Multi-objective Comprehensive Optimum Study of Computer-Controlled Truck Dispatching

According to the demand of modern surface mine production, production, a multi-objective optimum dispatchingmodel is set up in this paper, it includes overall comprehensive optimal model, the goal programming model to optimize truck fleet in mine haulage system, and the selection of real time dispatching criteria. A surface coal mineis studied as a case in a built system simulation mantel, and the simulation result shows that the model is correct.

Study on Risk Dispatch Model of Hydropower Station in the Market Environment

In the power market environment, due to the uncertainty of the reservoir inflow and the pool purchase price, it is very important to research power generation risk dispatch of hydropower plants, taking into consideration the benefits and risk control of both sides. This paper investigates power generation risk dispatch of hydropower plants in the market environment, and proposes a mathematical model which considers maximization of benefits and risk control, reflects control willingness of risk and benefits, resolves it with the PSO algorithm, finding more economic and reasonable results. The feasibility and validity of the model and resolving methods are verified by an example.

Optimal Active Power Dispatching of Microgrid and Distribution Network Based on Model Predictive Control

First, a three-tier coordinated scheduling system consisting of a distribution network dispatch layer, a microgrid centralized control layer, and local control layer in the energy internet is proposed. The multi-time scale optimal scheduling of the microgrid based on Model Predictive Control（MPC） is then studied, and the optimized genetic algorithm and the microgrid multi-time rolling optimization strategy are used to optimize the datahead scheduling phase and the intra-day optimization phase. Next, based on the three-tier coordinated scheduling architecture, the operation loss model of the distribution network is solved using the improved branch current forward-generation method and the genetic algorithm. The optimal scheduling of the distribution network layer is then completed. Finally, the simulation examples are used to compare and verify the validity of the method.

Uncertain Dispatching Decision and Genetic Algorithms for Railyards Operations

In this paper, a fuzzy dispatching model has been developed and genetic algorithms have been used for considering the corrdination among uncertain decisions in railyards dispatching plan. The objective considered here is to maximize the average grade of satisfaction including the yards output and ontime service of the plan. Based on the analysis of the fuzzy scheduled model for the problem, the chromosome and fitness function of genetic algorithms are proposed. The genetic operators are designed and the genetic algorithms are given. Experimental results show that the genetic algorithms and fuzziness approach could be a promising way for railyards dispatching problem.

Resilience-oriented Valuation for Energy Storage Amidst Extreme Events

In power grids,the frequency is increasing of extreme accidents which have a low probability but high risk such as natural disasters and deliberate attacks.This has sparked discussions on the resilience of power grids.Energy-storage systems(ESSs)are critical for enhancing the resilience of power grids.ESSs,with their mechanism of flexible charging and discharging,adjust energy usage as needed during disasters,thereby mitigating the impact on the grid and enhancing security and resilience.This,in turn,ensures the power system’s stable operation.Currently,there is limited systematic research quantifying the economic value of energy storage in resilience scenarios.Therefore,a model and methodology were proposed to quantify the value of energy storage systems for enhancing grid resilience during extreme events.A two-stage stochastic optimization mathematical model was developed.The first stage involves pre-deployment based on day-ahead expectations,and the second stage involves simulating potential failure scenarios through real-time scheduling.Considering the temporal dimension,the energy storage systems with flexible regulation capabilities was used as emergency power sources to reduce occurrences of load-shedding.Here,a novel index was proposed that quantifies the resilience value of energy storage as the economic value of energy storage per unit of capacity,as reflected in the emergency dispatch model.This index helps determine the balance between the energy storage investment cost and resilience value.Finally,an IEEE-30 node transmission system was used to verify the feasibility and effectiveness of the proposed method.The findings revealed a significant improvement in the resilience value,with a 23.49%increase observed when energy storage systems were implemented compared to the scenario without energy storage systems.The optimal capacity configurations for the flywheel,lithium-ion batteries,and pumped hydro storage were 10 MW,11 MW,and 12 MW,respectively,highlight their potential to maximize value in experimental system.