband capability of a fully integrated CMOS X-Hall current sensor in current mode interfaced with a transimpedance amplifier (TIA), chip CH09, realized in CMOS technology for power electronics applications such as power converters. The system exploits a common-mode control system to operate the dual supply system, 5-V for the X-Hall probe and 1.2-V for the readout. The developed prototype achieves a maximum acquisition bandwidth of 12 MHz, a power consumption of 11.46 mW, resolution of 39 mArms, a sensitivity of 8 % /T, and a FoM of 569-MHz/A2mW, significantly higher than current state-of-the-art. Further enhancements were proposed to CH09 as a new chip CH100, aiming for accuracy levels prerequisite for a real-time power electronic application. The TIA was optimized for a wider bandwidth of 26.7 MHz with nearly 30% reduction of the integrated input referred noise of 26.69 nArms at the probe-AFE interface in the frequency band of DC-30 MHz, and a 10% improvement in the dynamic range. The expected input range is 5-A. The chip incorporates a dual sensing chain for differential sensing to overcome common mode interferences. A novel offset cancellation technique is proposed that would require switching of polarity of bias currents. Thermal gain drift was improved by a factor of 8 and will be digitally calibrated utilizing a new built-in temperature sensor with a post calibration measurement accuracy greater than 1%. The estimated power consumption of the entire system is 55.6 mW. Both prototypes have been implemented through a 90-nm microelectronic process from STMicroelectronics and occupy a silicon area of 2.4 mm2.

Design and Characterization of an Active Three-Phase EMI Noise Separator for Three-Phase Power Electronics Systems

One of the major issues for power converters that are connected to the electric grid are the measurement of three phase Conduced Emissions (CE), which are regulated by international and regional standards. CE are composed of two components which are Common Mode (CM) noise and Differential Mode (DM) noise. To achieve compliance with these regulations the Equipment Under Test (EUT) includes filtering and other electromagnetic emission control strategies. The separation of differential mode and common mode noise in Electromagnetic Interference (EMI) analysis is a well-known procedure which is useful especially for the optimization of the EMI filter, to improve the CM or DM attenuation depending on which component of the conducted emissions is predominant, and for the analysis and the understanding of interference phenomena of switched mode power converters. However, separating both components is rarely done during measurements. Therefore, in this thesis an active device for the separation of the CM and DM EMI noise in three phase power electronic systems has been designed and experimentally analysed.

Simulation of the Barkhausen Noise using random field Ising model with long-range interaction

We present a method to simulate the Magnetic Barkhausen Noise using the Random Field Ising Model with magnetic long-range interaction. The method allows calculating the magnetic flux density behavior in particular sections of the lattice reticule. The results show an internal demagnetizing effect that proceeds from the magnetic long-range interactions. This demagnetizing effect induces the appearing of a magnetic pattern in the region of magnetic avalanches. When compared with the traditional method, the proposed numerical procedure neatly reduces computational costs of simulation. (c) 2008 Published by Elsevier B.V.

Nondestructive inspection of plastic deformation in commercial carbon steels using magnetic Barkhausen noise

The present work shows measurements of the Magnetic Barkhausen Noise (MBN) in commercial AISI/SAE 1045 and ASTM 36 steel deformed samples. The correlation between the MBN root mean square, Barkhausen signal profile and MBN power spectrum with the plastic deformation is established. The results show that the power spectral density of the Barkhausen signal is more effective as nondestructive evaluator than root mean square of Barkhausen signal. The Outcomes also suggest the presence of unbalanced tensions between the surface and the bulk of sample due to the presence of plastic deformation.

The sound-field characterisation of a power transformer

In order to effectively suppress the noise radiation from large electrical power transformers, both the structure-borne and air-borne sound fields need to be characterised. The characterisation can be made either from theoretical predictions or by in-situ measurements. This paper presents the study of the sound radiation from a large power transformer in a substation. The radiation pattern can be predicted from the measured acceleration distribution and the predicted value is not affected by other noise sources. Alternatively, the farfield sound pressure level can be predicted from the sound pressure level measured at NEMA locations. Both the near- and far-field power radiation can be in-situ measured using the sound intensity technique. It is shown that both the vibration of a transformer tank wall and the radiated noise consist of a series of tonal components mainly at the first few harmonic frequencies of 100 Hz. Also, the neglect of the noise radiation from the transformer (top and bottom) lids does not affects the accuracy of the transformer radiation characterisation. (C) 1998 Elsevier Science Ltd. All rights reserved.

