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Uncertainty of the wind power output is the main influence factor for wind power utilization in the bulk power system. Because of the large capacity and the load characteristic, energy-intensive load holds great potentials to share the burden of wind power fluctuation smoothing. In this paper, a direct control scheme of the energy-intensive load power is proposed to smooth the wind power fluctuation. Based on the characteristic of the energy-intensive load production technology, the feasibility of energy-intensive load control and its influence on the production are discussed. A feedback control is designed to regulate the saturable reactor and transformer tap changer when the power support from the bulk power system is limited. Regulation capacity is analyzed quantitatively based on the energy-intensive load equivalent circuit model. A grid-connected energy-intensive enterprise driven by self-generation wind power plants and thermal power plants is studied as an example case. By the proposed energy-intensive load control scheme, power fluctuation of the wind farms can be smoothed with the minimum control cost. Besides, the regulation requirement of the bulk power system is eased correspondingly so that the utilization capacity of the power system can be improved significantly. Simulation is done on the real-time digital simulator to verify the effectiveness of the proposed control method. [ABSTRACT FROM AUTHOR]

Optimisation of reserve purchased in advance becomes increasingly essential to hedge against the growing level of power unbalance brought by the integration of large‐scale wind power. Moreover, due to the centralised integration mode of wind farms, cross‐region reserve sharing strategy becomes quite imperative. Therefore, this study presents a dynamic reserve demand estimation (DRDE) model, which synthetically considers N − 1 contingency along with load and wind forecast error. In the proposed approach, historical data is rearranged by a two‐dimensional binning technique and fitted by the versatile probability distribution model, which assisting the model reacts to different prediction level in each dispatch period dynamically. Furthermore, a cost‐effectivity oriented reserve allocation strategy for the multi‐area system is developed based on the DRDE model. The efficiency of the proposed method is tested in both 6‐bus test system and IEEE 118‐bus test system. The results show that, whether in the scenario of self‐sufficient reserve supplying or cross‐region reserve sharing strategy, the proposed estimation model effectively reduces the expectation of both load shedding and wind curtailment. Moreover, the proposed strategy improves the economy of system operation on the premise of ensuring system reliability. [ABSTRACT FROM AUTHOR]

As the installed capacity of wind power is growing, the stochastic variability of wind power leads to the mismatch of demand and generated power. Employing the regulating capability of demand to improve the utilization of wind power has become a new research direction. Meanwhile, the micro combined heat and power (micro-CHP) allows residential consumers to choose whether generating electricity by themselves or purchasing from the utility company, which forms a residential hybrid energy system. However, the impact of the demand response with hybrid energy system contained micro-CHP on the large-scale wind power utilization has not been analyzed quantitatively. This paper proposes an operation optimization model of the residential hybrid energy system based on price response, integrating micro-CHP and smart appliances intelligently. Moreover, a novel load aggregation method is adopted to centralize scattered response capability of residential load. At the power grid level, a day-ahead stochastic economic dispatch model considering demand response and wind power is constructed. Furthermore, simulation is conducted respectively on the modified 6-bus system and IEEE 118-bus system. The results show that with the method proposed, the wind power curtailment of the system decreases by 78% in 6-bus system. In the meantime, the energy costs of residential consumers and the operating costs of the power system reduced by 10.7% and 11.7% in 118-bus system, respectively. [ABSTRACT FROM AUTHOR]