An Analytical Method for Delineating Feasible Region for PV Integration Capacities in Net-zero Distribution Systems Considering Battery Energy Storage System Flexibility

To provide guidance for photovoltaic(PV)system integration in net-zero distribution systems(DSs),this paper proposes an analytical method for delineating the feasible region for PV integration capacities(PVICs),where the impact of battery energy storage system(BESS)flexibility is considered.First,we introduce distributionally robust chance constraints on network security and energy/carbon net-zero requirements,which form the upper and lower bounds of the feasible region.Then,the formulation and solution of the feasible region is proposed.The resulting analytical expression is a set of linear inequalities,illustrating that the feasible region is a polyhedron in a high-dimensional space.A procedure is designed to verify and adjust the feasible region,ensuring that it satisfies network loss constraints under alternating current(AC)power flow.Case studies on the 4-bus system,the IEEE 33-bus system,and the IEEE 123-bus system verify the effectiveness of the proposed method.It is demonstrated that the proposed method fully captures the spatio-temporal coupling relationship among PVs,loads,and BESSs,while also quantifying the impact of this relationship on the boundaries of the feasible region.

A Multi-objective Chance-constrained Information-gap Decision Model for Active Management to Accommodate Multiple Uncertainties in Distribution Networks

The load demand and distributed generation(DG)integration capacity in distribution networks(DNs)increase constantly,and it means that the violation of security constraints may occur in the future.This can be further worsened by short-term power fluctuations.In this paper,a scheduling method based on a multi-objective chance-constrained information-gap decision(IGD)model is proposed to obtain the active management schemes for distribution system operators(DSOs)to address these problems.The maximum robust adaptability of multiple uncertainties,including the deviations of growth prediction and their relevant power fluctuations,can be obtained based on the limited budget of active management.The systematic solution of the proposed model is developed.The max term constraint in the IGD model is converted into a group of normal constraints corresponding to extreme points of the max term.Considering the stochastic characteristics and correlations of power fluctuations,the original model is equivalently reformulated by using the properties of multivariate Gaussian distribution.The effectiveness of the proposed model is verified by a modified IEEE 33-bus distribution network.The simulation result delineates a robust accommodation space to represent the adaptability of multiple uncertainties,which corresponds to an optional active management strategy set for future selection.

An optimization strategy of controlled electric vehicle charging considering demand side response and regional wind and photovoltaic

Renewable energy,such as wind and photovoltaic(PV),produces intermittent and variable power output.When superimposed on the load curve,it transforms the load curve into a‘load belt’,i.e.a range.Furthermore,the large scale development of electric vehicle(EV)will also have a significant impact on power grid in general and load characteristics in particular.This paper aims to develop a controlled EV charging strategy to optimize the peak-valley difference of the grid when considering the regional wind and PV power outputs.The probabilistic model of wind and PV power outputs is developed.Based on the probabilistic model,the method of assessing the peak-valley difference of the stochastic load curve is put forward,and a two-stage peak-valley price model is built for controlled EV charging.On this basis,an optimization model is built,in which genetic algorithms are used to determine the start and end time of the valley price,as well as the peak-valley price.Finally,the effectiveness and rationality of the method are proved by the calculation result of the example.

Substation planning method in an active distribution network under low-carbon economy

A substation planning method that accounts for the widespread introduction of distributed generators(DGs)in a low-carbon economy is proposed.With the proliferation of DGs,the capacity that DGs contribute to the distribution network has become increasingly important.The capacity of a DG is expressed as a capacity credit(CC)that can be evaluated according to the principle that the reliability index is unchanged before and after the introduction of the DG.A method that employs a weighted Voronoi diagram is proposed for substation planning considering CC.A low-carbon evaluation objective function is added to the substation planning model to evaluate the contribution of DGs to a low-carbon economy.A case study is analyzed to demonstrate the practicality of the proposed method.

Low-carbon benefit analysis on DG penetration distribution system

In response to the severe energy and environmental issues,CO_(2)emission reduction and low-carbon development are inevitable.China has become the biggest CO_(2)emitter in the world since 2006.As a major CO_(2)emission source in China,the power industry is facing greater pressure for carbon emission abatement.By applying various low-carbon power technologies and mechanisms,the potential for CO_(2)emission reduction in power systems is considerable.This paper proposes a pseudo-sequential Monte Carlo simulation method for the low-carbon benefit evaluation of distribution system including distributed wind turbines,solar array and battery energy storage systems.The hourly sequential models and state variation models for wind turbines,solar array and battery are established.The non-power components are sequentially sampled and the components of the wind turbine,the solar array and the battery are non-sequentially sampled.The failure modes and effect analysis(FMEA)procedure for the system are discussed and the heuristic load shedding approach is used,then the low-carbon benefit evaluation procedure is illustrated.Based on this,the system state transition sampling method for calculating the loss of expected energy index with high DG penetration is proposed.The state transition models for non-active elements and DGs are established.The validity of the proposed method is demonstrated by a study case.The method can be used for the low-carbon benefit analysis on DG penetration distribution networks.

A diagnostic method for distribution networks based on power supply safety standards

In order to overcome the shortages of diagnostic method for distribution networks considering the reliability assessment,this paper proposed a method based on power supply safety standards.It profoundly analyzed the security standard of supply for urban power networks,and established quantitative indicators of load groups based on different fault conditions.Then a method suitable for diagnostic evaluation of urban distribution networks in China was given.In the method,“N-1”calibration analysis of the distribution network was conducted.Then the results are compared with quantitative indicators of load groups on different conditions deriving the diagnostic conclusions and the standard revision is discussed.The feasibility and accuracy of the method is finally verified in the case study.