Transitioning power distribution grid into nanostructured ecosystem : prosumer-centric sovereignty

PhD ThesisGrowing acceptance for in-house Distributed Energy Resource (DER) installations at lowvoltage level have gained much significance in recent years due to electricity market liberalisations and opportunities in reduced energy billings through personalised utilisation management for targeted business model. In consequence, modelling of passive customers’ electric power system are progressively transitioned into Prosumer-based settings where presidency for Transactive Energy (TE) system framework is favoured. It amplifies Prosumers’ commitments into annexing TE values during market participations and optimised energy management to earn larger rebates and incentives from TE programs. However, when dealing with mass Behind-The-Meter DER administrations, Utility foresee managerial challenges when dealing with distribution network analysis, planning, protection, and power quality security based on Prosumers’ flexibility in optimising their energy needs. This dissertation contributes prepositions into modelling Distributed Energy Resources Management System (DERMS) as an aggregator designed for Prosumer-centered cooperation, interoperating TE control and coordination as key parameters to market for both optimised energy trading and ancillary services in a Community setting. However, Prosumers are primarily driven to create a profitable business model when modelling their DERMS aggregator. Greedy-optimisation exploitations are negative concerns when decisions made resulted in detrimental-uncoordinated outcomes on Demand-Side Response (DSR) and capacity market engagements. This calls for policy decision makers to contract safe (i.e. cooperative yet competitive tendency) business models for Prosumers to maximise TE values while enhancing network’s power quality metrics and reliability performances. Firstly, digitalisation and nanostructuring of distribution network is suggested to identify Prosumer as a sole energy citizen while extending bilateral trading between Prosumer-to- Prosumer (PtP) with the involvements of other grid operators−TE system. Modelling of Nanogrid environment for DER integrations and establishment of local area network infrastructure for IoT security (i.e. personal computing solutions and data protection) are committed for communal engagements in a decentralise setting. Secondly, a multi-layered Distributed Control Framework (DCF) is proposed using Microsoft Azure cloud-edge platform that cascades energy actors into respective layers of TE control and coordination. Furthermore, modelling of flexi-edge computing architecture is proposed, comprising of Contract-Oriented Sensor-based Application Platform (COSAP) employing Multi-Agent System (MAS) to enhance data-sharing privacy and contract coalition agreements during PtP engagements. Lastly, the Agents of MAS are programmed with cooperative yet competitive intelligences attributed to Reinforcement Learning (RL) and Neural Networks (NN) algorithms to solve multimodal socio-economical and uncertainty problems that corresponded to Prosumers’ dynamic energy priorities within the TE framework. To verify the DERMS aggregator operations, three business models were proposed (i.e. greedy-profit margin, collegial-peak demand, reserved-standalone) to analyse comparative technical/physical and economic/social dimensions. Results showed that the proposed TE-valued DERMS aggregator provides participation versatility in the electricity market that enables competitive edginess when utilising Behind-The-Meter DERs in view of Prosumer’s asset scheduling, bidding strategy, and corroborative ancillary services. Performance metrics were evaluated on both domestic and industrial NG environments against IEEE Standard 2030.7-2017 & 2030.8-2018 compliances to ensure deployment practicability. Subsequently, proposed in-house protection system for DER installation serves as an add-on monitoring service which can be incorporated into existing Advance Distribution Management System (ADMS) for Distribution Service Operator (DSO) and field engineers use, ADMS aggregator. It provides early fault detections and isolation processes from allowing fault current to propagate upstream causing cascading power quality issues across the feeder line. In addition, ADMS aggregator also serves as islanding indicator that distinguishes Nanogrid’s islanding state from unintentional or intentional operations. Therefore, a Overcurrent Current Relay (OCR) is proposed using Fuzzy Logic (FL) algorithm to detect, profile, and provide decisional isolation processes using specified OCRs. Moreover, the proposed expert knowledge in FL is programmed to detect fault crises despite insufficient fault current level contributed by DER (i.e. solar PV system) which conventional OCR fails to trigger

