Investigating a Green Economy Transition of the Electricity Sector in the Western Cape Province of South Africa: A System Dynamics Approach

Abstract

The Western Cape Government in South Africa has identified the concept of a green economy as a way to transform the Province's economy to one that is more sustainable from an economic, social, and environmental perspective. System dynamics modelling was used to develop a better understanding of the implications of different green economy policies and investments in the electricity sector of the Western Cape Province. The results suggest that continuing on the current policy path would increase the gap between demand and supply, increase the carbon footprint of the electricity sector, and not provide growth in employment in the sector. Strategic green economy investments are therefore expected to impact positively on a number of indicators across a number of sectors. OPSOMMINGDie Wes-Kaapse Regering van Suid-Afrika het die konsep van die groen ekonomie geïdentifiseer as 'n werktuig om die provinsie se ekonomie te omskep in een wat meer volhoubaar is van 'n ekonomiese, sosiale, en omgewings perspektief af. Stelseldinamika modellering was gebruik om 'n beter begrip te ontwikkel van die moontlike voordele en impakte wat verskillende groen ekonomie beleide en beleggings in die elektrisiteits-sektor van die Wes-Kaap kan bewerkstellig. Die resultate van die modellering stel voor dat die voortsetting van die huidige beginsels en beleid sal lei tot 'n groter gaping tussen die aanvraag en die verskaffing van elektriese krag, 'n groter koolstofvoetspoor van die elektrisiteits-sektor, en geen groei in die werkverskaffing van die sektor nie. Daar word verwag dat strategiese groen ekonomie beleggings 'n positiewe impak sal bewerkstellig in menigte aanwysers.

Financing and Management Strategies for Expanding Green Development Projects: A Case Study of Energy Corporation in China’s Renewable Energy Sector Using Machine Learning (ML) Modeling

“…Technical and logistical challenges encompass the complex engineering and construction requirements of harsh marine environments, including foundation design, turbine installation, cable laying, and maintenance strategies. Environmental considerations emphasize the importance of minimizing adverse impacts on marine ecosystems, necessitating thorough environmental impact assessments, effective mitigation measures and robust monitoring protocols [53][54][55][56][57][58][59][60]. Stakeholder engagement and permitting challenges involve actively involving local communities, fishing industries, and other relevant stakeholders, addressing their concerns and establishing clear communication channels.…”

“…Additionally, larger renewable energy projects structured as green investment trusts, enabling individuals to directly finance assets, could tap into significant pools of private capital that would otherwise be inaccessible. By strategically combining public, private, and citizen capital sources tailored to each phase of project development, broader investments can be mobilized while safeguarding ratepayers and aligning stakeholder interests for sustainable growth [54][55][56][57][58][59][60][61].…”

“…These devices can monitor various parameters including performance, temperature, vibration and energy production, providing real-time insights into the health and performance of the assets. By harnessing the power of Big Data analytics, the collected data can be processed and analyzed to extract meaningful patterns, trends and correlations [55][56][57][58][59][60][61][62]. Advanced algorithms and machine learning techniques can be applied to identify potential issues, predict failures and optimize maintenance schedules.…”

“…Real-time data can be accessed through centralized platforms, enabling asset managers and operators to remotely monitor the performance and health of multiple projects simultaneously. This remote monitoring capability enhances operational efficiency, reduces costs associated with on-site visits and enables prompt response to emerging issues [57][58][59][60][61][62][63]. Moreover, the insights derived from IoT and Big Data analytics can drive continuous improvement and optimization of renewable energy projects.…”

“…AI-enabled algorithms help optimize output mixtures. IoT solutions developed internally reduce reliance on the original equipment manufacturers, limiting data access [51][52][53][54][55][56][57][58]. This gives greater autonomy over long-term operations and value extraction through performance upgrades identified autonomously.…”