Liwei Ju

Multiobjective Synergistic Scheduling Optimization Model for Wind Power and Plug-In Hybrid Electric Vehicles under Different Grid-Connected Modes

In order to promote grid’s wind power absorptive capacity and to overcome the adverse impacts of wind power on the stable operation of power system, this paper establishes benefit contrastive analysis models of wind power and plug-in hybrid electric vehicles (PHEVs) under the optimization goal of minimum coal consumption and pollutant emission considering multigrid connected modes. Then, a two-step adaptive solving algorithm is put forward to get the optimal system operation scheme with the highest membership degree based on the improved constraints method and fuzzy decision theory. Thirdly, the IEEE36 nodes 10-unit system is used as the simulation system. Finally, the sensitive analysis for PHEV’s grid connected number is made. The result shows the proposed algorithm is feasible and effective to solve the model. PHEV’s grid connection could achieve load shifting effect and promote wind power grid connection. Especially, the optimization goals reach the optimum in fully optimal charging mode. As PHEV’s number increases, both abandoned wind and thermal power generation cost would decrease and the peak and valley difference of load curve would gradually be reduced.

A Multiobjective Robust Scheduling Optimization Mode for Multienergy Hybrid System Integrated by Wind Power, Solar Photovoltaic Power, and Pumped Storage Power

Wind power plant (WPP), photovoltaic generators (PV), cell-gas turbine (CGT), and pumped storage power station (PHSP) are integrated into multienergy hybrid system (MEHS). Firstly, this paper presents MEHS structure and constructs a scheduling model with the objective functions of maximum economic benefit and minimum power output fluctuation. Secondly, in order to relieve the uncertainty influence of WPP and PV on system, robust stochastic theory is introduced to describe uncertainty and propose a multiobjective stochastic scheduling optimization mode by transforming constraint conditions with uncertain variables. Finally, a 9.6 MW WPP, a 6.5 MW PV, three CGT units, and an upper reservoir with 10 MW·h equivalent capacity are chosen as simulation system. The results show MEHS system can achieve the best operation result by using the multienergy hybrid generation characteristic. PHSP could shave peak and fill valley of load curve by optimizing pumping storage and inflowing generating behaviors based on the load supply and demand status and the available power of WPP and PV. Robust coefficients can relieve the uncertainty of WPP and PV and provide flexible scheduling decision tools for decision-makers with different risk attitudes by setting different robust coefficients, which could maximize economic benefits and minimize operation risks at the same time.

Selection Ideal Coal Suppliers of Thermal Power Plants Using the Matter-Element Extension Model with Integrated Empowerment Method for Sustainability

In order to reduce thermal power generation cost and improve its market competitiveness, considering fuel quality, cost, creditworthiness, and sustainable development capacity factors, this paper established the evaluation system for coal supplier selection of thermal power and put forward the coal supplier selection strategies for thermal power based on integrated empowering and ideal matter-element extension models. On the one hand, the integrated empowering model can overcome the limitations of subjective and objective methods to determine weights, better balance subjective, and objective information. On the other hand, since the evaluation results of the traditional element extension model may fall into the same class and only get part of the order results, in order to overcome this shortcoming, the idealistic matter-element extension model is constructed. It selects the ideal positive and negative matter-elements classical field and uses the closeness degree to replace traditional maximum degree of membership criterion and calculates the positive or negative distance between the matter-element to be evaluated and the ideal matter-element; then it can get the full order results of the evaluation schemes. Simulated and compared with the TOPSIS method, Romania selection method, and PROMETHEE method, numerical example results show that the method put forward by this paper is effective and reliable.

