Tuned Passive Harmonic Filters MarketSize and Trends

Increasing dependence on electric power source is expected to propel growth of the tuned passive harmonic filters market

According U.S. Energy Information Administration’s International Energy Outlook 2016, global industrial consumption of electrical energy as a power source is expected to grow from 31.9 quadrillion British Thermal Units (Btu) in 2012 to 40.0 Btu in 2025. Moreover, OECD countries are expected to witness an annual average change of 0.7% and non-OECD countries of 1.6% in the duration of 2012–2040. Furthermore, increasing utilization of renewable energy sources for electricity generation is among the prominent trends gaining traction, in order to reduce environmental impacts, which is expected to fuel demand for tuned passive harmonic filters over the forecast period.

Market Trends

Increasing demand for these filters to reduce harmonic distortions for enhancing supply efficiency and avoid system malfunctions is expected to drive growth of the market

Power systems have recurring distortions of current and voltage waveforms, owing to extensive usage of loads that produce currents with higher frequencies. Growing number of non-linear loads in conjunction with substantial surge in demand for electricity has led to introduction of large number of parameters that distort the voltage and can potentially cause malfunction, overheating, and breakdown of the systems utilized in power systems. Requirement to provide consistent supply and avoid potential damage to the end user and power systems is expected to lead to demand for these power factor correction systems and fuel growth of the tuned passive harmonic filters market. These equipment are featured with large sizes of MVAR ratings, maintenance free service, and are economically viable than synchronous condensers. It also offers many advantages for systems that require high starting power, voltage support, and protection in case of source. These features are expected to lead to high adoption of these systems over the forecast period.