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All Journal Research of Scientia Naturalis Journal of Social Entrepreneurship and Creative Technology
Johannes Muller
University of Heidelberg
Agriculture, Biological Sciences & Forestry Chemistry Decision Sciences, Operations Research & Management Physics

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OPTIMIZATION OF RENEWABLE ENERGY GRIDS USING COMPUTATIONAL INTELLIGENCE AND HEURISTIC ALGORITHMS FOR RESILIENT AND SUSTAINABLE POWER DISTRIBUTION Sulaiman Sulaiman; Johannes Muller; Oliver Harris
Research of Scientia Naturalis Vol. 3 No. 2 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/scientia.v3i2.4169

Abstract

Rapid expansion of renewable energy resources has increased the operational complexity of modern electricity grids as intermittent generation, distributed energy resources, and dynamic demand challenge conventional optimization methods. This study evaluated the effectiveness of computational intelligence and heuristic algorithms in optimizing renewable energy grids by improving power system resilience, renewable energy utilization, operational efficiency, and adaptive grid management. A mixed-methods sequential explanatory design was applied using 2,400 simulation scenarios across forty benchmark renewable energy distribution systems with varying renewable penetration, battery storage capacities, distributed generation configurations, and demand response conditions. Quantitative analyses included structural equation modeling, hierarchical regression, multivariate analysis, mediation, and moderation analyses, while qualitative evidence from expert interviews, engineering discussions, and technical document reviews was examined through thematic analysis. The findings showed that hybrid computational intelligence algorithms consistently outperformed conventional optimization approaches by enhancing renewable energy utilization, reducing power losses, improving voltage stability, accelerating computational convergence, and strengthening grid resilience. Distributed energy coordination and renewable forecasting further improved optimization performance under uncertain operating conditions. Overall, intelligent optimization represents an adaptive cyber-physical framework integrating renewable generation, energy storage, and demand response into resilient and sustainable electricity distribution systems. The proposed framework provides practical guidance for utility operators, system planners, and policymakers to accelerate reliable renewable energy integration while supporting long-term decarbonization and sustainable power system transformation.
MICROBIAL CONSORTIA ENGINEERING: BRIDGING ENVIRONMENTAL MICROBIOLOGY AND SYNTHETIC BIOLOGY Achmad Agus Salim; Lucas Wong; Johannes Muller
Research of Scientia Naturalis Vol. 3 No. 1 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/scientia.v3i1.3342

Abstract

Natural ecosystems rely on complex microbial interactions that surpass the metabolic capabilities of isolated monocultures, yet engineering stable multi-species systems remains a significant challenge in biotechnology. This research addresses the unpredictability of interspecies social dynamics by integrating principles from environmental microbiology with the precision of synthetic biology. The study aims to evaluate a rational design framework for “obligate syntrophy” to maintain community stability and enhance metabolic throughput during the processing of complex feedstocks. Utilizing a “bottom-up” methodology, a synthetic consortium of Escherichia coli and Pseudomonas putida was engineered with cross-feeding circuits and quorum-sensing feedback loops for real-time population regulation. Results demonstrate that the engineered consortia achieved a stable co-existence for over 240 hours, representing a 45% increase in biomass yield and a 70% improvement in detoxification efficiency compared to non-engineered mixed cultures. Statistical analysis confirms that the division of metabolic labor significantly reduces individual cellular burden while increasing overall community resilience. This research concludes that bridging ecological wisdom with genetic circuit design provides a superior architecture for robust industrial bioprocessing. The findings offer a scalable blueprint for “programmable ecology,” asserting that engineered microbial consortia are essential for unlocking the full potential of the global circular bioeconomy.
CREATIVE BUSINESS MODELS FOR SOCIAL CHANGE: INTEGRATING TECHNOLOGY, COMMUNITY, AND SUSTAINABILITY Arteurt Yoseph Merung; Ethan Tan; Li Wei; Johannes Muller
Journal of Social Entrepreneurship and Creative Technology Vol. 3 No. 1 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jseact.v3i1.3297

Abstract

The growing complexity of social and environmental challenges has exposed the limitations of conventional business models that prioritize economic value over societal well-being. In response, creative business models have emerged as alternative approaches that integrate technology, community engagement, and sustainability to generate social change. This study aims to examine how such creative business models are structured and how the integration of technological enablement, community participation, and sustainability principles contributes to long-term social impact. The research employs a qualitative and exploratory design based on secondary data analysis of peer-reviewed literature, policy reports, and documented case studies of social enterprises and community-based ventures. Thematic and cross-case analysis was conducted to identify recurring patterns of value creation, governance, and innovation processes. The findings reveal that social change-oriented business models are most effective when technology functions as an enabling infrastructure, communities act as co-creators rather than beneficiaries, and sustainability is embedded as a core value logic. Integrated models demonstrate greater resilience, legitimacy, and adaptability compared to fragmented approaches. The study concludes that creative business models represent a viable pathway for aligning economic activity with social and environmental objectives. Strengthening integration among technology, community, and sustainability is essential for advancing inclusive and sustainable societal transformation.
Co-Authors Achmad Agus Salim Arteurt Yoseph Merung Ethan Tan Li Wei Lucas Wong Oliver Harris Sulaiman Sulaiman