考虑风电和电动汽车等不确定性负荷的电力系统节能减排调度

Energy-saving Emission-reduction Dispatching of Electrical Power System Considering Uncertainty of Load with Wind Power and Plug-in Hybrid Electric Vehicles

可入网电动汽车(plug-in hybrid electric vehicles,PHEVs)和风电等可再生能源发电的快速发展为电力系统的安全和经济运行带来了新挑战。为此,综合考虑了负荷和风电的不确定性、可入网电动汽车的智能充放电控制以及PHEVs与风电的协调互补和系统的节能减排,构建了计及碳排放的调度模型。先采用多场景模拟技术将风电和负荷不确定性的随机过程分解为若干典型的离散概率场景;再采用多代理技术将24 h对应为24个工作代理,工作代理负责火电、风电和PHEVs之间的静态调度;协同代理负责工作代理之间的动态协调。最后对含10机火电机组、PHEVs和风电的系统进行仿真。结果表明,多场景模拟能减少调度求解难度;含风电和PHEVs的系统能有效协调风电和PHEVs,减少其运行成本和碳排放量;通过调节节能与减排需求对应的权重,可以实现节能和减排之间的有效折衷。

The rapid development of plug-in hybrid electric vehicles （PHEVs） and wind power brings new challenges to power system security and economic operation. To this end, taking the factors into consideration such as the uncertainty of wind farms and load, smart charging and discharging of PHEVs, the coordination of wind generator and PHEVs, and the energy saving emission reduction, we established an energy-saving and emission reduction model relating to the carbon emission. Firstly, we divided the uncertain random process of wind power and load into several discrete probability scenarios using the multi-scenario simulation. Then, we divided a day into 24 work agents using the multi-agent technol- ogy, and each work agent takes charge of the static scheduling among wind, PHEVs and thermal units, while the cooperative agent takes charge of the dynamic harmony among each work agent. Finally, we simulated the system that contained 10 thermal units, a wind farm, and PHEVs. The results show that, the multi-scenario simulation can reduce the computational complexity. The system can coordinate the wind and PHEVs effectively, and greatly cut the operation cost and carbon emission. The tradeoffbetween the weight of cost and emission can be achieved by adjust the weight of cost and emission.