Robust transmission expansion planning model considering multiple uncertainties and active load

Uncertainty must be well addressed in transmission expansion planning(TEP)problem,and it significantly affects the reliability and cost-effectiveness of power systems.Owing to the complex operating environment of power systems,it is crucial to consider different types of uncertainties during the planning stage.In this paper,a robust TEP model is proposed by considering multiple uncertainties and active load.Specifically,in this model,the uncertainties of wind power output and contingency probability are considered simultaneously.The uncertainties are described by scenario and interval,and the Benders decomposition technique is applied to solve the model.The feasibility and effectiveness of the proposed model are illustrated using the IEEE RTS and IEEE 118-node systems.

Resilience-oriented Transmission Expansion Planning with Optimal Transmission Switching Under Typhoon Weather

This paper presents resilience-oriented transmission expansion planning(RTEP)with optimal transmission switching(OTS)model under typhoon weather.The proposed model carefully considers the uncertainty of component vulnerability by constructing a typhoon-related box uncertainty set where component failure rate varies within a range closely related with typhoon intensity.Accordingly,a min-max-min model is developed to enhance transmission network resilience,where the upper level minimizes transmission lines investment,the middle level searches for the probability distribution of failure status leading to max worst-case expected load-shedding(WCEL)under typhoon,and the lower level optimizes WCEL by economic dispatch(ED)and OTS.A nested decomposition algorithm based on benders decomposition is developed to solve the model.Case studies of modified IEEE 30-bus and 261-bus system of a Chinese region illustrate that:a)the proposed RTEP method can enhance resilience of transmission network with less investment than widely used RTEP method based on attacker and defender(DAD)model,b)the influence of OTS on RTEP is closely related with contingency severity and system scale and c)the RTEP model can be efficiently solved even in a large-scale system.

Suggestion on 9th Five year and 2010 plan for transmission and substation equipment

China’s power transmission equipment industry has formed, through technical innovation and development in past several decades especially in the period from the "6th Five Year Plan" to "8th Five Year Plan", a capability in furnishing equipments for 15,000 MW yearly key power transmission, power networks and substations project with voltage up to 500 kV. These achievements

Coordinated Planning of Large-Scale Wind Farm Integration System and Transmission Network

Large-scale centralized exploitation of intermittent wind energy resources has become popular in many countries.However,as a result of the frequent occurrence of largescale wind curtailment,expansion of corresponding transmission projects has fallen behind the speed at which installed wind capacity can be developed.In this paper,a coordinated planning approach for a large-scale wind farm integration system and its related regional transmission network is proposed.A bilevel programming model is formulated with the objective of minimizing cost.To reach the global optimum of the bi-level model,this work proposes that the upper-level wind farm integration system planning problem needs to be solved jointly with the lower-level regional transmission planning problem.The bi-level model is expressed in terms of a linearized mathematical problem with equilibrium constraints(MPEC)by Karush-KuhnTucker conditions.It is then solved using mixed integer linear programming solvers.Numerical simulations are conducted to show the validity of the proposed coordinated planning method.

A Scenario-Based Robust Transmission Network Expansion Planning Method for Consideration of Wind Power Uncertainties

This paper uses a novel scenario generation method for tackling the uncertainties of wind power in the transmission network expansion planning(TNEP)problem.A heuristic moment matching(HMM)method is first applied to generate the typical scenarios for capturing the stochastic features of wind power,including expectation,standard deviation,skewness,kurtosis,and correlation of multiple wind farms.Then,based on the typical scenarios,a robust TNEP problem is presented and formulated.The solution of the problem is robust against all the scenarios that represent the stochastic features of wind power.Three test systems are used to verify the HMM method and is compared against Taguchi’s Orthogonal Array(OA)method.The simulation results show that the HMM method has better performance than the OA method in terms of the trade-off between robustness and economy.Additionally,the main factors influencing the planning scheme are studied,including the number of scenarios,wind farm capacity,and penalty factors,which provide a reference for system operators choosing parameters.