A Nano-Biased Energy Management Using Reinforced Learning Multi-Agent on Layered Coalition Model: Consumer Sovereignty

Trends in energy management schema have advanced into legislating consumer-centered solutions due to inclination interests for personal owned distributed energy resources at the low-voltage level. Thence, this paper proposes a tailorable energy manager tool that empowers Prosumer(s) in a nanostructured distribution network to take sole precedence when prosuming optimal services to the energy system. It too acts as an aggregator that attests cooperative energy management processes amongst Prosumers to enhance demand-side responses and economics. The suggested nano-biased energy manager engages multi-agent network as the basis coordinator for peer-to-peer advocacy in a decentralized environment. The agents were then programmed with reinforcement and extreme learning machine intelligence on a layered coalition model to compute joint decision-making processes with constraint relaxation relaxed decision constraints and policies. The problem formulations assure engagement of energy management in the liberalized market is sustainable, reliable, and non-discriminated. Computational validations were analyzed using MATLAB and Java agent development framework on four aggregated Nanogrids representing the residential, commercial, and industrial building. Results have shown positive eco-strategic managerial avenues where cooperative assets scheduling and bidding-abled decorum were autonomously acquired. Reduced operating costs were gained from energy trading profit margin due to strategic use/sell of electricity based on real-time tariff and conferred incentive packages but constrained within the mandatory obligation to demand-side management. The subsidiary, the inauguration of meshed communication infrastructure has shown adequate monitoring and commanding resolutions for decentralized Agent(s) to function collaboratively

Design and Control of a DC Collection System for Modular-Based Direct Electromechanical Drive Turbines in High Voltage Direct Current Transmission

In response to an increasing demand for offshore turbine-based technology installations, this paper proposes to design a DC collection system for multi-connected direct drive turbines. Using tidal stream farm as the testbed model, inverter design and turbine control features were modelled in compliance with high voltage ride-through capabilities that operate in isochronous mode suggested by IEEE1547-2018. The aim of the paper is twofold. Firstly, operation analyses in engaging a single-stage impedance source inverter as an AC-link busbar aggregator to pilot a parallel-connected electromechanical drive system. It uses a closed-loop voltage controller to secure voltage-active power (Volt/Watt) dynamics in correspondence with turbine’s arbitrary output voltage level. It also aspires to truncate active rectification stages at generation-side as opposed to a traditional back-to-back converter. Secondly, a proposition for a torque-controlled blade pitching system is modelled to render a close to maximum power point tracking using blade elevation and mechanical speed manipulations. The reserve active power generation aids with compensating an over-voltage crisis as a substitute for typical reactive power absorption. The proposed Testbed system was modelled in PSCAD, adopting industrial related specifications and real-time ocean current profiles for HVDC transmission operations. Analytical results have shown a positive performance index and transient responses at respective tidal steam turbine clusters that observe fault ride-through criterion despite assertive operating conditions

Apprehending Fault Crises for an Autogenous Nanogrid System: Sustainable Buildings

This paper presents a novel approach for in-house operators to profile and allege fault interferences in a nanogrid system either locally or externally. The proposed hybridized methodology is modeled to apprehend, classify, and locate fault interventions using a heuristic data-driven processing model and a sensing directional flow theorem. Employment of fuzzy control and discrete Fourier transform systems are fused to recompose directional fault relay functionalities. The algorithm is composed of three computational stages: stage 1 quantifies conditional correlate coefficients (COC) based on current and phase angle features sampled at interconnecting feeders, stage 2 engages a fuzzy logic controller to express linguistic truth values against calculated COCs, and stage 3 directs circuit breaker operations advocating post phase-shift aberrations to isolate the faulted region. A nanogrid model inspired by Singapore’s Green Mark Building Incentive is developed in the MATLAB environment consisting of a combine heat and power microturbine, a rooftop photovoltaic system, and battery storage units tied to the 22-kVAC distribution network. Analytical results exhibit practicability and decisive settlements in diagnosing various types of fault crises despite low data logging signal-to-noise ratio. Conjointly, engagements of circuit breakers have rendered accurate switching operations toward isolating faulted regions