| The uncertainty brought by renewable energy generation will become more and more serious with the increasing proportion of renewable energy in power system.In all kinds of renewable energy generation,wind power as a kind of clean energy and its superiority,has been vigorously developed in our country.But it also brings a lot of problems,such as wind power consumption obstruction,wind power uncertainty aggravate the system operating pressure and so on.Due to the changes of the power side,the optimal scheduling of the system will gradually fall short only depending on the power side.How to tap the adjustment capacity of the demand side is an effective way to face the high proportion of renewable energy system,while the energy intensive load(such as electric arc furnace,electrolytic aluminum,etc.)has great demand side response potential due to its large demand for electricity and its adjustable operation mode,which can effectively participate in the consumption of wind power.In this paper,the participation of energy intensive load in wind power consumption is studied.The specific work contents include:(1)The power output characteristics of wind power are analyzed to clarify the feasibility of energy intensive load participating in wind power consumption.On this basis,by analyzing the operation characteristics of energy intensive load,a discrete electric arc furnace power model suitable for power grid dispatching is proposed.The model mainly considers power regulation by adjusting the position of electric arc furnace transformer tap and changing the production plan of electric arc furnace through start-stop.At the same time,constraints such as adjustment times and off-peak start and stop are added to make it conform to the actual operation condition of electric arc furnace.Comparing with the actual operation power curve of electric arc furnace in an iron and steel enterprise,the effectiveness of the proposed electric arc furnace power model is verified.According to the operation characteristics of electrolytic aluminum,a continuous electrolytic aluminum power model is established,which provides the basis for the subsequent study on the participation of energy intensive load in wind power consumption.(2)Aiming at the participation of electric arc furnace load in wind power consumption in iron and steel enterprises,the Monte Carlo method is adopted to study the interaction between wind power and electric arc furnace considering the fluctuation in the actual operation process,and the reserve capacity required by the power system to cope with the fluctuation of wind power and electric arc furnace is obtained.On this basis,The method of determining moving peak-flat and flat-valley boundary and dividing peak-flat-valley period based on net load curve is proposed to stimulate the electric arc furnace load to participate in the demand response.Through the incentive of price,the steel enterprises can arrange more production plans in the valley period,reduce production plans in the peak period or do not arrange production plans,so that the steel enterprises can reduce the cost of electricity while promoting the consumption of wind power.(3)Considering the uncertainty of wind power output and electric arc furnace load during intra-day operation of the actual power system,the system may face insufficient reserve capacity and be forced to abandon wind or cut load within intra-day.Therefore,risk cost is taken into account to measure the risk of intra-day system scheduling when the energy intensive load is involved in wind power consumption.Combining the discrete adjustment characteristics of electric arc furnace load and the continuous adjustment characteristics of electrolytic aluminum,and taking the minimum operation cost including wind abandonment and load cutting risk as the objective function,a strategy of day-ahead and intra-day consumption of wind power with energy intensive load considering the operation risk was proposed to optimize the production plan of energy intensive load,which could not only realize the system’s wind power consumption but also reduce its operation risk in the face of uncertainty. |