Electricity demand forecasting for decentralised energy management

The world is experiencing a fourth industrial revolution. Rapid development of technologies is advancing smart infrastructure opportunities. Experts observe decarbonisation, digitalisation and decentralisation as the main drivers for change. In electrical power systems a downturn of centralised conventional fossil fuel fired power plants and increased proportion of distributed power generation adds to the already troublesome outlook for operators of low-inertia energy systems. In the absence of reliable real-time demand forecasting measures, effective decentralised demand-side energy planning is often problematic. In this work we formulate a simple yet highly effective lumped model for forecasting the rate at which electricity is consumed. The methodology presented focuses on the potential adoption by a regional electricity network operator with inadequate real-time energy data who requires knowledge of the wider aggregated future rate of energy consumption. Thus, contributing to a reduction in the demand of state-owned generation power plants. The forecasting session is constructed initially through analysis of a chronological sequence of discrete observations. Historical demand data shows behaviour that allows the use of dimensionality reduction techniques. Combined with piecewise interpolation an electricity demand forecasting methodology is formulated. Solutions of short-term forecasting problems provide credible predictions for energy demand. Calculations for medium-term forecasts that extend beyond 6-months are also very promising. The forecasting method provides a way to advance a novel decentralised informatics, optimisation and control framework for small island power systems or distributed grid-edge systems as part of an evolving demand response service

Achieving Very High PV Penetration

This article argues that optimally deployed intermittency solutions could affordably transform solar power generation into the firm power delivery system modern economies require, thereby enabling very high solar penetration and the displacement conventional power generation. The optimal deployment of these high‐penetration enabling solutions imply the existence of a healthy power grid, and therefore imply a central role for utilities and grid operators. This article also argues that a value‐based electricity compensation mechanism, recognizing the multifaceted, penetration‐dependent value and cost of solar energy, and capable of shaping consumption patterns to optimally match resource and demand, would be an effective vehicle to enable high solar penetration and deliver affordable firm power generation

Digital Ecosystems: Ecosystem-Oriented Architectures

We view Digital Ecosystems to be the digital counterparts of biological ecosystems. Here, we are concerned with the creation of these Digital Ecosystems, exploiting the self-organising properties of biological ecosystems to evolve high-level software applications. Therefore, we created the Digital Ecosystem, a novel optimisation technique inspired by biological ecosystems, where the optimisation works at two levels: a first optimisation, migration of agents which are distributed in a decentralised peer-to-peer network, operating continuously in time; this process feeds a second optimisation based on evolutionary computing that operates locally on single peers and is aimed at finding solutions to satisfy locally relevant constraints. The Digital Ecosystem was then measured experimentally through simulations, with measures originating from theoretical ecology, evaluating its likeness to biological ecosystems. This included its responsiveness to requests for applications from the user base, as a measure of the ecological succession (ecosystem maturity). Overall, we have advanced the understanding of Digital Ecosystems, creating Ecosystem-Oriented Architectures where the word ecosystem is more than just a metaphor.Comment: 39 pages, 26 figures, journa

e-Report Generator Supporting Communications and Fieldwork: A Practical Case of Electrical Network Expansion Projects

In this piece of work we present a simple way to incorporate Geographical Information System tools that have been developed using open source software in order to help the different processes in the expansion of the electrical network. This is accomplished by developing a novel fieldwork tool that provides the user with automatically generated enriched e-reports that include information about every one of the involved private real estates in a specific project. These reports are an eco-friendly alternative to paper format, and can be accessed by clients using any kind of personal device with a minimal set of technical requirements

Technical Change Theory and Learning Curves: Patterns of Progress in Energy Technologies

This paper presents a comparative analysis of energy technology learning and progress within the framework of Schumpeter’s invention-innovation-diffusion paradigm. We estimate learning by doing and research rates for a range of energy technologies in four stages of technical progress. Emerging and mature technologies respond slowly to research and development (R&D) and capacity expansion; evolving technologies exhibit high learning-by-doing and research rates; reviving technologies exhibit considerable response to learning-by-research although they do not face significant market constraints. We generally find higher learning-by-doing than learning-by-research rates but do not find any development stage where learning-by-doing alone is the dominant driver of technical change. Also, high capital intensity and market constraints appear to slow down the pace of progress of emerging and evolving technologies. We find little scope for potential substitution between learning-by-doing and learning-by-research across the technologies and different stages of their development path