Supply chain management as beyond operational efficiency

The orthodoxy of supply chain management (SCM) emphasises competitive advantage through increased operational efficiency and market responsiveness from production and distribution processes into the hands of consumers. It anticipates that future competition will be between chains rather than between firms. While well established in other industry sectors, the SCM concept is newly developed in the Australian agri-food sector. Critical review of the concept has identified key issues of power among channel members, processes of chain initiation and innovation, and the inability of SCM to offer a viable business strategy for some firms. Building on those insights, this paper examines the supply chain concept for horticulture. Horticultural products are characterised by perishability, heterogeneity and lags in production response to market signals. Producers’ profits are vulnerable to quantity, timing of supply and product specification. Many supply chains in smaller industries are loose, fragmented, interwoven, unstable and unique! Firms operating within these environments need an astute understanding of the chains, the hierarchy of channel members and their relative position. Effective business strategies – for individual firms and supply chains - need to be developed and redeveloped to accommodate the dynamic nature of horticulture. Two case studies are discussed as contributions to this early stage of the theoretical development of supply chain management. The SCM concept also has implications for horticultural researchers, involving a wider range of industry stakeholders, technical problems and research skills. As for business management, the usefulness of the concept will depend on its capacity to increase responsiveness to customers’ preferences and customer value.

A real time pricing approach to deal with excessive wind power situations

The introduction of wind power generation in several countries around the world, including in European countries, where energy policy directives have encouraged the use of renewables, led to several changes in market and power systems operation. The intensive integration of these sources has led to situations in which the demand is lower than the available renewable resources. In these situations a part of the available generation is wasted if not used for storage or to supply additional demand. This paper proposes a real time demand response methodology based on changing the electricity price for the consumers expecting an increase in the demand in the periods in which that demand is lower than the available renewable generation. The consumers response to the changes in electricity price is characterized by their price elasticity of demand considered distinct for each consumer type. The proposed methodology is applied to the Portuguese power system, in the context of the Iberian electricity market (MIBEL). The renewable-based producers are considered as special producers, with special tariffs, and so it is important to use the energy available as it will be paid anyway. In this context, consumers are entities actively participating in the operation of the market.

Matrix Converter-Based Unified Power-Flow Controllers: Advanced Direct Power Control Method

This paper presents a direct power control (DPC) for three-phase matrix converters operating as unified power flow controllers (UPFCs). Matrix converters (MCs) allow the direct ac/ac power conversion without dc energy storage links; therefore, the MC-based UPFC (MC-UPFC) has reduced volume and cost, reduced capacitor power losses, together with higher reliability. Theoretical principles of direct power control (DPC) based on sliding mode control techniques are established for an MC-UPFC dynamic model including the input filter. As a result, line active and reactive power, together with ac supply reactive power, can be directly controlled by selecting an appropriate matrix converter switching state guaranteeing good steady-state and dynamic responses. Experimental results of DPC controllers for MC-UPFC show decoupled active and reactive power control, zero steady-state tracking error, and fast response times. Compared to an MC-UPFC using active and reactive power linear controllers based on a modified Venturini high-frequency PWM modulator, the experimental results of the advanced DPC-MC guarantee faster responses without overshoot and no steady-state error, presenting no cross-coupling in dynamic and steady-state responses.

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.

AI in power systems and energy markets

In a world increasingly conscientious about environmental effects, power and energy systems are undergoing huge transformations. Electric energy produced from power plants is transmitted and distributed to end users through a power grid. The power industry performs the engineering design, installation, operation, and maintenance tasks to provide a high-quality, secure energy supply while accounting for its systems’ abilities to withstand uncertain events, such as weather-related outages. Competitive, deregulated electricity markets and new renewable energy sources, however, have further complicated this already complex infrastructure.Sustainable development has also been a challenge for power systems. Recently, there has been a signifi cant increase in the installation of distributed generations, mainly based on renewable resources such as wind and solar. Integrating these new generation systems leads to more complexity. Indeed, the number of generation sources greatly increases as the grid embraces numerous smaller and distributed resources. In addition, the inherent uncertainties of wind and solar energy lead to technical challenges such as forecasting, scheduling, operation, control, and risk management. In this special issue introductory article, we analyze the key areas in this field that can benefi t most from AI and intelligent systems now and in the future.We also identify new opportunities for cross-fertilization between power systems and energy markets and intelligent systems researchers.

Market power analysis in the Iberian electricity market using a conjectural variations model

In the last years the electricity industry has faced a restructuring process. Among the aims of this process was the increase in competition, especially in the generation activity where firms would have an incentive to become more efficient. However, the competitive behavior of generating firms might jeopardize the expected benefits of the electricity industry liberalization. The present paper proposes a conjectural variations model to study the competitive behavior of generating firms acting in liberalized electricity markets. The model computes a parameter that represents the degree of competition of each generating firm in each trading period. In this regard, the proposed model provides a powerful methodology for regulatory and competition authorities to monitor the competitive behavior of generating firms. As an application of the model, a study of the day-ahead Iberian electricity market (MIBEL) was conducted to analyze the impact of the integration of the Portuguese and Spanish electricity markets on the behavior of generating firms taking into account the hourly results of the months of June and July of 2007. The advantages of the proposed methodology over other methodologies used to address market power, namely Residual Supply index and Lerner index are highlighted. (C) 2014 Elsevier Ltd. All rights reserved.