Game-theoretic approaches for smart prosumer communities

Global warming is endangering the Earth’s ecosystem. It is imperative for humanity to limit greenhouse gas emissions in order to combat rising global average temperatures. Demand-side management (DSM) schemes have widely been analysed in the context of the future smart grid. Often they are based on game-theoretic approaches to schedule the electricity consumption of its participants such that it results in small peak-to-average ratios (PAR) of the aggregated load. In order to guarantee high comfort levels for the consumer, we investigate DSM schemes on the basis of individually owned energy storage systems. The scheduling of these batteries is incentivised by a specific pricing function offered to the users. Within this thesis we cover various aspects for these type of management schemes. Firstly, we design a simple game-theoretic scheduling mechanism and analyse how the battery model, more specifically the round-trip efficiency, affects the outcome. From the simulations we find the importance of highly efficient energy storage systems for the engagement of participants. Secondly, the simple scheduling mechanism is replaced with a more advanced dynamic game, that models fine-grained control over the battery. For this novel game, we derive an analytical solution for the best response of a user, considerably speeding up the solution algorithm for the game. Furthermore, a comparison between the two games also shows the improvements in reducing the PAR of the aggregated load. Based on the augmented game, we investigate the resilience of the equilibrium solution with respect to inevitable real-world forecasting errors. One of the main findings of this thesis is reflected in the results showing the robustness of the schedules for a large number of simulated scenarios and even in the worst-case. Thirdly, we explicitly deal with the finite horizon effect that occurs due to the fixed time frame of the game mechanism. This eventually leads to a DSM system which results in a mean PAR of the aggregated load close to the optimum. Further studies show that these outcomes can be achieved due to the interaction of the households. Individual scheduling of batteries reduces the potential reduction of PAR and is especially detrimental for the robustness against forecasting errors. Fourthly, the developed model is analysed with respect to cyber-physical attacks. We develop a novel type of data-injection attack on the forecasted data and show their impact. After suggesting suitable monitoring strategies to the utility company, a game-theoretic model is employed to understand their decision making process. Finally, we investigate which battery size is optimal for such a DSM scheme. The respective experiments give insight into the different factors that determine the sizing of the battery. From the results we can infer that certain types of users only require a small scale battery system to achieve considerable gains. Overall, this thesis provides an in-depth analysis of a demand-side management scheme that can be employed by prosumers all around the world in the nearest future. Furthermore, the experiments give insights to utility companies to focus on community approaches and how they can mitigate potential cyber attacks

Multi-busbar sub-module modular multilevel converter

Modular multilevel converter (MMC) plays increasingly significant roles in large scale power electronics system including high voltage direct current (HVDC) system, static synchronous compensator (STATCOM), large scale energy storage, motor control, and so on, thanks to its advantages including modular configurations, reduced dv/dt, low total harmonic distortions, and low power losses. The classic sub-module (SM) topologies (e.g. half or full bridge types) all have in common their single connection arrangement between each SM in their series connection within a stack; i.e. a single busbar. This single busbar arrangement does come however with some drawbacks in terms of performance, reliability and flexibility. The lack of redundant switching states limits the potential optimization for the whole MMC. To solve the above mentioned issue, this thesis presents the control and performance of a new topology of SMs for MMCs, which uses multiple parallel connections between SMs and is referred to as multi-busbar sub-module (MBSM). Stacks made entirely of MBSMs can see improved functionalities such as pre-charging capability, capacitor paralleling, lower power losses, improved reliability, and a rational bypass mechanism in the event of SM failure. The soft-parallel mechanism is proposed to maintain voltage balancing without the requirement of additional spike current inductors. Despite the fact that the number of semiconductors in MBSM MMC has been doubled, semiconductor losses have been reduced to 80% of those in its counterpart. Simulation results have verified the characteristics of a FB MBSM MMC in an HVDC scenario. Several advanced control schemes for the control of the MBSM MMC are also investigated, including an algorithm to automatically generate independent variables state space models from linear electrical circuits, a model predictive control-based start-up controller to simplify the SM pre-charge procedure and at the same time improve the transient performance, and a reinforcement learningbased low-level controller to achieve low switching frequency operation of the MBSM MMC. The control schemes are validated by detailed theoretical analysis and simulation results. Besides, some MBSM applications in the operation scenarios of STATCOM are studied. Two topologies of delta-configured, partially rated energy storage (PRES) MBSM STATCOM and their corresponding low-level controllers are presented to improve the active power output capability. The soft parallel of MBSM is more effective in reactive power mode than active power mode due to the location of ES, which sees their current circulation limited to their own SM capacitor. The proposed controller for the MBSM STATCOM dynamically switches between two operation modes to reduce the converter losses over the extended range of active power. Simulation results confirm the earlier point, in that PRES-MBSMSTATCOM performs better at pure reactive power set-points and marginally better at high active power. This is explained by the fact that MBSM operates more frequently in soft-paralleling mode when the ES releases less power, i.e. reactive power set-points. Then the MBSM concept is further extended to a structure with more busbars, named multi-H-bridge SM, aiming at solving the current sharing issue of paralleled discrete SiC MOSFETs in large current applications. When compared to conventional FBSM constructed directly paralleled SiC MOSFETs, simulation results show that the current sharing performance against on-state resistance mismatch is improved and the switching loss is reduced. The same converter rating can be achieved with fewer MHSMs compared with Si IGBT SMs. Finally, the designing process of a benchtop-scale, low-voltage, open-source, and affordable hardware prototype of a MMC, the μMMC, is presented with a case study of a three-phase inverter-mode MMC. The proposed μMMC is configured as full bridge SMs type in the experiment, yet the flexible structure makes it capable to be configured as other SM types, including MBSMs. The cost for a single μMMC could be around 50 pounds. The control framework and concrete implementation are presented in detail. With the application of the μMMC, the STM32Cube Hardware Abstraction Layer, and the MATLAB/Simulink hardware support packages, it is possible to shorten the transition process from simulation to hardware realization to several hours. The experiment setup and results of a three-phase inverter mode MMC validate the proposed μMMC’s effectiveness, scalability, and convenience

Sustainable Building and Indoor Air Quality

This Special Issue addresses a topic of great contemporary relevance; in developed countries, most of peoples’ time is spent indoors and, depending on each person, the presence in the home ranges from 60% to 90% of the day, and 30% of that time is spent sleeping. Taking into account these data, indoor residential environments have a direct influence on human health. In addition to this, in developing countries, significant levels of indoor pollution make housing unsafe, with a detrimental impact on the health of inhabitants. Housing is therefore a key health factor for people all over the world, and various parameters such as air quality, ventilation, hygrothermal comfort, lighting, physical environment, and building efficiency, among others, can contribute to healthy architecture, and the conditions that can result from the poor application of these parameters

Generalized averaged Gaussian quadrature and applications

A simple numerical method for constructing the optimal generalized averaged Gaussian quadrature formulas will be presented. These formulas exist in many cases in which real positive GaussKronrod formulas do not exist, and can be used as an adequate alternative in order to estimate the error of a Gaussian rule. We also investigate the conditions under which the optimal averaged Gaussian quadrature formulas and their truncated variants are internal

MS FT-2-2 7 Orthogonal polynomials and quadrature: Theory, computation, and applications

Quadrature rules find many applications in science and engineering. Their analysis is a classical area of applied mathematics and continues to attract considerable attention. This seminar brings together speakers with expertise in a large variety of quadrature rules. It is the aim of the seminar to provide an overview of recent developments in the analysis of quadrature rules. The computation of error estimates and novel applications also are described