Temporal relations between mineral deposits and global tectonic cycles

Natural Environment Research Council (grant NE/J021822/1) supported this research.Mineral deposits are heterogeneously distributed in both space and time, with variations reflecting tectonic setting, evolving environmental conditions, as in the atmosphere and hydrosphere, and secular changes in the Earth’s thermal history. The distribution of deposit types whose settings are tied to plate margin processes (e.g. orogenic gold, volcanic-hosted massive sulphide, Mississippi valley type Pb–Zn deposits) correlates well with the supercontinent cycle, whereas deposits related to intra-cratonic settings and mantle-driven igneous events, such as Ni–Cu–PGE deposits, lack a clear association. The episodic distribution of deposits tied to the supercontinent cycle is accentuated by selective preservation and biasing of rock units and events during supercontinent assembly, a process that encases the deposit within the assembled supercontinent and isolates it from subsequent removal and recycling at plate margins.Publisher PD

A dynamic simulation of low-carbon policy influences on endogenous electricity demand in an isolated island system

This paper considers the dynamics of electricity demand in response to changes arising from low-carbon policies and socio-economic developments. As part of an investigation into the evolution of such systems on small economically-developed islands, endogenous electricity demand and associated policies are studied for the Azorean island of São Miguel. A comprehensive System Dynamics (SD) model covering the period 2005 − 2050 is presented which captures both historical behaviours and real-world influences on the endogenous demand dynamics of an island-based electricity system. The impact of tourism, energy efficiency and electric vehicles (EV) expansion allied with associated policy options, are critically evaluated by the SD model using a series of scenarios. The model shows that energy efficiency measures exhibit the most significant long-term impact on electricity demand, while in contrast, policies to increase tourism have a much less direct impact and EV expansion has thought-provoking impacts on the long-term demand, although this is not as influential as energy efficiency measures

Adaptive Governance and Evolving Solutions to Natural Resource Conflicts

New Zealand is facing increasing challenges in managing natural resources (land, freshwater, marine space and air quality) under pressures from domestic (population growth, agricultural intensification, cultural expectations) and international (climate change) sources. These challenges can be described in terms of managing ‘wicked problems’; i.e. problems that may not be understood fully until they have been solved, where stakeholders have different world views and frames for understanding the problem, the constraints affecting the problem and the resources required to solve it change over time, and no complete solution is ever actually found. Adaptive governance addresses wicked problems through a framework to engage stakeholders in a participative process to create a long term vision. The vision must identify competing goals and a process for balancing them over time that acknowledges conflicts cannot always be resolved in a single lasting decision. Circumstances, goals and priorities can all vary over time and by region. The Resource Management Act can be seen as an adaptive governance structure where frameworks for resources such as water may take years to evolve and decades to fully implement. Adaptive management is about delivery through an incremental/experimental approach, limits on the certainty that governments can provide and stakeholders can demand, and flexibility in processes and results. In New Zealand it also requires balancing central government expertise and resources, with local authorities which can reflect local goals and knowledge, but have varying resources and can face quite distinct issues of widely differing severity. It is important to signal the incremental, overlapping, iterative and time-consuming nature of the work involved in developing and implementing adaptive governance and management frameworks. Managing the expectations of those involved as to the nature of the process and their role in it, and the scope and timing of likely outcomes, is key to sustaining participation.Adaptive capacity; governance; resilience

What Matters to Metros: Foundational Indicators for Economic Competitiveness

Foundational Indicators for Economic Competitiveness helps community leaders identify factors that are associated with economic growth in mid-sized U.S. metropolitan areas in a post-recession economy. This work builds upon six previous iterations (called the dashboard of economic indicators) and assesses the relationship of 55 variables to economic growth across four measures: per capita income, gross metropolitan product (GmP), productivity and employment, between 1990 and 2011.Results of the study indicate that growth is not a one-size-fits-all proposition for America's mid-sized metros. education and innovation remain highly associated with GmP, productivity and per capita income growth over the past two decades, but strong performance in those areas has been insufficient to restore jobs to many of our communities. Alternatively, many metro areas that have been successful in adding jobs, struggle to translate that growth into rising incomes. This research provides data that civic leaders can use to ask more strategic questions about how "growth" can be pursued, and to identify their own distinct approaches to get there