Moving Towards Sustainable and Resilient Smart Water Grids

abstract: Urban water systems face sustainability and resiliency challenges including water leaks, over-use, quality issues, and response to drought and natural disasters. Information and communications technology (ICT) could help address these challenges through the development of smart water grids that network and automate monitoring and control devices. While progress is being made on technology elements, as a system, the smart water grid has received scant attention. This article aims to raise awareness of the systems-level idea of smart water grids by reviewing the technology elements and their integration into smart water systems, discussing potential sustainability and resiliency benefits, and challenges relating to the adoption of smart water grids. Water losses and inefficient use stand out as promising areas for applications of smart water grids. Potential barriers to the adoption of smart water grids include lack of funding for research and development, economic disincentives as well as institutional and political structures that favor the current system. It is our hope that future work can clarify the benefits of smart water grids and address challenges to their further development.The final version of this article, as published in Challenges, can be viewed online at: http://www.mdpi.com/2078-1547/5/1/12

Smart meters adoption: recent advances and future trends

High growth in electricity demand and peaks in the load curve, caused mainly by households, require big investments in infrastructure that are used for short periods. Because of this, it is necessary to look for new developments that allow meeting the needs of users as well as using the electricity system resources efficiently. This is possible through the Smart Grid (SG), which additionally allows users to have autonomy in the electricity supply chain. Our focus of investigation is with households because they can monitor their demand and help to reduce the peaks of the load curve. To do this, users must use Smart Meters, because these devices allow consumers to obtain the information necessary to control their demand. This paper presents a systematic analysis of published literature related to the study of the SG from the demand side, analyses the current situation of this topic and the impact of Smart Meter penetration in households

Computational intelligence from AI to BI to NI

ABSTRACT This paper gives highlights of the history of the neural network field, stressing the fundamental ideas which have been in play. Early neural network research was motivated mainly by the goals of artificial intelligence (AI) and of functional neuroscience (biological intelligence, BI), but the field almost died due to frustrations articulated in the famous book Perceptrons by Minsky and Papert. When I found a way to overcome the difficulties by 1974, the community mindset was very resistant to change; it was not until 1987/1988 that the field was reborn in a spectacular way, leading to the organized communities now in place. Even then, it took many more years to establish crossdisciplinary research in the types of mathematical neural networks needed to really understand the kind of intelligence we see in the brain, and to address the most demanding engineering applications. Only through a new (albeit short-lived) funding initiative, funding crossdisciplinary teams of systems engineers and neuroscientists, were we able to fund the critical empirical demonstrations which put our old basic principle of "deep learning" firmly on the map in computer science. Progress has rightly been inhibited at times by legitimate concerns about the "Terminator threat" and other possible abuses of technology. This year, at SPIE, in the quantum computing track, we outline the next stage ahead of us in breaking out of the box, again and again, and rising to fundamental challenges and opportunities still ahead of us

Combined Use of Sensitivity Analysis and Hybrid Wavelet-PSO- ANFIS to Improve Dynamic Performance of DFIG-Based Wind Generation

In the past few decades, increasing growth of wind power plants causes different problems for the power quality in the grid. Normal and transient impacts of these units on the power grid clearly indicate the need to improve the quality of the electricity generated by them in the design of such systems. Improving the efficiency of the large-scale wind system is dependent on the control parameters. The main contribution of this study is to propose a sensitivity analysis approach integrated with a novel hybrid approach combining wavelet transform, particle swarm optimization and an Adaptive-Network-based Fuzzy Inference System (ANFIS) known as Wavelet-ANFIS-PSO to acquire the optimal control of Doubly-Fed Induction Generators (DFIG) based wind generation. In order to mitigate the optimization complexity, sensitivity analysis is offered to identify the Unified Dominate Control Parameters (UDCP) rather than optimization of all parameters. The robustness of the proposed approach in finding optimal parameters, and consequently achieve a high dynamic performance is confirmed on two area power system under different operating conditions

Small-Scale Smart Grid Construction and Analysis

The smart grid (SG) is a commonly used catch-phrase in the energy industry yet there is no universally accepted definition. The objectives and most useful concepts have been investigated extensively in economic, environmental and engineering research by applying statistical knowledge and established theories to develop simulations without constructing physical models. In this study, a small-scale version (SSSG) is constructed to physically represent these ideas so they can be evaluated. Results of construction show data acquisition three times more expensive than the grid itself although mainly due to the incapability to downsize 70% of data acquisition costs to small-scale. Experimentation on the fully assembled grid exposes the limitations of low cost modified sine wave power, significant enough to recommend pure sine wave investment in future SSSG iterations. Findings can be projected to full-size SG at a ratio of 1:10, based on the appliance representing average US household peak daily load. However this exposes disproportionalities in the SSSG compared with previous SG investigations and recommended changes for future iterations are established to remedy this issue. Also discussed are other ideas investigated in the literature and their suitability for SSSG incorporation. It is highly recommended to develop a user-friendly bidirectional charger to more accurately represent vehicle-to-grid (V2G) infrastructure. Smart homes, BEV swap stations and pumped hydroelectric storage can also be researched on future iterations of the SSSG

