Stochastic programming based coordinated expansion planning of generation,transmission,demand side resources,and energy storage considering the DC transmission system

With the increasing penetration of wind and solar energies,the accompanying uncertainty that propagates in the system places higher requirements on the expansion planning of power systems.A source-grid-load-storage coordinated expansion planning model based on stochastic programming was proposed to suppress the impact of wind and solar energy fluctuations.Multiple types of system components,including demand response service entities,converter stations,DC transmission systems,cascade hydropower stations,and other traditional components,have been extensively modeled.Moreover,energy storage systems are considered to improve the accommodation level of renewable energy and alleviate the influence of intermittence.Demand-response service entities from the load side are used to reduce and move the demand during peak load periods.The uncertainties in wind,solar energy,and loads were simulated using stochastic programming.Finally,the effectiveness of the proposed model is verified through numerical simulations.

Rolling Decision Model of Thermal Power Retrofit and Generation Expansion Planning Considering Carbon Emissions and Power Balance Risk

With the increasing urgency of the carbon emission reduction task,the generation expansion planning process needs to add carbon emission risk constraints,in addition to considering the level of power adequacy.However,methods for quantifying and assessing carbon emissions and operational risks are lacking.It results in excessive carbon emissions and frequent load-shedding on some days,although meeting annual carbon emission reduction targets.First,in response to the above problems,carbon emission and power balance risk assessment indicators and assessment methods,were proposed to quantify electricity abundance and carbon emission risk level of power planning scenarios,considering power supply regulation and renewable energy fluctuation characteristics.Secondly,building on traditional two-tier models for low-carbon power planning,including investment decisions and operational simulations,considering carbon emissions and power balance risks in lower-tier operational simulations,a two-tier rolling model for thermal power retrofit and generation expansion planning was established.The model includes an investment tier and operation assessment tier and makes year-by-year decisions on the number of thermal power units to be retrofitted and the type and capacity of units to be commissioned.Finally,the rationality and validity of the model were verified through an example analysis,a small-scale power supply system in a certain region is taken as an example.The model can significantly reduce the number of days of carbon emissions risk and ensure that the power balance risk is within the safe limit.

Power generation expansion planning approach considering carbon emission constraints

Decarbonization of the power sector in China is an essential aspect of the energy transition process to achieve carbon neutrality.The power sector accounts for approximately 40%of China’s total CO_(2) emissions.Accordingly,collaborative optimization in power generation expansion planning(GEP)simultaneously considering economic,environmental,and technological concerns as carbon emissions is necessary.This paper proposes a collaborative mixedinteger linear programming optimization approach for GEP.This minimizes the power system’s operating cost to resolve emission concerns considering energy development strategies,flexible generation,and resource limitations constraints.This research further analyzes the advantages and disadvantages of current GEP techniques.Results show that the main determinants of new investment decisions are carbon emissions,reserve margins,resource availability,fuel consumption,and fuel price.The proposed optimization method is simulated and validated based on China’s power system data.Finally,this study provides policy recommendations on the flexible management of traditional power sources,the market-oriented mechanism of new energy sources,and the integration of new technology to support the attainment of carbon-neutral targets in the current energy transition process.

Generation-expansion planning with linearized primary frequency response constraints

As renewable energy resources increasingly penetrate the electric grid,the inertia capability of power systems has become a developmental bottleneck.Nevertheless,the importance of primary frequency response(PFR)when making generation-expansion plans has been largely ignored.In this paper,we propose an optimal generation-expansion planning framework for wind and thermal power plants that takes PFR into account.The model is based on the frequency equivalent model.It includes investment,startup/shutdown,and typical operating costs for both thermal and renewable generators.The linearization constraints of PFR are derived theoretically.Case studies based on the modified IEEE 39-bus system demonstrate the efficiency and effectiveness of the proposed method.Compared with methods that ignore PFR,the method proposed in this paper can effectively reduce the cost of the entire planning and operation cycle,improving the accommodation rate of renewable energy.

