Optimal sizing of power systems has a tremendous effective role in reducing the total system cost by preventing unneeded investment in installing unnecessary generating units. This paper presents an optimal sizing and planning strategy for a completely hybrid renewable energy power system in a remote Japanese island, which is composed of photovoltaic (PV), wind generators (WG), battery energy storage system (BESS), fuel cell (FC), seawater electrolysis plant, and hydrogen tank. Demand response programs are applied to overcome the performance variance of renewable energy systems (RESs) as they offer an efficient solution for many problems such as generation cost, high demand peak to average ratios, and assist grid reliability during peak load periods. Real-Time Pricing (RTP), which is deployed in this work, is one of the main price-based demand response groups used to regulate electricity consumption of consumers. Four case studies are considered to confirm the robustness and effectiveness of the proposed schemes. Mixed-Integer Linear Programming (MILP) is utilized to optimize the size of the system’s components to decrease the total system cost and maximize the profits at the same time.

The integration of renewable energy sources into the power grid poses several challenges due to their variability in output power as they primarily depend on weather conditions. As a countermeasure, battery energy storage systems are introduced in order to mitigate output power fluctuations of the renewable energy sources. Moreover, demand response programs have been attracting huge attention as an effective mechanism for efficient energy management. It enables power suppliers to cope with the output uncertainty of renewable energy systems. First step, we propose an HRES design methodology that takes into account one year. In order to find the optimal power supply configuration, it is necessary to take into account the changes in load demand due to weather conditions and seasons for one year. However, the computational cost of simulating one year is huge and requires a rather long simulation time. Therefore, we propose a simplified simulation method that uses clustering to account for changes in load demand due to weather and seasonality in one year. Second, the first proposed method is used to propose a method for optimizing the HRES equipment capacity and operation schedule considering demand response. In this paper, mixed-integer linear programing is used as the optimization method. The proposed method considers two types of demand response and achieves cost reduction by controlling load demand in response to generated power fluctuations.

Deep-sea vesicomyid clams, including the genus Phreagena, harbor obligate sulfur-oxidizing symbiotic bacteria in gill epithelial cells. Difficulty in maintaining Phreagena clams in rearing tanks has been a major obstacle to achieving a better understanding of their unique biology. To improve the method of rearing Phreagena clams, here we reared them in an artificial chemosynthetic aquarium and evaluated the effects of the aquarium system on long-term clam rearing. We compared the survival of clams reared in the artificial chemosynthetic tank with the survival of those in the normal tank, and analyzed the symbiont abundance using semi-quantification of fluorescent in situ hybridization signals. Our results indicate that the artificial chemosynthetic aquarium system had specific effects on symbiont abundance and possibly on host survival. Furthermore, transmission electron microscopic observations of sulfur globules in the symbiont cells and expression analyses of the dsrA gene of the symbiont indicated that stocked elemental sulfur could be consumed as an energy source to reduce sulfide shortages. We discuss the importance of higher and more stable sulfide concentrations and the proportions of available O₂ and CO₂ in driving appropriate metabolic functions of the symbiont and improving the survival of the clams.