Assessing Solar Microgrid Resilience in Coastal Community Utilities Ltd.

Thesis Abstract

Coastal Community Utilities Ltd. operates in a climate-vulnerable coastline where frequent tropical storms and rising sea levels disrupt conventional power delivery, exposing critical vulnerabilities in its solar-driven microgrid portfolio. The study addresses the gap in empirical understanding of resilience attributes—system reliability, operational continuity, and recovery efficiency—within small-to-medium scale solar microgrids serving coastal communities. The aim is to evaluate resilience performance of CCC Utilities’ solar microgrids under hydro-meteorological stressors and to identify mechanisms that enhance continuity of service and rapid recovery. Specific objectives are (i) characterize the resilience requirements of the coastal microgrid under storm-induced outages; (ii) quantify the relationship between system design parameters (site selection, battery storage capacity, and inverter control strategies) and resilience metrics; (iii) assess governance, maintenance, and operational practices that influence transient and sustained performance; (iv) develop a predictive model for outage duration and restoration time; and (v) propose a framework of engineering and organizational practices to improve resilience. The methodology adopts a mixed-methods approach anchored in the resilience engineering framework and the theory of socio-technical systems. The population comprises all operational solar microgrids within CCC Utilities’ network (n=24). A stratified random sample of 12 microgrids will be selected to ensure representation across coastal zones, load profiles, and storage configurations. Data collection comprises (i) quantitative archival data from SCADA logs and outage records for the past five years, including 1,800 hourly data points per site, (ii) structured surveys and interview protocols with 25 engineers and operators, and (iii) site assessments to document hardware configurations, battery chemistries, and inverter controls. Instruments include a resilience metrics checklist, a reliability-centered maintenance (RCM) data sheet, and a semi-structured interview guide. Validity and reliability will be ensured through triangulation, pilot testing, and inter-rater reliability checks (Cronbach’s alpha target ?0. eight for survey scales). Data analysis will proceed in three stages (a) descriptive statistics and time-series analyses to establish baseline resilience indicators; (b) regression modeling and survival analysis to identify determinants of outage duration and restoration time; (c) thematic analysis of interview transcripts to elucidate organizational and governance factors, guided by the Normal Accident Theory and the Resilience Engineering paradigm. A finite-state machine model will be used to simulate microgrid operation under predefined storm scenarios, and an optimization framework utilizing multi-criteria decision analysis (MCDA) will evaluate trade-offs between storage capacity, dispatch strategies, and resilience outcomes. Expected findings indicate that resilience is significantly influenced by (i) storage adequacy relative to peak load and renewable intermittency, (ii) intelligent dispatch strategies incorporating islanded operation and demand response, (iii) proactive maintenance practices and rapid fault isolation, and (iv) governance protocols for collaborative decision-making during extreme events. The study anticipates that microgrids with modular battery configurations, adaptive inverter controls, and formalized outage response playbooks will demonstrate shorter restoration times and higher reliability during storm events. The contribution to knowledge lies in a context-specific resilience assessment framework for coastal solar microgrids, integrating engineering design, operation analytics, and organizational practices, and in a validated predictive model linking design variables to resilience outcomes. The research will offer practical recommendations for CCC Utilities, including recommended storage capacities per site, standardized islanding procedures, enhanced SCADA-based monitoring for resilience metrics, and governance reforms to streamline disaster response. The main conclusion is that resilience gains are maximized when technical design enhancements are closely aligned with organizational readiness and cross-functional coordination. Recommendations include (i) increasing storage capacity to maintain at least 30% of peak local load during outages, (ii) implementing adaptive dispatch algorithms with islanding enabled by real-time frequency and voltage support, (iii) adopting a formal resilience governance framework with defined roles, decision rights, and after-action review processes, and (iv) establishing routine resilience drills and shared data platforms across the network to support continuous improvement.