Distributed resource scheduling in smart grid with electric vehicle deployment using fireworks algorithm

Global warming and climate change are two key probing issues in the present context.The electricity sector and transportation sector are two principle entities propelling both these issues.Emissions from these two sectors can be offset by switching to greener ways of transportation through the electric vehicle (EV) and renewable energy technologies (RET).Thus,effective scheduling of both resources holds the key to sustainable practice.This paper presents a scheduling scenario-based approach in the smart grid.Problem formulation with dual objective function including both emissions and cost is developed for conventional unit commitment with EV and RET deployment.In this work,the scheduling and commitment problem is solved using the fireworks algorithm which mimics explosion of fireworks in the sky to define search space and the distance between associated sparks to evaluate global minimum.Further,binary coded fireworks algorithm is developed for the proposed scheduling problem in the smart grid.Thereafter,possible scenarios inconventional as well as smart grid are put forward.Following that,the proposed methodology is simulated using a test system with thermal generators.

A Multiple Emission Constrained Approach for Self-scheduling of GENCO Under Renewable Energy Penetration

The electric sector contributes substantially to both greenhouse gas(GHG)and non-greenhouse gas(NGHG)emissions,which means that both conventional and thermal generation companies(GENCOs)must follow certain environmental guidelines to address various emission requirements.This paper presents a methodology to investigate the feasibility of both GHG and NGHG emission reduction in a deregulated electricity market.The proposed model takes into consideration the effect of NGHG emission cost constraints in conjunction with classical GHG emission constraints for the scheduling aspects of GENCO.A profit based self-scheduling problem with conventional fossil fueled generators and renewable energy technologies(RETs)is formulated including emission penalties and avoidance costs of GHG and NGHG emissions,respectively.Thereafter,a set of pareto solutions is evaluated for different possible scheduling scenarios.A simple,effective optimality criteria is also postulated to identify the tradeoff solution.Finally,a sensitivity analysis of various technical,environmental,as well as economic aspects is presented to examine the effect of NGHG consideration and RET inclusion in scheduling.The simulation results are presented and discussed in detail to examine the effect of NGHG consideration in self-scheduling practices of GENCO in the electricity market,thus reflecting the benefits of the proposed approach over classical emission handling approaches.