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.

Generation expansion planning considering efficient linear EENS formulation

Power system equipment outages are one of the most important factors affecting the reliability and economy of power systems.It is crucial to consider the reliability of the planning problems.In this paper,a generation expansion planning(GEP)model is proposed,in which the candidate generating units and energy storage systems(ESSs)are simultaneously planned by minimizing the cost incurred on investment,operation,reserve,and reliability.The reliability cost is computed by multiplying the value of lost load(VOLL)with the expected energy not supplied(EENS),and this model makes a compromise between economy and reliability.Because the computation of EENS makes the major computation impediment of the entire model,a new efficient linear EENS formulation is proposed and applied in a multi-step GEP model.By doing so,the computation efficiency is significantly improved,and the solution accuracy is still desirable.The proposed GEP model is illustrated using the IEEE-RTS system to validate the effectiveness and superiority of the new model.

Power Generation Expansion Planning Using an Interior Point with Cutting Plane （IP/CP） Method

The generation expansion planning is one of complex mixed-integer optimization problems, which involves a large number of continuous or discrete decision variables and constraints. In this paper, an interior point with cutting plane （IP/CP） method is proposed to solve the mixed-integer optimization problem of the electrical power generation expansion planning. The IP/CP method could improve the overall efficiency of the solution and reduce the computational time. Proposed method is combined with the Bender＇s decomposition technique in order to decompose the generation expansion problem into a master investment problem and a slave operational problem. The numerical example is presented to compare with the effectiveness of the proposed algorithm.

The Development of the Generation Expansion Planning System Using Multi-Criteria Decision Making Rule

The power expansion planning is large and capital intensive capacity planning. In the past, the expansion planning was established with the proper supply reliability in order to minimize social cost. However, such planning cannot be used in the power markets with many market participants. This paper proposed the power expansion planning process in the power markets. This system is composed of Regulator and Generation Company （GENCO）＇s model. Multi-criteria decision making rule is used for regulator model and several scenarios for GENCO model are applied.

Distribution Network Expansion Planning Based on Multi-objective PSO Algorithm

This paper presents a novel approach for electrical distribution network expansion planning using multi-objective particle swarm optimization (PSO). The optimization objectives are: investment and operation cost, energy losses cost, and power congestion cost. A two-phase multi-objective PSO algorithm is employed to solve this optimization problem, which can accelerate the convergence and guarantee the diversity of Pareto-optimal front set as well. The feasibility and effectiveness of both the proposed multi-objective planning approach and the improved multi-objective PSO have been verified by the 18-node typical system.

A Novel Bi-Level VSC-DC Transmission Expansion PlanningMethod of VSC-DC for Power System Flexibility and Stability Enhancement

Investigating flexibility and stability boosting transmission expansion planning(TEP)methods can increase the renewable energy(RE)consumption of the power systems.In this study,we propose a bi-level TEP method for voltage-source-converter-based direct current(VSC-DC),focusing on flexibility and stability enhancement.First,we established the TEP framework of VSC-DC,by introducing the evaluation indices to quantify the power system flexibility and stability.Subsequently,we propose a bi-level VSC-DC TEP model:the upper-level model acquires the optimal VSC-DC planning scheme by using the improved moth flame optimization(IMFO)algorithm,and the lower-level model evaluates the flexibility through time-series production simulation.Finally,we applied the proposedVSC-DC TEPmethod to the modified IEEE-24 and IEEE-39 test systems,and obtained the optimalVSCDC planning schemes.The results verified that the proposed method can achieve excellent RE curtailment with high flexibility and stability.Furthermore,the well-designed IMFO algorithm outperformed the traditional particle swarm optimization(PSO)and moth flame optimization(MFO)algorithms,confirming the effectiveness of the proposed approach.

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.

