Simulation support for internet-based energy services

The rapidly developing Internet broadband network offers new opportunities for deploying a range of energy, environment and health-related services for people in their homes and workplaces. Several of these services can be enabled or enhanced through the application of building simulation. This paper describes the infrastructure for e-services under test within a European research project and shows the potential for simulation support for these services

A nexus perspective on competing land demands: Wider lessons from a UK policy case study

As nations develop policies for low-carbon transitions, conflicts with existing policies and planning tools are leading to competing demands for land and other resources. This raises fundamental questions over how multiple demands can best be managed. Taking the UK as an empirical example, this paper critiques current policies and practices to explore the interdependencies at the water-energy-food nexus. It considers how current land uses and related policies affect the UK’s resilience to climate change, setting out an agenda for research and practice relevant to stakeholders in land-use management, policy and modelling. Despite recent progress in recognising such nexus challenges, most UK land-related policies and associated science continue to be compartmentalised by both scale and sector and seldom acknowledge nexus interconnections. On a temporal level, the absence of an over-arching strategy leaves inter-generational trade-offs poorly considered. Given the system lock-in and the lengthy policy-making process, it is essential to develop alternative ways of providing dynamic, flexible, practical and scientifically robust decision support for policy-makers. A range of ecosystem services need to be valued and integrated into a resilient land-use strategy, including the introduction of non-monetary, physical-unit constraints on the use of particular services

Multiscale design for system-wide peer-to-peer energy trading

The integration of renewable generation and the electrification of heating and transportation are critical for the sustainable energy transition toward net-zero greenhouse gas emissions. These changes require the large-scale adoption of distributed energy resources (DERs). Peer-to-peer (P2P) energy trading has gained attention as a new approach for incentivizing the uptake and coordination of DERs, with advantages for computational scalability, prosumer autonomy, and market competitiveness. However, major unresolved challenges remain for scaling out P2P trading, including enforcing network constraints, managing uncertainty, and mediating transmission and distribution conflicts. Here, we propose a novel multiscale design framework for P2P trading, with inter-platform coordination mechanisms to align local transactions with system-level requirements, and analytical tools to enhance long-term planning and investment decisions by accounting for forecast real-time operation. By integrating P2P trading into planning and operation across spatial and temporal scales, the adoption of large-scale DERs is tenable and can create economic, environmental, and social co-benefits

Large Scale Deployment of Renewables for Electricity Generation

Comparisons of resource assessments suggest resource constraints are not an obstacle to the large-scale deployment of renewable energy technologies. Economic analysis identifies barriers to the adoption of renewable energy sources resulting from market structure, competition in an uneven playing field and various non-market place barriers. However, even if these barriers are removed, the problem of ‘technology lock-out’ remains. The key policy response is strategic deployment coupled with increased R&D support to accelerate the pace of improvement through market experience. The paper suggests significant contributions from various technologies, but does not assess their optimal or maximal market share

Scaling laws of strategic behaviour and size heterogeneity in agent dynamics

The dynamics of many socioeconomic systems is determined by the decision making process of agents. The decision process depends on agent's characteristics, such as preferences, risk aversion, behavioral biases, etc.. In addition, in some systems the size of agents can be highly heterogeneous leading to very different impacts of agents on the system dynamics. The large size of some agents poses challenging problems to agents who want to control their impact, either by forcing the system in a given direction or by hiding their intentionality. Here we consider the financial market as a model system, and we study empirically how agents strategically adjust the properties of large orders in order to meet their preference and minimize their impact. We quantify this strategic behavior by detecting scaling relations of allometric nature between the variables characterizing the trading activity of different institutions. We observe power law distributions in the investment time horizon, in the number of transactions needed to execute a large order and in the traded value exchanged by large institutions and we show that heterogeneity of agents is a key ingredient for the emergence of some aggregate properties characterizing this complex system.Comment: 6 pages, 3 figure

Estimating the Effects of Interest Rates on Share Prices Using Multi-scale Causality Test in Emerging Markets: Evidence from Turkey

This paper examines the impacts of changes in interest rates on stock returns by using wavelet analysis with Granger causality test. Financial time series in non-coherent markets should be analyzed by advanced methods capturing complexity of the markets and non-linearities in stock returns. As a semi-parametric method, wavelets analysis might be superior to detect the chaotic patterns in the non-coherent markets. By using daily closing values of the ISE 100 Index and compounded interest rates, it is proven that and starting with 9 days time-scale effect interest rate is granger cause of ISE 100 index and the effects of interest rates on stock return increases with higher time-scales. This evidence shows that bond market has significant long-term effect on stock market for Turkey and traders should consider long-term money markets changes as well as short-term changes.Interest rates; Emerging markets; Wavelets; Stock returns; Multi-scale Granger causality