Low Carbon Economic Dispatch of Integrated Energy System Considering Power Supply Reliability and Integrated Demand Response

Integrated energy system optimization scheduling can improve energy efficiency and low carbon economy.This paper studies an electric-gas-heat integrated energy system,including the carbon capture system,energy coupling equipment,and renewable energy.An energy scheduling strategy based on deep reinforcement learning is proposed to minimize operation cost,carbon emission and enhance the power supply reliability.Firstly,the lowcarbon mathematical model of combined thermal and power unit,carbon capture system and power to gas unit(CCP)is established.Subsequently,we establish a low carbon multi-objective optimization model considering system operation cost,carbon emissions cost,integrated demand response,wind and photovoltaic curtailment,and load shedding costs.Furthermore,considering the intermittency of wind power generation and the flexibility of load demand,the low carbon economic dispatch problem is modeled as a Markov decision process.The twin delayed deep deterministic policy gradient(TD3)algorithm is used to solve the complex scheduling problem.The effectiveness of the proposed method is verified in the simulation case studies.Compared with TD3,SAC,A3C,DDPG and DQN algorithms,the operating cost is reduced by 8.6%,4.3%,6.1%and 8.0%.

Reliability of Power System Integrated with Wind Generation Considering Carbon Tax

This paper proposes a method to evaluate the reliability of power system with different capacities of wind power while considering carbon tax. The proposed method is a hybrid approach which combines Frequency and Duration (F&D) method and Monte Carlo Simulation (MCS) method. MCS method is used to achieve a model to simulate the random status of power system. Also, the proposed method is applied on the IEEE 14-bus test system to investigate the effects of integrating different capacities of wind energy to the reliability of power system with considering carbon tax.

Fundamental Research on Enhancing Operation Reliability for Large-Scale Interconnected Power Grids——An interview with Zhou Xiaoxin, chief scientist of "973 Program"

At the end of last year, the editors from Power and Electrical Engineers interviewed Zhou Xiaoxin on "Fundamental Research on Enhancing Operation Reliability for Large-Scale Interconnected Power Grids", a project of "973 Program". Mr. Zhou, the chief engineer of China Electric Power Research Institute(CEPRI) and an academician of Chinese Academy of Sciences, is the chief scientist in charge of this research project.

Mathematical Morphology-Based Artificial Technique for Renewable Power Application

This paper suggests a combined novel control strategy for DFIG based wind power systems(WPS)under both nonlinear and unbalanced load conditions.The combined control approach is designed by coordinating the machine side converter(MSC)and the load side converter(LSC)control approaches.The proposed MSC control approach is designed by using a model predictive control(MPC)approach to generate appropriate real and reactive power.The MSC controller selects an appropriate rotor voltage vector by using a minimized optimization cost function for the converter operation.It shows its superiority by eliminating the requirement of transformation,switching table,and the PWM techniques.The proposed MSC reduces the cost,complexity,and computational burden of the WPS.On the other hand,the LSC control approach is designed by using a mathematical morphological technique(MMT)for appropriate DC component extraction.Due to the appropriate DC-component extraction,the WPS can compensate the harmonics during both steady and dynamic states.Further,the LSC controller also provides active power filter operation even under the shutdown of WPS condition.To verify the applicability of coordinated control operation,the WPS-based microgrid system is tested under various test conditions.The proposed WPS is designed by using a MATLAB/Simulink software.

Robust N−k Security-constrained Optimal Power Flow Incorporating Preventive and Corrective Generation Dispatch to Improve Power System Reliability

As extreme weather events have become more frequent in recent years,improving the resilience and reliability of power systems has become an important area of concern.In this paper,a robust preventive-corrective security-constrained optimal power flow(RO-PCSCOPF)model is proposed to improve power system reliability under N−k outages.Both the short-term emergency limit(STL)and the long-term operating limit(LTL)of the post-contingency power flow on the branch are considered.Compared with the existing robust corrective SCOPF model that only considers STL or LTL,the proposed ROPCSCOPF model can achieve a more reliable generation dispatch solution.In addition,this paper also summarizes and compares the solution methods for solving the N−k SCOPF problem.The computational efficiency of the classical Benders decomposition(BD)method,robust optimization(RO)method,and line outage distribution factor(LODF)method are investigated on the IEEE 24-bus Reliability Test System and 118-bus system.Simulation results show that the BD method has the worst computation performance.The RO method and the LODF method have comparable performance.However,the LODF method can only be used for the preventive SCOPF and not for the corrective SCOPF.The RO method can be used for both.