Resilience-oriented Hardening and Expansion Planning of Transmission System Under Hurricane Impact

In this paper,we propose a two-stage transmission hardening and planning(TH&P)model that can meet the load growth demand of normal scenarios and the resilience requirements of hurricane-induced damage scenarios.To better measure the resilience requirements,the proposed TH&P model includes two resilience assessment indexes,namely,the load shedding(LS)under the damage scenario and the average connectivity degree(ACD)at different stages.The first-stage model,which aims to meet the load growth demand while minimizing the LS,is formulated as a mixed-integer linear program(MILP)to minimize the total planning and hardening cost of transmission lines,the operating cost of generators,and the penalty cost of wind power and load shedding in both normal and damage scenarios.The second-stage model aims to further improve the ACD when the ACD of the scheme obtained from the first-stage model cannot reach the target.Specifically,the contribution of each transmission line to the ACD is calculated,and the next hardened line is determined to increase the ACD.This process is repeated until the ACD meets the requirements.Case studies of the modified IEEE RTS-24 and two-area IEEE reliability test system-1996 indicate the proposed TH&P model can meet the requirements for both normal and damage scenarios.

Security value based expansion planning of power system with integration of large-scale wind power

Concerning the integration of large-scale wind power,an integrated model of generation and transmission expansion planning is proposed based on the assessment of the value of steady state and dynamic security.In the assessment of security value,the unit commitment simulation based on the predicted hourly load and wind power output data in the planning horizon is used to evaluate the costs of preventive control,emergency control and social losses due to the uncertainty of load and wind power.The cost of preventive control consists of the fuel cost of power generation,the environmental cost and the load shedding cost.This not only provides a systematic method of security assessment of power system expansion planning schemes,but also broadens the perspective of power system planning from the technology and economic assessment to the measure of the whole social value.In the assessment process,the preventive control and emergency control of cascading failures are also presented,which provides a convincing tool for cascading failure analysis of planning schemes and makes the security assessment more comprehensive and reasonable.The proposed model and method have been demonstrated by the assessment of two power system planning schemes on the New England 10-genarator 39-bus System.The importance of considering the value of security and simulating hourly system operation for the planning horizon,in expansion planning of power system with integration of large-scale wind power,has been confirmed.

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 Considering Uncertainties in Loads and Renewable Energy Resources

This paper proposes a novel method for transmission network expansion planning(TNEP)that take into account uncertainties in loads and renewable energy resources.The goal of TNEP is to minimize the expansion cost of candidate lines without any load curtailment.A robust linear optimization algorithm is adopted to minimize the load curtailment with uncertainties considered under feasible expansion costs.Hence,the optimal planning scheme obtained through an iterative process would be to serve loads and provide a sufficient margin for renewable energy integration.In this paper,two uncertainty budget parameters are introduced in the optimization process to limit the considered variation ranges for both the load and the renewable generation.Simulation results obtained from two test systems indicate that the uncertainty budget parameters used to describe uncertainties are essential to arrive at a compromise for the robustness and optimality,and hence,offer a range of preferences to power system planners and decision makers.

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.

Analysis of electric vehicle charging using the traditional generation expansion planning analysis tool WASP-IV

Electric vehicles(EV)are proposed as a measure to reduce greenhouse gas emissions in transport and support increased wind power penetration across modern power systems.Optimal benefits can only be achieved,if EVs are deployed effectively,so that the exhaust emissions are not substituted by additional emissions in the electricity sector,which can be implemented using Smart Grid controls.This research presents the results of an EV roll-out in the all island grid(AIG)in Ireland using the long term generation expansion planning model called the Wien Automatic System Planning IV(WASP-IV)tool to measure carbon dioxide emissions and changes in total energy.The model incorporates all generators and operational requirements while meeting environmental emissions,fuel availability and generator operational and maintenance constraints to optimize economic dispatch and unit commitment power dispatch.In the study three distinct scenarios are investigated base case,peak and off-peak charging to simulate the impacts of EV’s in the AIG up to 2025.

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.

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.

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.