Modelling Dynamic Constraints in Electricity Markets and the Costs of Uncertain Wind Output

Building on models that represent inter-temporal constraints in the optimal production decisions for electricity generation,the paper analysis the resulting costs and their impact on prices during the day. We linearise the unit commitment problem to facilitate th

Overview of Energy Management and Leakage Control Systems for Smart Water Grids and Digital Water

Current and future smart cities are moving towards the zero-net energy use concept. To this end, the built environment should also be designed for efficient energy use and play a significant role in the production of such energy. At present, this is achieved by focusing on energy demand in buildings and to the renewable trade-off related to smart power grids. However, urban water distribution systems constantly carry an excess of hydraulic energy that can potentially be recovered to produce electricity. This paper presents a comprehensive review of current strategies for energy production by reviewing the state-of-the-art of smart water systems. New technologies (such as cyber-physical systems, digital twins, blockchain) and new methodologies (network dynamics, geometric deep learning) associated with digital water are also discussed. The paper then focuses on modelling the installation of both micro-turbines and pumps as turbines, instead of/together with pressure reduction valves, to further demonstrate the energy-recovery methods which will enable water network partitioning into district metered areas. The associated benefits on leakage control, as a source of energy, and for contributing to overall network resilience are also highlighted. The paper concludes by presenting future research directions. Notably, digital water is proposed as the main research and operational direction for current and future Water Distribution Systems (WDS) and as a holistic, data-centred framework for the operation and management of water networks.</jats:p

Optimal Transmission Investment Strategies for Sustainable Power Systems

Maintaining security and reliability in the electricity supply is fundamental to the functioning of a modern society and drives the need for adequate transmission capacity for both market participants and customers. Planning the investment in transmission has always been a complicated undertaking due to the high development costs and long lead times. Furthermore, to anticipate the future needs of customers is a task as difficult as that of cost-effective planning and construction of new facilities. Trying to find treatments for some of these issues represents a major motivation for this thesis. This thesis investigates the problem of how much reinforcement a transmission system requires when a significant proportion of wind generation is integrated into an existing transmission system. A multi-period transmission planning model is developed for determining optimal transmission capacity by balancing amortised transmission investment costs and annual generation costs subject to network security constraints, The model employs the security-constrained DC optimal power flow formulation and applies a solver (DashXpress) to obtain the results of the remaining linear large-scale optimisation problem. This thesis begins by exploring the impact of wind generation on the determination of appropriate levels of system capacity on the transmission network starting from the premise that it is no longer cost effective to invest in sufficient network capacity to accommodate simultaneous peaks from all generators. As such, a significant finding of this study is that conventional and wind generation should share network capacity. Given the acknowledged increase in uncertainty to security of supply due to difficulties in wind generation forecast this thesis also explores the optimal sourcing of generation reserve, and investigates investment in transmission capacity to exploit the cost benefits offered by standing reserve. Finally, the thesis presents and evaluates an alternative associated with transmission operation and investment level of risk and uncertainty by introducing more flexibility to the way the transmission system is operated. Application of Quadrature Boosters and Demand Side as model of corrective control, brings savings in operating costs without jeopardizing the level of system security, enables better utilisation of existing facilities and reduces the demand for new transmission investment

Operational Research: Methods and Applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order. The authors dedicate this paper to the 2023 Turkey/Syria earthquake victims. We sincerely hope that advances in OR will play a role towards minimising the pain and suffering caused by this and future catastrophes

Building-integrated rooftop greenhouses: an energy and environmental assessment in the mediterranean context

A sustainable and secure food supply within a low-carbon and resilient infrastructure is encapsulated in several of The United Nations’ 17 sustainable development goals. The integration of urban agriculture in buildings can offer improved efficiencies; in recognition of this, the first south European example of a fully integrated rooftop greenhouse (iRTG) was designed and incorporated into the ICTA-ICP building by the Autonomous University of Barcelona. This design seeks to interchange heat, CO2 and rainwater between the building and its rooftop greenhouse. Average air temperatures for 2015 in the iRTG were 16.5 °C (winter) and 25.79 °C (summer), making the iRTG an ideal growing environment. Using detailed thermophysical fabric properties, 2015 site-specific weather data, exact control strategies and dynamic soil temperatures, the iRTG was modelled in EnergyPlus to assess the performance of an equivalent ‘freestanding’ greenhouse. The validated result shows that the thermal interchange between the iRTG and the ICTA-ICP building has considerable moderating effects on the iRTG’s indoor climate; since average hourly temperatures in an equivalent freestanding greenhouse would have been 4.1 °C colder in winter and 4.4 °C warmer in summer under the 2015 climatic conditions. The simulation results demonstrate that the iRTG case study recycled 43.78 MWh of thermal energy (or 341.93 kWh/m2/yr) from the main building in 2015. Assuming 100% energy conversion efficiency, compared to freestanding greenhouses heated with oil, gas or biomass systems, the iRTG delivered an equivalent carbon savings of 113.8, 82.4 or 5.5 kg CO2(eq)/m2/yr, respectively, and economic savings of 19.63, 15.88 or 17.33 €/m2/yr, respectively. Under similar climatic conditions, this symbiosis between buildings and urban agriculture makes an iRTG an efficient resource-management model and supports the promotion of a new typology or concept of buildings with a nexus or symbiosis between energy efficiency and food production.Postprint (published version

Strategic decision-making in multi-agent markets: The emergence of endogenous crises and volatility

Traditional economic frameworks are built upon perfectly rational agents and equilibrium outcomes. However, during times of crises, these frameworks prove insufficient. In this thesis, we take an alternative perspective based on "Complexity Economics", relaxing the assumption of perfectly rational agents and allowing for out-of-equilibrium dynamics. While many contemporary approaches explain crises and non-equilibrium market phenomena as the rational reaction to external news, the emergence of endogenous crises remains an open question. We begin addressing this question by demonstrating how a multi-agent model of heterogeneous boundedly rational agents acting according to heuristics can reproduce and forecast key non-linear price movements in the Australian housing market, during boom and bust cycles. In order to provide foundations for such heuristic-based reasoning, we then propose a novel information-theoretic approach, Quantal Hierarchy, for modelling limitations in strategic reasoning, demonstrating how this convincingly and generically captures the decision-making of interacting agents in competitive markets outperforming existing approaches. In addition, we demonstrate how a concise generalised market model can generate important stylised facts, such as fat-tails and volatility clustering, and allow for the emergence of crises, purely endogenously. This thesis provides support to the interacting agent hypothesis, addressing a crucial question of whether crisis emergence and various stylised facts can be seen as endogenous phenomena, and provides a generic method for representing strategic agent reasoning