Study on the Optimal Operation of a Hydropower Plant Group Based on the Stochastic Dynamic Programming with Consideration for Runoff Uncertainty

Hydropower plant operation reorganizes the temporal and spatial distribution of water resources to promote the comprehensive utilization of water resources in the basin. However, a lot of uncertainties were brought to light concerning cascade hydropower plant operation with the introduction of the stochastic process of incoming runoff. Therefore, it is of guiding significance for the practice operation to investigate the stochastic operation of cascade hydropower plants while considering runoff uncertainty. The runoff simulation model was constructed by taking the cascade hydropower plants in the lower reaches of the Lancang River as the research object, and combining their data with the copula joint function and Gibbs method, and a Markov chain was adopted to construct the transfer matrix of runoff between adjacent months. With consideration for the uncertainty of inflow runoff, the stochastic optimal operation model of cascade hydropower plants was constructed and solved by the SDP algorithm. The results showed that 71.12% of the simulated monthly inflow of 5000 groups in the Nuozhadu hydropower plant drop into the reasonable range. Due to the insufficiency of measured runoff, there were too many 0 values in the derived transfer probability, but after the simulated runoff series were introduced, the results significantly improved. Taking the transfer probability matrix of simulated runoff as the input of the stochastic optimal operation model of the cascade hydropower plants, the operation diagram containing the future-period incoming water information was obtained, which could directly provide a reference for the optimal operation of the Nuozhadu hydropower plant. In addition, taking the incoming runoff process in a normal year as the standard, the annual mean power generation based on stochastic dynamic programming was similar to that based on dynamic programming (respectively 305.97 × 108kW⋅h and 306.91 × 108kW⋅h), which proved that the operation diagram constructed in this study was reasonable.

Research on the Operation Model and Strategy of Lithium Battery to Provide Frequency Regulation in the Power System

With the development of smart grid and energy internet, energy storage will play an important role in maintaining the power balance and providing frequency regulation in future power system. Consequently, energy storage faces a trade-off problem between the energy market and frequency regulation market. In this work, an operation model and strategy of energy storage to provide frequency regulation is proposed. Taking lithium battery as an example of energy storage, its technical feasibility to provide frequency regulation is firstly discussed. Then, a day-ahead energy market model in the power system is constructed to calculate the revenue of lithium battery. Finally, the operation strategy of lithium battery to provide secondary frequency regulation (namely AGC) is proposed based on the model of opportunity cost. Case study is conducted on a modified IEEE 6-bus system. It shows that the reduced marginal revenue of lithium battery in the energy market increases with the growth of its declared capacity for frequency regulation. Consequently, the optimal declared frequency regulation capacity for lithium battery is the amount, at which the reduced marginal revenue in the energy market is equal to the compensation price of frequency regulation.

Optimal Operation Model of Park Integrated Energy System Considering Uncertainty of Flexible Electrical, Thermal and Gas Load

Flexible Load (FL) of electricity, heat and gas can improve the operation economy, flexibility and reliability of PIES. Aiming at the uncertainty of FL in the actual operation of the park integrated energy system (PIES), an optimal operation model of PIES with uncertainty of FL is proposed. Firstly, the uncertainty models of shiftable electric load and transferable load response are established, respectively. And then an adjustable heat load response model considering the uncertainty of solar radiation intensity is established. On this basis, an optimal operation model of PIES considering the uncertainty of the FL with the goal of maximizing the total revenue is constructed and is solved by the enhanced-interval linear programming method. Simulation indicate that FL can improve the operating economy of PIES and renewable energy consumption.