A Scenario-classification Hybrid-based Banding Method for Power Transfer Limits of Critical Inter-corridors

To secure power system operations,practical dispatches in industries place a steady power transfer limit on critical inter-corridors,rather than high-dimensional and strong nonlinear stability constraints.However,computational complexities lead to over-conservative pre-settings of transfer limit,which further induce undesirable and non-technical congestion of power transfer.To conquer this barrier,a scenario-classification hybrid-based banding method is proposed.A cluster technique is adopted to separate similarities from historical and generated operating condition dataset.With a practical rule,transfer limits are approximated for each operating cluster.Then,toward an interpretable online transfer limit decision,costsensitive learning is applied to identify cluster affiliation to assign a transfer limit for a given operation.In this stage,critical variables that affect the transfer limit are also picked out via mean impact value.This enables us to construct low-complexity and dispatcher-friendly rules for fast determination of transfer limit.The numerical case studies on the IEEE 39-bus system and a real-world regional power system in China illustrate the effectiveness and conservativeness of the proposed method.

Component importance assessment of power systems for improving resilience under wind storms

Increasingly natural disasters and man-made malicious attacks threaten the power systems.Improving the resilience has become an inevitable requirement for the development of power systems.The importance assessment of components is of significance for resilience improvement,since it plays a crucial role in strengthening grid structure,designing restoration strategy,and improving resource allocation efficiency for disaster prevention and mitigation.This paper proposes a component importance assessment approach of power systems for improving resilience under wind storms.Firstly,the component failure rate model under wind storms is established.According to the model,system states under wind storms can be sampled by the non-sequential Monte Carlo simulation method.For each system state,an optimal restoration model is then figured out by solving a component repair sequence optimization model considering crew dispatching.The distribution functions of component repair moment can be obtained after a sufficient system state sampling.And Copeland ranking method is adopted to rank the component importance.Finally,the feasibility of the proposed approach is validated by extensive case studies.

Trading Model Combining Electricity, Heating,and Cooling Under Multi-energy Demand Response

The emerging multi-energy system has brought new challenges and opportunities to energy business worldwide.To address the issues in multi-energy trading,this paper proposes an electricity,heating,and cooling trading model for the interaction between the multi-energy service provider(MESP)and multi-energy consumer(MEC)by using bi-level programming.In the upper level,the model instructs the MESP to make decisions on the optimal energy purchasing scheme and energy economic dispatch.In the lower level,optimal consuming patterns of different energies with the given retail prices are modeled for the MEC.Specifically,a novel multi-energy demand response(DR)program that employs energy conversion devices is proposed.Numerical results show that MEC can reduce its consumption cost via the multi-energy DR.Meanwhile,MESP benefits greatly from the flexibilities of energy conversion.This research can provide theoretical support for the future development of multi-energy trading.

Optimal scheduling of power systems considering demand response

A novel optimal scheduling method considering demand response is proposed for power systems incorporating with large scale wind power.The proposed method can jointly dispatch the energy resources and demand side resources to mitigate the fluctuation of load and wind power output.It is noticed in practical operation that,without customer’s satisfaction being considered,customers might reject the too frequent or violent demand response all together.In this case,two indices that measure the customer satisfaction are then introduced as constraints to reduce the impact to end-users and avoid extreme demand adjustment.To make the model solvable,a proximate decoupling technique is used to dispose the concave constraint introduced by the customer satisfaction constraints.Results from the case studies show that the proposed model can significantly reduce the operation cost of power system while the demand response meets customer satisfaction.Especially,the total start-up costs of conventional thermal units decreases dramatically due to less startup times.Moreover,compared to the consumption way satisfaction constraint,the payment satisfaction constraint has a heavier influence on the cost.

Catastrophe Risk Management for Electric Power Distribution Systems:An Insurance Approach

High-impact,low-probability catastrophes may cause equipment damage,customer outages and serious economic losses to an aging power distribution infrastructure with low redundancy and automation.To cope with catastrophe risks faced by distribution systems(DSs),insurance is proposed as a supplement to existing resilience enhancement measures,which can provide financial aid in recovery after disasters,as well as incentives to make DSs more resilient to potential hazards.This calls for a quantitative assessment for insurance pricing that can not only predict potential losses caused by future catastrophes but also evaluate the effect of risk management measures.In this paper,a four-module actuarial framework,including hazard,vulnerability,resilience,and insurance modules,is developed to assess the catastrophe risks of DSs.Based on Monte Carlo simulation(MCS)and mixed integer linear programming(MILP),the dynamic characteristics of disasters,random failures of equipment,control measures including fault isolation,load transfer,line patrolling,manual switching,and fault repair,are comprehensively incorporated in the premium determination of catastrophe insurance.Numerical simulations are performed on the modified IEEE 33-bus test systems to illustrate the validity of the proposed catastrophe insurance schemes.