Low carbon design strategies for landscape architecture based on renewable energy technologies

Abstract

ABSTRACT With the continuous accumulation of the greenhouse effffect, the global climate warming situation is becoming more and more serious, and the energy consumption, including landscape architecture, is increasing, and gradually becoming the main source of greenhouse gas emissions. Therefore, it is very necessary to optimize the scheduling of the energy system of landscape architecture. On the basis of renewable energy technology, the research improves the non-dominated sequencing genetic algorithm, and combines it with the depth deterministic strategy gradient algorithm to jointly apply it to the energy system scheduling of landscape architecture. The experimental results show that the combined algorithm increases signifificantly after the average reward of 2000, with the highest of −250; After the number of 60 × 40 rounds, the combined algorithm reward value is stable at −0.5 × 106 ; In the energy system scheduling of landscape buildings, the wind and photovoltaic capacity it controls can carry more than 200MW of electrical load during peak electrical load periods, improving the utilization rate of renewable energy, and the highest value in the one-week carbon emission experiment is below 700,000 tonnes, far lower than other algorithms, effffectively reducing carbon emissions.