The renewable portfolio standard has been promoted in parallel with the reform of the electricity market,and the flexibility requirement of the power system has rapidly increased.To promote renewable energy consumption and improve power system flexibility,a bi-level optimal operation model of the electricity market is proposed.A probabilistic model of the flexibility requirement is established,considering the correlation between wind power,photovoltaic power,and load.A bi-level optimization model is established for the multi-markets; the upper and lower models represent the intra-provincial market and inter-provincial market models,respectively.To efficiently solve the model,it is transformed into a mixed-integer linear programming model using the Karush-Kuhn-Tucker condition and Lagrangian duality theory.The economy and flexibility of the model are verified using a provincial power grid as an example.

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Half-wavelength transmission can transmit large-scale renewable energy over very long distances.This paper proposes an improved steady-state voltage-control method for half-wavelength transmission systems considering largescale wind-power transmission.First,the unique voltage characteristics of half-wavelength lines are deduced based on the distributed parameter model.In the secondary voltage-control level,reactive power-transmission limits of half-wavelength lines are introduced as another control objective except for tracing the pilot bus voltage reference.Considering the uncertainty and fluctuation of wind power,the overvoltage risk-assessment method of half-wavelength lines is presented to determine specific voltage-control strategies.Simulation results demonstrate that the proposed voltage-control method delivers superior tracking performance according to a voltage reference value and prevents the overvoltage risk of halfwavelength lines effectively in different wind-power penetrations.

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Since the connection of small-scale wind farms to distribution networks,power grid voltage stability has been reduced with increasing wind penetration in recent years,owing to the variable reactive power consumption of wind generators.In this study,a two-stage reactive power optimization method based on the alternating direction method of multipliers (ADMM)algorithm is proposed for achieving optimal reactive power dispatch in wind farm-integrated distribution systems.Unlike existing optimal reactive power control methods,the proposed method enables distributed reactive power flow optimization with a two-stage optimization structure.Furthermore,under the partition concept,the consensus protocol is not needed to solve the optimization problems.In this method,the influence of the wake effect of each wind turbine is also considered in the control design.Simulation results for a mid-voltage distribution system based on MATLAB verified the effectiveness of the proposed method.

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With the development of carbon electricity,achieving a low-carbon economy has become a prevailing and inevitable trend.Improving low-carbon expansion generation planning is critical for carbon emission mitigation and a lowcarbon economy.In this paper,a two-layer low-carbon expansion generation planning approach considering the uncertainty of renewable energy at multiple time scales is proposed.First,renewable energy sequences considering the uncertainty in multiple time scales are generated based on the Copula function and the probability distribution of renewable energy.Second,a two-layer generation planning model considering carbon trading and carbon capture technology is established.Specifically,the upper layer model optimizes the investment decision considering the uncertainty at a monthly scale,and the lower layer one optimizes the scheduling considering the peak shaving at an hourly scale and the flexibility at a 15-minute scale.Finally,the results of different influence factors on low-carbon generation expansion planning are compared in a provincial power grid,which demonstrate the effectiveness of the proposed model.

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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.

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A power source-power grid coordinated typhoon defense strategy is proposed in this study to minimize the cost of power grid anti-typhoon reinforcement measures and improve defense efficiency.It is based on multiagent dynamic game theory.This strategy regards a typhoon as a rational gamer that always causes the greatest damage.Together with the grid planner and black start unit (BSU)planner,it forms a multiagent defense-attack-defense dynamic game model naturally.The model is adopted to determine the optimal reinforcements for the transmission lines,black start power capacity,and location.Typhoon Hato,which struck a partial coastal area in Guangdong province in China in 2017,was adopted to formulate a step-by-step model of a typhoon attacking coastal area power systems.The results were substituted into the multiagent defense-attack-defense dynamic game model to obtain the optimal transmission line reinforcement positions,as well as optimal BSU capacity and geographic positions.An effective typhoon defense strategy and minimum load shedding were achieved,demonstrating the feasibility and correctness of the proposed strategy.The related theories and methods of this study have positive significance for the prevention of uncertain large-scale natural disasters.

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There has been an intense discussion on the energy infrastructure cooperation in Northeast Asia.Most studies have focused on the technical feasibility of grid interconnection,deployment of renewable energy,and have ignored the quantitative analysis of social and economic benefits of these proposals.This study uses a computable general equilibrium model to evaluate the effects of energy interconnection in Northeast Asia.Key model development tasks include 1)constructing a new nesting structure,2)econometrically estimating the constant elasticities of substitution (CES)between fossil- and non-fossil-power generation bundles,3)developing a new base-case scenario,and 4)developing the policy scenario.We found that while Northeast Asia will benefit from energy interconnection development with higher GDP than in the base-case; there will be a trade-off between higher investment and lower consumption.Sector results and environmental implications in this region are also discussed.

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The ubiquitous power Internet of Things (UPIoT)is an intelligent service system with comprehensive state perception,efficient processing,and flexible application of information.It focuses on each link of the power system and makes full use of the mobile internet,artificial intelligence,and other advanced information and communication technologies in order to realize the inter-human interaction of all things in all links of the power system.This article systematically presents to the national and international organizations and agencies in charge of UPIoT layer standardization the status quo of the research on the Internet of Things (IoT)-related industry standards system.It briefly describes the generic standard classification methods,layered architecture,conceptual model,and system tables in the UPIoT application layer.Based on the principles of inheritance,innovation,and practicability,this study divides the application layer into customer service,power grid operation,integrated energy,and enterprise operation,emerging business and analyzes the standard requirements of these five fields.This study also proposes a standard plan.Finally,it summarizes the research report and provides suggestions for a follow-up work.

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The use of clean electricity to replace fossil energy burning for heating is an important emission reduction way to achieve carbon neutrality.Without a good business model,it is very difficult to promote electric heating as a replacement for coal-fired systems in some areas with abundant coal resources.This study proposed a new business model for electric heating with stakeholders that included the government,the power grid company,and heat users.Based on this model,a specific tri-objective optimization model was proposed with the electric heating promotion power,heating electricity price,and government subsidy as variables to characterize the game relationship of the stakeholders,and the components of the stakeholder benefit function were analyzed in detail.A classical multi-objective genetic algorithm was used to solve the model.Finally,an “electrical heating” project for a typical area in China was analyzed,and four promotion cases were examined.The results showed that the power grid company and users had an antagonistic relationship in relation to the electricity price,but the best solution was found for all three stakeholders due to the high financial subsidies provided by the government.

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With the development of the energy Internet,more distributed generators are connected to the power grid,resulting in numerous heterogeneous energy networks.However,different energy networks cannot perform efficient energy trading in the centralized management mode,this deeply affecting the complementary ability of heterogeneous energy,resulting in the islanded energy phenomenon.In this model,the same energy on the chain is traded within the chain,and the heterogeneous energy on different chains is traded across chains.To trade energy between heterogeneous energy networks more efficiently,the blockchain-based cross-chain model is proposed based on the existing infrastructure.Heterogeneous energy nodes are assigned to different energy sub-chains and cross-chain energy transactions are performed through a relay-chain,which utilizes the improved Boneh-Lynn-Shacham signature scheme consensus algorithm based on the proof-of-stake and practical Byzantine fault tolerance.The experimental simulations on energy trading efficiency,throughput,and security,show its superiority over existing systems.Further,the simulation results provide a reference for the application of cross-chain technology in energy interconnection.

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