Quantum computing promises to provide significant speedup over classical computing in several important problem domains, which has garnered the attention of many researchers. Yet, developing and executing algorithms on quantum hardware pose economic challenges, especially for individuals and small research groups. Quantum simulators can bridge this gap by enabling researchers to use readily available classical hardware to perform quantum experiments. However, publicly available simulators are often time-shared through cloud-based high performance computing (HPC) environments and are not customizable to the particular needs of the developer. Moreover, local simulators running on consumer-grade CPUs, suffer from prolonged execution times. Therefore, the acceleration and customization of quantum simulations using local and dedicated hardware accelerators such as FPGAs can provide a better developer experience, faster design iteration, and potentially a cost-effective solution for quantum computing research and prototyping. In this paper, we evaluate using cost-effective, commercial-off-the-shelf FPGA boards for quantum application development on standard and full-featured quantum simulation frameworks such as IBM-Qiskit. More specifically, we provide a trade-off study of using FPGAs for such quantum simulation frameworks with respect to performance, resource, and cost requirements. In our experiments, we use commercially available FPGA boards such as the PYNQ-ZU, KV260, and RFSoC 4x2 for simulating resource and compute-intensive multidimensional quantum convolution as a case study. We leverage the performance-cost-ratio (PCR) metric to compare these boards against a server-grade CPU and show that cost-effective reconfigurable hardware can be a practical, accessible, and affordable option for quantum computing research.