Developing a Simulation Model for Power Demand Control Analysis and Privacy Protection in Smart Grid

With the growing awareness of the need for Smart Grid, various countries are taking initiatives for developing Smart Grid. However, there is limited research on utilizing Smart Grid for Power Demand Control compared to the other areas such as Smart Grid communication network or renewable energy integration. Therefore, this study attempts to help the current Outage Management System by creating a Simulator that allows an intuitive power demand control analysis. Electrical usage is simulated by taking various inputs including the number of houses, family size, work and life patterns, electrical devices, time, etc. For accurate estimate of family and life style, US census data has been used. The graphical interface allows generating the electrical usage data, then it displays both individual and aggregate usage data over time. Through the two-way communication capability of Smart Grid, the devices can be remotely and dynamically controlled by the provider to meet the power supply condition. The simulator demonstrates that substantial amount of electric power can be reduced efficiently by selective demand control over Smart Grid. Furthermore, this study explores potential privacy issues in Smart Grid and suggests data anonymization as a viable solution. Recommendations for future studies are proposed as well

Towards the next generation of smart grids: semantic and holonic multi-agent management of distributed energy resources

The energy landscape is experiencing accelerating change; centralized energy systems are being decarbonized, and transitioning towards distributed energy systems, facilitated by advances in power system management and information and communication technologies. This paper elaborates on these generations of energy systems by critically reviewing relevant authoritative literature. This includes a discussion of modern concepts such as ‘smart grid’, ‘microgrid’, ‘virtual power plant’ and ‘multi-energy system’, and the relationships between them, as well as the trends towards distributed intelligence and interoperability. Each of these emerging urban energy concepts holds merit when applied within a centralized grid paradigm, but very little research applies these approaches within the emerging energy landscape typified by a high penetration of distributed energy resources, prosumers (consumers and producers), interoperability, and big data. Given the ongoing boom in these fields, this will lead to new challenges and opportunities as the status-quo of energy systems changes dramatically. We argue that a new generation of holonic energy systems is required to orchestrate the interplay between these dense, diverse and distributed energy components. The paper therefore contributes a description of holonic energy systems and the implicit research required towards sustainability and resilience in the imminent energy landscape. This promotes the systemic features of autonomy, belonging, connectivity, diversity and emergence, and balances global and local system objectives, through adaptive control topologies and demand responsive energy management. Future research avenues are identified to support this transition regarding interoperability, secure distributed control and a system of systems approach

Una aproximación a la adopción de medidores inteligentes en el mercado eléctrico colombiano y su influencia en la demanda

Resumen: La creciente demanda de electricidad y los elevados picos en la curva de carga hacen necesarias fuertes inversiones en infraestructura para poder suplir las necesidades de los usuarios en los cortos periodos de tiempo en los que se dan, lo que conlleva a que se deba tener gran capacidad instalada solo para periodos cortos del día. Es por esto que se deben buscar opciones y nuevos desarrollos que permitan suplir satisfactoriamente estas necesidades y que se utilicen los recursos del sistema eficientemente. Debido a esto nacen las Redes Eléctricas Inteligentes como un enfoque para mejorar las condiciones actuales del sistema y brindar a los usuarios mayor autonomía en la cadena de suministro. El foco de esta investigación son los hogares, ya que estos pueden monitorear se demanda y mover una parte de esta lo cual ayuda a reducir los picos de la curva de carga. Para poder hacer esto los usuarios deben usar medidores inteligentes, por medio de los cuales se puede medir y controlar su demanda horaria. Dado lo anterior se desea estudiar el posible comportamiento de los usuarios ante la entrada de los medidores inteligentes en el sistema eléctrico colombiano y evaluar cómo sería el cambio en la curva de carga con los cambios en los hábitos de consumo de los hogares.Abstract: The high growth in electricity demand and the peaks in the load curve make it necessary to make big investments in infrastructure in order to meet the needs of users, which causes the necessity of capacity for short periods of time. This is why it is necessary to look for new developments that allow meeting the needs of users as well as using the electricity system resources efficiently. This is why we have researched Smart Grid (SG), which is an approach to improve conditions of the current system and to allow for users to have autonomy in the electricity supply chain. The focus of this research is households, because they can monitor their demand and move a part of this which helps to reduce the load curve peaks. To do this, users must use smart meters, through which it is possible to measure and control the hourly demand. Based on the aforementioned, the possible user’s behavior with Smart meters implementation in the Colombian electricity system will be studied and the change in the load curve given by habits change by household will be evaluated.Maestrí