We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Technical, economic, and environmental assessment of a stand-alone power system based on diesel engine with/without energy storage using an optimization algorithm: A case study in China.
- Authors
Chen, Yujie; Zhang, Shuo
- Abstract
In stand-alone power systems, technical, economic, and environmental (TEE) assessment of hybrid energy systems under uncertainty is an important issue. This paper focuses on the TEE assessment of a stand-alone hybrid energy system composed of photovoltaic (PV) and diesel generator (DG) with/without battery energy storage (BS) in remote islands in China. So, determining the optimal sizes of PV and DG with/without BS for economic, reliable, and efficient operation of a hybrid power system in a microgrid is important. For this goal, a modified swarm intelligence algorithm is used to optimize, techno-economic feasibility and avoid potential CO2 emission. To demonstrate the effectiveness of the modified swarm intelligence algorithm, it is compared with the standard swarm intelligence method and simple simulated annealing method in terms of operational cost reduction and power loss reduction. The aim of the optimization is to minimize the cost of a stand-alone solar power system based on diesel engine with/without battery energy storage system by optimal determination of the load uncertainty and CO2 emission. The optimal results are developed further by performing sensitivity analysis, such as the effect of the fuel cost and the penalty cost of CO2 emission. Over the case study, simulation results show that the proposed algorithm obtains more promising results in terms of TEE aspects. The reliability, low carbon, and cost-effectiveness of stand-alone solar power systems based on diesel engine with battery energy storage system can be easily calculated using the correlations derived in this analysis. The resulting cost of energy is in the range of 0.2845 to 0.6492 $/kWh.
- Subjects
CHINA; OPTIMIZATION algorithms; BATTERY storage plants; DIESEL motors; HYBRID power systems; ENERGY storage; ENERGY consumption; PHOTOVOLTAIC power systems
- Publication
Environmental Science & Pollution Research, 2024, Vol 31, Issue 27, p38585
- ISSN
0944-1344
- Publication type
Article
- DOI
10.1007/s11356-023-31488-3