A new method for optimal FTU placement in distribution network under consideration of power service reliability

Modern distribution network with high penetration of intermittent renewable sources and the so-called prosumers requires more reliable distribution automation(DA) system for safe operation and control. The design of optimal feeder terminal units(FTU)placement is critical and economical for the effective DA application. Previously proposed solutions of optimal FTU placement aiming to ensure the accuracy of state estimation(SE), typically include the following two main shortcomings: 1) only to obtain the optimal FTU placement in quantity, and the analysis of FTU location is not considered yet; 2) few consider the uncertainty of intermittent power injections in the analysis of state estimation. In this paper, a modified methodology of FTU placement is proposed not only aiming to ensure the accuracy of state estimation with the minimum number of meters, but also finding those specific FTU locations to guarantee the power service reliability. Moreover, the uncertainty models of those intermittent power injections are also considered by using probability density function(PDF). The resultant optimization problem is addressed by using the covariance matrix adaptation evolution strategy(CMA-ES). Case studies demonstrate the feasibility and effectiveness of the proposed methodology.

Operation Strategies for Coordinating Battery Energy Storage with Wind Power Generation and Their Effects on System Reliability

The variability of wind power generation requires the allocation of a flexible energy reserve which is capable of compensating for possible imbalances between the load and generation. To reduce the variability of wind power generation and loss of load in generation deficit, we propose operation strategies for coordinating battery energy storage with wind power generation. The effects of the operation strategies on system reliability are evaluated by the developed computation model that represents the main aspects and operation limitations of the batteries. The performance evaluation of the power system is based on the composite reliability indices of loss of load probability(LOLP) and expected energy not supplied(EENS), which is calculated through sequential Monte Carlo simulation. Tests are performed by the developed model with a tutorial system consisting of five busbars and the IEEE RTS system. The results show that the use of large-scale batteries is an alternative to physically guarantee the wind power plants and to act as an operation reserve to reduce the risk of loss of load.

Applications of survival functions to continuous semi-Markov processes for measuring reliability of power transformers

The reliability of power transformers is subject to service age and health condition.This paper proposes a practical model for the evaluation of two reliability indices:survival function(SF)and mean residual life(MRL).In the proposed model,the periodical modeling of power transformers are considered for collecting the information on health conditions.The corresponding health condition is assumed to follow a continuous semi-Markov process for representing a state transition.The proportional hazard model(PHM)is introduced to incorporate service age and health condition into hazard rate.In addition,the proposed model derives the analytical formulas for and offers the analytical evaluation of SF and MRL.SF and MRL are calculated for new components and old components,respectively.In both cases,the proposed model offers rational results which are compared with those obtained from comparative models.The results obtained by the contrast of the proposed analytical method and the Monte Carlo method.The impact of differentmodel parameters and the coefficient of variation(CV)on reliability indices are discussed in the case studies.

Smart Grid Functionalities Evaluation

In the last years, with the advent of Smart Grids, many research and demonstration projects have seen the light in order to involve electric system in the implementation of advances in information and communication technologies, in order to improve network efficiency, reliability, security and quality of service. Before new implementations are performed, previous results have to be studied, and taken into account. In this line, this work presents the methodology, results and conclusions of the evaluation of the Smart Grid functionalities developed by 5 different DSOs during DISCERN project in order to select the optimal, cost-effective and most replicable solutions for the strategic development of the intelligence at medium voltage (MV) and low voltage (LV) networks.

A Tabu-search-based Algorithm for Distribution Network Restoration to Improve Reliability and Resiliency

Fault restoration techniques have always been crucial for distribution system operators(DSOs).In the last decade,it started to gain more and more importance due to the introduction of output-based regulations where DSO performances are evaluated according to frequency and duration of energy supply interruptions.The paper presents a tabu-searchbased algorithm able to assist distribution network operational engineers in identifying solutions to restore the energy supply after permanent faults.According to the network property,two objective functions are considered to optimize either reliability or resiliency.The mathematical formulation includes the traditional feeders,number of switching operation limit,and radiality constraints.Thanks to the DSO of Milan,Unareti,the proposed algorithm has been tested on a real distribution network to investigate its effectiveness.

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.

Primary energy congestion of power systems

Primary energy has the potential to bring challenges to the reliability,economic,and eco-friendliness of global electric power systems.The concept of electric power security are proposed,including many factors that are not considered in power system reliability analysis,such as coal supply for power system,fuel price for electricity power market,carbon emissions of power generation,and so on.It is broader than power system reliability and security,which means that providing energy in the form of reliable,economical,and eco-friendly electric power.Following an account of existing blackout defence methods and systems,the processes of transforming various kinds of primary energy into electric power and the interactions between them are described,particularly with regard to flows of energy,capital,and information.Factors that limit the liquidity of these flows are defined as“generalized congestion”,and the challenges presented by primary energy are named“primary energy congestion”.China’s dilemma on coal supply for power generation is presented in some detail as an example of primary energy congestion.To cope with impacts of the primary energy on electric power systems,an idea is introduced to extend the scope of existing coordinated blackout defence systems to account for primary energy,which would lead to an integrated tool to provide decision support to power system operators accounting for primary energy congestion.

Framework of Probabilistic Power System Planning

This paper presents the framework of probabilistic power system planning.The basic concepts,criteria,procedure,analysis techniques and tasks of probabilistic power system planning are discussed.Probabilistic reliability evaluation and probabilistic economic assessment are two key steps.It should also be recognized that probabilistic system planning has a wider coverage than these two aspects.An actual example using a utility system is given to demonstrate an application of probabilistic transmission development planning.

