APPLICATION OF SOLAR ENERGY TO MEASURE PHOTOVOLTAIC CAPACITY AND BATTERY OPTIMIZATION

Unang Achlison; Iman Saufik Suasana; Dendy Kurniawan

doi:10.51903/jtie.v1i1.145

Unang Achlison Universita Sains dan Teknologi Komputer
Iman Saufik Suasana Universita Sains dan Teknologi Komputer
Dendy Kurniawan Universita Sains dan Teknologi Komputer

DOI: https://doi.org/10.51903/jtie.v1i1.145

Keywords: Solar Energy, Battery Optimization, Markov Decision Process, Photovoltaic, Virtual Container

Abstract

This study uses the Markov Decision Model (MDP) to implement battery degradation and optimize battery use in Photovoltaic and the battery system model created. The battery optimization scheme for home loads uses the application of solar energy to optimally measure photovoltaic and battery capacity against each other. The different qualities of the standard used in this study are described starting from system characteristics and charge settings to an analysis of MDP and battery degeneration. Various systems undergo a list of analyses to implement awareness reasoning although developing battery volume and photovoltaic for the current system. The parametric span of cosmic and battery central tariff, the tariff of power worn taken away the framework, tariff of battery degeneration, time of year, photovoltaic generator size, battery size, and Health Status (SoH) of batteries were carried out to determine the optimal volume estimate and analyze the trade-offs essential in a mix scheme. This is then used to treasure trove the minimum amount of fee of the scheme with photovoltaic and battery application.

This study support decision of the essential sizing deliberation for photovoltaic and battery-managed home loads linked to the services grid. Insightful that the battery can be used more destructively, also it can be formed lower and run at a greater C speed. This study analyzes actual fog computing research tools and storage composition algorithms for fog computing and develops a fog computing monitoring framework to provide data for fog computing storage composition algorithms. The framework proposed in this study provides granular container virtual hardware resource information and black box monitoring of service layer information associated with microservices. Framework usefulness on Raspberry Pis and CPU overhead of framework tested.

The results of this study present the framework proposed could be used on single-chip microcomputers with relatively inadequate computational performance. In addition, a minimal effect on the battery degeneration system on the MDP decision due to the low system C-rate limit for the battery and interesting behavior of total fee and demand is also found. For future research, testing different maximum C levels should be considered to determine the photovoltaic size and battery system affected. Various battery optimization systems can be proved to check the benefit and disbenefits in the microgrid system case study. Lastly, collecting a scheme for actual-time reproduction to know how nice the operation is performing is the next stage of implementing MDP for battery management and system development.

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