Stochastic optimization for price-based unit commitment in renewable energy-based personal rapid transit systems in sustainable smart cities

Power resources scheduling and planning have a great impact on today's sustainable cities. The conventional power plants as well as renewable energy resources should be committed to considering social, technical, economic, and environmental sustainability optimally. On the other hand, transportation electrification is one of the key pillars of today's smart cities. In this paper, the generation capacity is scheduled to meet system's loadability using a new personal rapid transit system, which is carried out utilizing a price-based unit commitment (PBUC) that maximizes profit based on price signals in the context of a stochastic optimization scheme. The personal rapid transit system at the University of West Virginia is considered as a case study based on several prescribed planning scenarios. Wind power energy, as one of the popular renewable energy sources, is considered for power generation. The integrated simulation and optimization results confirm the effectiveness and robustness of the proposed PBUC methodology.