Optimal generation scheduling of co-located floating solar photovoltaic-wind-hydro with virtual energy banking services | |
| Author | Vatee Laoharojanaphand |
| Call Number | AIT Diss no.ET-22-01 |
| Subject(s) | Renewable energy sources Wind turbines Photovoltaic power generation Renewable energy sources Wind turbines Photovoltaic power generation |
| Note | A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Engineering in Energy |
| Publisher | Asian Institute of Technology |
| Abstract | Renewable energy sources (RESs) such as wind turbines (WT) and solar photovoltaic (PV) provide clean energy without emission but are volatile due to their intermittent sources of energy. The volatility of power output can cause a frequency fluctuation in power systems especially when a large-scale PV or wind power plant is installed in a system. The hydro power plant (HPP), also considered a renewable energy source, can play important role in maintaining power system stability because of its flexibility, fast startup time, high ramp rate, and large amount of storage. However, the disadvantages are the limitation of water inflow and water release. Moreover, the growth of the population, the limitation of land use, and the environmental concern make the construction of new hydro power plants can be very difficult due to the requirement of a large area. Thus, combining the existing hydro power plants with the PV plant or WT can be an effective solution. The hydro power plant can accommodate the fluctuation of power output from PV or WT. On the other hand, PV and WT can help hydro power plants in reducing of water amount to be used to produce electricity. Hence, combining the advantages of PV, WT, and HPP makes renewable energy production more reliable and more efficient water resource utilization. This dissertation proposes the optimal generation scheduling of the co-located floating PV(FPV)-WT-HPP generation in a large-scale power system. The concept is to perform the generation scheduling of the HPP to accommodate the fluctuation of WT and PV generation. The objective function is the total generation cost minimization and is subjected to power balance, reserve generation, reservoir constraint, and generating unit operating constraints. The enhanced adaptive Lagrange Relaxation (ELR) which improved the initialization and adaptive adjustment of Lagrange multipliers in the standard Lagrangian Relaxation (LR) method, is adopted for the unit commitment problem-solving part of this thesis. The next part of this dissertation proposes the optimal generation scheduling of HPP with co-located FPV-WT generation employing the Stochastic Weight Trade-off Chaotic Particle Swarm Optimization (SWTC-PSO). The intermittency of FPV and WT generation, for short term generation scheduling, is compensated by HPP. The combined HPP with WT and FPV becomes a dispatchable generation. The objective is to either maximize the dam water level or minimize the amount of water spillage subject to power balance, thermal generator, and hydro operating constraints without having to select the objective function according to the season. All of the HPPs’ power generation is optimized for maximum upper reservoir water or minimum spill water. Then, the virtual battery service using the above-mentioned co-located FPV-WT-HPP power plant concept is proposed. Virtual Battery (VB) is the operating concept in which the grid operator permits the prosumer to export surplus PV generation and store it in the system. Then, the prosumer is entitled to draw back the same amount of energy from the system, paying the storage fee. Rather than a physical battery, the utility can use a co-located power plant (CLPP) consists out of HPP, floating solar PV (FPV), and neighboring wind turbines, to store the prosumers’ energy, charging a low premium. In addition to conventional generation, the CLPP can provide virtual battery service for extra revenue since the PV, WT, and HPP can complement each other in many ways. The CLPP’s profit when delivering the VB service is maximized in this scenario. Finally, the techno-economic analysis of the CLPP with Virtual Energy Banking services (VEBS) is conducted. Virtual Energy Banking services is a concept in which the CLPP acts like a bank and allows its customer to withdraw, deposit, or loan energy. The withdraw, and loan transaction is met by the increasing generation of HPP. On the other hand, the deposit transaction is achieved by reducing the HPP generation. In this section, the objective is to find the FPV and WT installed capacity which maximizes the Net Present Value of the 25- year co-located FPV-WT-HPP project. The optimization problem is resolved with Stochastic Weight Trade-off Chaotic Enhanced Leader Particle Swarm Optimization (SWTC-ELPSO), a novel optimization technique that combines the strength of the personal best particle search capability from SWTC-PSO with the 5-stage mutation of global best particle from Enhanced Leader Particle Swarm Optimization (ELPSO). The SWTC-ELPSO provides a better result in terms of higher NPV value and lower standard deviation compared with other optimization techniques. |
| Year | 2022 |
| Type | Dissertation |
| School | School of Environment, Resources, and Development |
| Department | Department of Energy and Climate Change (Former title: Department of Energy, Environment, and Climate Change (DEECC)) |
| Academic Program/FoS | Energy (ET, Start from 2022) |
| Chairperson(s) | Weerakorn Ongsakul; |
| Examination Committee(s) | Singh, Jai Govind;Badir, Yuosre F. M.;Pinkayan, Subin; |
| Scholarship Donor(s) | Asian Institute of Technology Fellowship;Royal Thai Government; |
| Degree | Thesis (Ph.D.) - Asian Institute of Technology, 2022 |