Non-convex dynamic economic/environmental dispatch with plug-in electric vehicle loads

Electric vehicles are a key prospect for future transportation. A large penetration of electric vehicles has the potential to reduce the global fossil fuel consumption and hence the greenhouse gas emissions and air pollution. However, the additional stochastic loads imposed by plug-in electric vehicles will possibly introduce significant changes to existing load profiles. In his paper, electric vehicles loads are integrated into an 5-unit system using a non-convex dynamic dispatch model. The actual infrastructure characteristics including valve-point effects, load balance constrains and transmission loss have been included in the model. Multiple load profiles are comparatively studied and compared in terms of economic and environmental impacts in order o identify patterns to charge properly. The study as expected shows ha off-peak charging is the best scenario with respect to using less fuels and producing less emissions.

A self-learning teaching-learning based optimization for dynamic economic/environmental dispatch considering multiple plug-in electric vehicle loads

Economic and environmental load dispatch aims to determine the amount of electricity generated from power plants to meet load demand while minimizing fossil fuel costs and air pollution emissions subject to operational and licensing requirements. These two scheduling problems are commonly formulated with non-smooth cost functions respectively considering various effects and constraints, such as the valve point effect, power balance and ramp rate limits. The expected increase in plug-in electric vehicles is likely to see a significant impact on the power system due to high charging power consumption and significant uncertainty in charging times. In this paper, multiple electric vehicle charging profiles are comparatively integrated into a 24-hour load demand in an economic and environment dispatch model. Self-learning teaching-learning based optimization (TLBO) is employed to solve the non-convex non-linear dispatch problems. Numerical results on well-known benchmark functions, as well as test systems with different scales of generation units show the significance of the new scheduling method.

Complexity and Conundrums in Pollution Control:Improving Effectiveness in Regulatory Compliance

The last century has witnessed a dramatic increase in the wealth of European nations and the well being of their inhabitants. The focus has, however, largely been upon economic growth to the detriment of people and the environment. It is only in recent years that governments have taken cognisance of the impacts of our actions and there is a growing realisation that the causal factors must be identified and addressed as a matter of urgency. One of the key problem areas is pollution and as such environmental protection has become increasingly important as a mechanism for safeguarding the quality of air, water and land. This involves a range of activities from setting standards to monitoring and reporting on discharges and emissions, through to the enforcement of legislation. In theory, this is a simple challenge, in practice, it has proven to be an extremely complex equation that might only begin to be addressed through research. In this context it is strange, and alarming, to find that while it is an axiom of good practice that policy is informed by research there has been a dearth of investigation in this field. The purpose of this paper is, therefore, to consider the issue of pollution, how it impacts on the environment, what measures have been established in pursuit of reducing the number of incidences and, most significantly, which strategies might be employed to avoid or ameliorate detrimental impacts.