研究目的

The produced energy from varied sources in modern power systems is to be optimally planned for planning and operating of power system under the determined limit conditions. Recently, the rising overall people population of the world, the increasing of people requirements, improvements of technology, and ecosystem and global climate changes have caused with the increasing of electric energy demand. One of the most important solution methods to meet this energy demand is considered as utilization of renewable energy sources (RESs) in power systems. The structure of power systems has become with the usage of RESs more complex. The optimal power flow (OPF) from planning and operation problems has converted to difficult problem with RESs integrated into modern power systems. This paper presents the OPF problem of power systems with a high penetration of controllable renewable sources. These kinds of sources are able to inject a determined power since they have a back-up unit (storage). Uncertain solar irradiance and wind speed are simulated via log-normal and Rayleigh probability distributions, respectively. The proposed OPF problem with controllable renewable sources is solved by the differential evolutionary particle swarm optimization (DEEPSO) algorithm.

研究成果

As one of the most important problems in modern power networks, OPF problem has become a hot research topic. This paper represents the lately proposed OPF problem of power systems with controllable wind power and photovoltaic system. The proposed OPF problem is tested on modified IEEE 30-bus, 57-bus, and 118-bus test systems with RESs via different simulation cases to show its feasibility. In addition, the cost function models of thermal generators are considered with quadratic curves, valve-point effect, and prohibited operating zones in this study. The obtained numerical results from DEEPSO algorithm are compared with those of MSA, BSA, and DS optimization algorithms. To show resolvableness the proposed OPF problem with controllable wind power and photovoltaic system, the comparison shows that the DEEPSO approach has a best fitness value and a better convergence performance to optimal solutions than MSA, BSA, and DS approaches. In addition, the optimized control variables by using DEEPSO algorithm for the study cases are within the lower and upper limits values. To verify the superiority, robustness, and effectiveness of DEEPSO algorithm, Wilcoxon signed-rank test is applied for all the test cases. Future work could include further investigating other forms of the OPF problem, including the multiobjective OPF problem with RESs, dynamic OPF problem with RESs, and OPF problem with RESs in high-voltage direct current systems.

研究不足

The technical and application constraints of the experiments, as well as potential areas for optimization, include the complexity of integrating renewable energy sources into modern power systems and the challenges in solving the OPF problem with these sources.