Resilience Analysis and Cascading Failure Modeling of Power Systems Under Extreme Temperatures

In this paper, we propose an AC power flow based cascading failure model that explicitly considers external weather conditions, extreme temperatures in particular, and evaluates the impact of extreme temperature on the initiation and propagation of cascading blackouts. Based on this model, resilience analysis of the power system is performed with extreme temperatures. Specifically, the changes of load and dynamic line rating are modeled due to temperature disturbance. The probabilities for transmission line and generator outages are evaluated, and the timing for each type of events is calculated to decide the actual event sequence. It should be emphasized that the correlated events, in the advent of external temperature changes, could contribute to voltage instability. Besides, we model undervoltage load shedding and operator re-dispatch as control strategies for preventing the propagation of cascading failures. The effectiveness of the proposed model is verified by simulation results on the RTS-96 3-area system. It is found that temperature disturbances can lead to correlated load change and line/generator tripping, which will greatly increase the risk of cascading and voltage instability. Critical temperature change, critical area with temperature disturbance, the identification of most vulnerable buses, and the comparison of different control strategies are also investigated.

Data-driven Operation Risk Assessment of Wind-integrated Power Systems via Mixture Models and Importance Sampling

The increasing penetration of highly intermittent wind generation could seriously jeopardize the operation reliability of power systems and increase the risk of electricity outages. To this end, this paper proposes a novel data-driven method for operation risk assessment of wind-integrated power systems. Firstly, a new approach is presented to model the uncertainty of wind power in lead time. The proposed approach employs k-means clustering and mixture models(MMs) to construct time-dependent probability distributions of wind power.The proposed approach can also capture the complicated statistical features of wind power such as multimodality. Then, a nonsequential Monte Carlo simulation(NSMCS) technique is adopted to evaluate the operation risk indices. To improve the computation performance of NSMCS, a cross-entropy based importance sampling(CE-IS) technique is applied. The CE-IS technique is modified to include the proposed model of wind power.The method is validated on a modified IEEE 24-bus reliability test system(RTS) and a modified IEEE 3-area RTS while employing the historical data of wind generation. The simulation results verify the importance of accurate modeling of shortterm uncertainty of wind power for operation risk assessment.Further case studies have been performed to analyze the impact of transmission systems on operation risk indices. The computational performance of the framework is also examined.

An Optimization Model for Reliability Improvement and Cost Reduction Through EV Smart Charging

There is a general concern that the increasing penetration of electric vehicles(EVs)will result in higher aging failure probability of equipment and reduced network reliability.The electricity costs may also increase,due to the exacerbation of peak load led by uncontrolled EV charging.This paper proposes a linear optimization model for the assessment of the benefits of EV smart charging on both network reliability improvement and electricity cost reduction.The objective of the proposed model is the cost minimization,including the loss of load,repair costs due to aging failures,and EV charging expenses.The proposed model incorporates a piecewise linear model representation for the failure probability distributions and utilizes a machine learning approach to represent the EV charging load.Considering two different test systems(a 5-bus network and the IEEE 33-bus network),this paper compares aging failure probabilities,service unavailability,expected energy not supplied,and total costs in various scenarios with and without the implementation of EV smart charging.

An Optimal Expansion Planning of Electric Distribution Network Incorporating Health Index and Non-network Solutions

The health status of distribution equipment and networks is not considered directly in existing distribution network planning methods.In order to effectively consider the health status and deal with the risk associated with load and renewable generation uncertainties,this paper presents a new optimal expansion planning approach for distribution network(EPADN)incorporating equipment’s health index(HI)and non-network solutions(NNSs).HI and relevant risk are used to help develop the optimal equipment replacement strategy and temporary NNSs are considered as promising options for handling the uncertainties of load growth,reliability requirements of power supply and output of distributed energy resources(DERs)at a lower cost than network alternatives.An EPADN model using network solutions(NSs)and NNSs is proposed.The planning objectives of the proposed model are safety,reliability,economy,and‘greenness’that are also the meaning of distribution network HI.A method integrating an improved niche genetic algorithm(INGA)and a spanning tree algorithm(STA)is fitted to solve the model presented here for real sized networks with a manageable computational cost.Simulation results of an actual 22-node distribution network in China,illustrate the effectiveness of the proposed approach.

Analysis of the Quantity and Causes of Outages in LV/MV Electric Grids

The paper considers the quantity and causes of outages in electric grids of low and medium voltages using the example of an electric grid of a regional power supply company.The main types of damage to the equipment of power lines and transformer substations were identified.Data on other areas of rural and urban electric grids are also analyzed.The main directions for reducing the quantity of outages in electric grids are proposed based on this analysis.Among them,there are the use of isolated wires in power transmission lines,the improvement of design of switching devices,switches and terminals of transformers,the application of technical condition diagnostics,the disaggregating of power lines and the increase of protection sensitivity of power lines.Most of the causes of equipment damage can be prevented by increasing the maintenance level of this equipment.