Multiobjective CVaR Optimization Model and Solving Method for Hydrothermal System Considering Uncertain Load Demand

In order to solve the influence of load uncertainty on hydrothermal power system operation and achieve the optimal objectives of system power generation consumption, pollutant emissions, and first-stage hydropower station storage capacity, this paper introduced CVaR method and built a multiobjective optimization model and its solving method. In the optimization model, load demand’s actual values and deviation values are regarded as random variables, scheduling objective is redefined to meet confidence level requirement and system operation constraints and loss function constraints are taken into consideration. To solve the proposed model, this paper linearized nonlinear constraints, applied fuzzy satisfaction, fuzzy entropy, and weighted multiobjective function theories to build a fuzzy entropy multiobjective CVaR model. The model is a mixed integer linear programming problem. Then, six thermal power plants and three cascade hydropower stations are taken as the hydrothermal system for numerical simulation. The results verified that multiobjective CVaR method is applicable to solve hydrothermal scheduling problems. It can better reflect risk level of the scheduling result. The fuzzy entropy satisfaction degree solving algorithm can simplify solving difficulty and get the optimum operation scheduling scheme.

An Optimization Scheduling Model for Wind Power and Thermal Power with Energy Storage System considering Carbon Emission Trading

Wind power has the characteristics of randomness and intermittence, which influences power system safety and stable operation. To alleviate the effect of wind power grid connection and improve power system’s wind power consumptive capability, this paper took emission trading and energy storage system into consideration and built an optimization model for thermal-wind power system and energy storage systems collaborative scheduling. A simulation based on 10 thermal units and wind farms with 2800 MW installed capacity verified the correctness of the models put forward by this paper. According to the simulation results, the introduction of carbon emission trading can improve wind power consumptive capability and cut down the average coal consumption per unit of power. The introduction of energy storage system can smooth wind power output curve and suppress power fluctuations. The optimization effects achieve the best when both of carbon emission trading and energy storage system work at the same time.

The Optimization Model for Electric System Emergency Facility Storage and Transportation Considering Information Credibility

When dealing with power system emergency caused by natural disaster, information survey is the important foundation of emergency power supply and repair. The information credibility would directly inflect the credibility and timeliness of electric system emergency work. Therefore, this paper starts the study from the point of information credibility and sets minimizing total cost and loss as the objective function, taking time constraint, transportation road constraint, information credibility constraint, and the parameters of different facilities into consideration and building a location and storage optimization model for electric system emergency facility. And a corresponding facility transportation model was built considering the power loss in demand points. The simulation result shows that the models proposed by this paper could satisfy the requirement of information credibility, improve the adaptability to demand change, and cut down total cost and loss.

The Optimization Model for Interregional Power System Planning considering Carbon Emissions Trading and Renewable Energy Quota Mechanism

In China, the rapid construction of ultra-high-voltage (UHV) transmission lines promotes interregional resource optimizing configuration and interregional power system planning. This paper analyzes external environment of interregional power system planning from geographical, technical, and policy environments. Then, the paper takes the minimum system investment cost as the optimization objective and constructs the optimization model of interregional power system planning considering carbon emissions trading (CET) and renewable energy quota mechanism (REQ). Finally, this paper sets base scenario, carbon emissions trading scenario, renewable energy quota mechanism scenario, and comprehensive scenario for case simulation. The results show that interregional power system planning could connect power grids in different regions, enlarge wind power consumption space, and relieve the inconformity problem between power resource and load demand. CET and REQ can increase the installed proportion of clean energy and reduce carbon dioxide emissions, but the cost of transmission lines construction and system reserve will increase correspondingly. The optimization effect of REQ on power system planning is better than CET. When they are both introduced, the power structure will reach the best, carbon dioxide emissions will achieve the minimum, and comprehensive benefits will become more balanced.

Optimization Model of Multitype Generating Units Based on the Latin Hypercube Sampling Method and Mean Lower Semiabsolute Deviation Theory

The scheduling optimization of multiple-type generators is of great significance for the economic operation of the power system and the target achievement of energy-saving emission reduction. This chapter builds a two-stage fire and water turbine scheduling the optimization model based on the power performance. Firstly, this chapter simulated the output scenarios of wind power based on the Latin hypercube sampling (LHS) method; then, we minimized the wind curtailment as the main objective, selected the minimization of the system generating energy costs and the generating pollutant emissions as objective functions for cogeneration performance scheduling, and constructed multiple types of generators scheduling the optimization model. The optimization model can guarantee the timely adjustment and output stability for thermal power units in different scenarios, and thus promote the wind power integration.