Integrated generation-transmission expansion planning for offshore oilfield power systems based on genetic Tabu hybrid algorithm

To address the planning issue of offshore oil-field power systems, an integrated generation-transmission expansion planning model is proposed. The outage cost is considered and the genetic Tabu hybrid algorithm(GTHA)is developed to find the optimal solution. With the proposed integrated model, the planning of generators and transmission lines can be worked out simultaneously,which outweighs the disadvantages of separate planning,for instance, unable to consider the influence of power grid during the planning of generation, or insufficient to plan the transmission system without enough information of generation. The integrated planning model takes into account both the outage cost and the shipping cost, which makes the model more practical for offshore oilfield power systems. The planning problem formulated based on the proposed model is a mixed integer nonlinear programming problem of very high computational complexity, which is difficult to solve by regular mathematical methods. A comprehensive optimization method based on GTHA is also developed to search the best solution efficiently.Finally, a case study on the planning of a 50-bus offshore oilfield power system is conducted, and the obtained results fully demonstrate the effectiveness of the presented model and method.

Transmission network expansion planning with embedded constraints of short circuit currents and N-1 security

An approach of transmission network expan-sion planning with embedded constraints of short circuit currents and N-1 security is proposed in this paper.The problem brought on by the strong nonlinearity property of short circuit currents is solved with a linearization method based on the DC power flow.The model can be converted to a mixed-integer linear programming problem,realizing the optimization of planning model that considers the constraints of linearized short circuit currents and N-1 security.To compensate the error caused by the assump-tions of DC power flow,the compensation factor is pro-posed.With this factor,an iterative algorithm that can compensate the linearization error is then presented.The case study based on the IEEE 118-bus system shows that the proposed model and approach can be utilized to:opti-mize the construction strategy of transmission lines;ensure the N-1 security of the network;and effectively limit the short circuit currents of the system.

Stochastic Transmission Expansion Planning Incorporating Reliability Solved Using SFLA Meta-heuristic Optimization Technique

This paper addresses stochastic transmission expansion planning(TEP)under uncertain load conditions when reliability is taken into consideration.The main objective of the proposed TEP is to minimize the total planning cost by denoting the place,number,and type of new transmission lines subject to safe operation criteria.In this paper,the objective function consists of two terms,namely,investment cost(IC)of new lines and reliability cost.The reliability cost is incorporated as the loss of load cost(LOLC).Network uncertainties in the form of loads are molded as Gaussian probability distribution function(PDF).Monte-Carlo simulation is applied to tackle the uncertainties.The proposed stochastic TEP is expressed as constrained optimization planning and solved using shuffled frog leaping algorithm(SFLA)SFLA is compared to other optimization techniques such as particle swarm optimization(PSO)and genetic algorithms(GA).Finally,stochastic planning(planning including uncertainty)and deterministic planning(planning excluding uncertainty)are compared to demonstrate impacts of uncertainty on the results.Simulation results in different cases and scenarios verify the effectiveness and viability of the proposed stochastic TEP,including uncertainty and reliability.

Distributionally Robust Co-optimization of Transmission Network Expansion Planning and Penetration Level of Renewable Generation

Transmission network expansion can significantly improve the penetration level of renewable generation.However,existing studies have not explicitly revealed and quantified the trade-off between the investment cost and penetration level of renewable generation.This paper proposes a distributionally robust optimization model to minimize the cost of transmission network expansion under uncertainty and maximize the penetration level of renewable generation.The proposed model includes distributionally robust joint chance constraints,which maximize the minimum expectation of the renewable utilization probability among a set of certain probability distributions within an ambiguity set.The proposed formulation yields a twostage robust optimization model with variable bounds of the uncertain sets,which is hard to solve.By applying the affine decision rule,second-order conic reformulation,and duality,we reformulate it into a single-stage standard robust optimization model and solve it efficiently via commercial solvers.Case studies are carried on the Garver 6-bus and IEEE 118-bus systems to illustrate the validity of the proposed method.

Distributionally Robust Transmission Expansion Planning Considering Uncertainty of Contingency Probability

The outage of power system equipment is one of the most important factors that affect the reliability and economy of power system.It is crucial to consider the influence of contingencies elaborately in planning problem.In this paper,a distributionally robust transmission expansion planning model is proposed in which the uncertainty of contingency probability is considered.The uncertainty of contingency probability is described by uncertainty interval based on the outage rate of single equipment.An epigraph reformulation and Benders decomposition are applied to solve the proposed model.Finally,the feasibility and effectiveness of the proposed model are illustrated on the IEEE RTS system and the IEEE 118-bus system.

Two-Stage Stochastic Dual Dynamic Programming for Transmission Expansion Planning with Significant Renewable Generation and N-k Criterion

The large-scale integration of renewable energy sources(RES)is the global trend to deal with the energy crisis and greenhouse emissions.Due to the intermittent nature of RES together with the uncertainty of load demand,the problem of transmission expansion planning(TEP)is facing more and more challenges from uncertainties.In this paper,the TEP problem is modeled as a two-stage formulation,so as to minimize the total of investment costs and generation costs.To ensure the utilization level of the RES generation,the expansion plan is required to provide sufficient transmission capacity for the integration of RES.Also,N-k security criterion is considered into the model,so the expansion plan can meet the required security criteria.The stochastic dual dynamic programming(SDDP)approach is applied to consider the uncertainties,and the whole model is solved by Benders’decomposition technique.Two case studies are carried out to compare the performance of the SDDP approach and the deterministic approach.Results show that the expansion plan obtained by the SDDP approach has a better performance than that of the deterministic approach.

An Economic Benefit Evaluation Model and its Application for Optimizing Transmission Capacity of Multinational Interconnections

Multinational power grid interconnections play a critical part in supporting the vision of global energy internet.During the early stages of the Global Energy Internet,the value proposition of multinational interconnections should be carefully investigated in order to stimulate the activities for associated countries in such potential interconnections.This paper proposes a new e conomic benefit evaluation model which is quantified by using a chronological production cost simulation approach.The economic benefit model comprehensively considered investment costs and the benefits of the decrease of load payments and the increase of net generation revenue due to a transmission project interconnected with different countries.This economic benefit model can assist to quantitatively determine the optimal transmission capacity for multinational interconnections to achieve maximum economic benefits as a whole.In the case study,the economic benefit of an interconnected system of western China and the Gulf States is assessed by using the method proposed in this paper.And the optimal interconnection capacity with maximum benefit is achieved.The case study shows that the proposed method can be used for economic benefit assessment and is of great significance to the multinational and intercontinental transmission interconnections.

Expansion Planning for Renewable Integration in Power System of Regions with Very High Solar Irradiation

In this paper,we address the long-term generation and transmission expansion planning for power systems of regions with very high solar irradiation.We target the power systems that currently rely mainly on thermal generators and that aim to adopt high shares of renewable sources.We propose a stochastic programming model with expansion alternatives including transmission lines,solar power plants(photovoltaic and concentrated solar),wind farms,energy storage,and flexible combined cycle gas turbines.The model represents the longterm uncertainty to characterize the demand growth,and the short-term uncertainty to characterize daily solar,wind,and demand patterns.We use the Saudi Arabian power system to illustrate the functioning of the proposed model for several cases with different renewable integration targets.The results show that a strong dependence on solar power for high shares of renewable sources requires high generation capacity and storage to meet the night demand.

Application and Modeling of Battery Energy Storage in Power Systems

This paper presents engineering experiences from battery energy storage system(BESS)projects that require design and implementation of specialized power conversion systems(a fast-response,automatic power converter and controller).These projects concern areas of generation,transmission,and distribution of electric energy,as well as end-energy user benefits,such as grid frequency regulation,renewable energy smoothing and leveling,energy dispatching and arbitrage,power quality and reliability improvements for connected customers,islanding operations,and smart microgrid applications.In general,a grid level BESS project sends an interconnect request to utility power grids in the project development stage.Simulation models of equipment are then sent for a system impact study(e.g.,power flow and/or stability analysis),based on utility grid code requirements.The system study then determines the connection’s technical feasibility and impact of the project on the power grid.In this paper,a set of new BESS models is presented that are configured and parameterized for use in system impact studies as well as transmission planning studies.The models,which have been recently approved and released by the U.S.Western Electricity Coordinating Council(WECC),represent the steady state and dynamic performance of the BESS in several software platforms for power system studies based on operating project performance experience.Model benchmarking results as well as a real system case study are also included in the paper to show that the parameterized and tuned models respond correctly and as expected when system operating conditions change following contingency events.Finally,this paper provides useful guidelines in the use of new models to represent a BESS for power system analysis.