The Research about the Trans-provincial Centralized Bidding Trading Market of East China Power Grid --I:Empirical Analysis

The clearing price and bidding price in electricity market are two key indicators to measure whether it is reasonable or not. Based on the grey incidence analysis, this paper studies the correlation coefficient between the clearing price and bidding price with the generation cost, the supervision and rules of the market, the supply and demand situation, the behavior of market members over the same period, which is based on the actual data of the trans-provincial centralized trading market of East China Power Grid. The results show that the factors affecting the clearing price and bidding price from largest to smallest are generation cost, supervision and rules of the market, the supply and demand situation, the behavior of market members. The conclusion is that the trans-provincial trading platform of East China Power Grid is a reasonable regional market which can discover the market cost, and regulate the market supply and demand balance, and promote healthy competition.

Pricing Mechanism of China’s Trans-regional and Trans-provincial Electricity Trading

With the large-scale development of Chinese electric power, the contradiction of China’s energy supply and demand that reverse distributed is very prominent, therefore, promoting electricity trading is one of the important measures to get optimized configuration of energy resources in nationwide. For the two kinds of trading method, the “power point to the grid” trading and the “grid to grid” trading, this paper designed pricing mechanism model, and took one area as an example, we analyzed the impact of the participants by using different pricing mechanism, and put forward reasonable policy proposals for China’s pricing mechanism of trans-regional and trans-provincial electricity trading.

Optimal Decision-Making of Trans-Provincial Electricity Market Subjects with Risks under Renewable Portfolio Standards

The randomness and uncertainty of renewable energy generation are expected to significantly change the optimal decision-making of trans-provincial electricity market subjects.Therefore,it is beneficial to optimize the interests of each of these subjects,considering the unpredictable risks of renewable energy under the renewable portfolio standards(RPS)and researching their effects on the optimal decision-making of transprovincial electricity market multi-subjects.First,we develop a trans-provincial trading market mechanism for renewable energy and clarify the electricity supply and demand relation and the green certificates supply and demand relation of trans-provincial electricitymarketmulti-subjects.Then,under the RPS,we construct a multi-subject game model of the power supply chain that recognizes the risks,and adopt the reverse induction method to discuss the optimum risk-taking judgment of each subject in the trans-provincial electricity market.Finally,we useMATLAB to verify the viability and efficacy of the proposed gamemodel,and obtain a certain reference value for the optimal decision-making of trans-provincial electricity market subjects.In summary,we consider the uncertainty risks of renewable energy under RPS,study the effects of the green certificate price and risk aversion coefficient in the RPS mechanism on the optimal decisionmaking of trans-provincial electricity market subjects,and obtain the changing trends of two different power products and those of different electricity market subjects under the influence of the green certificate price and risk aversion coefficient,which have a certain reference value for studying the factors affecting the optimal decision-making of trans-provincial electricity market subjects.

The Research about the Trans-provincial Centralized Bidding Trading Market of East China Power Grid --II:Model Analysis

In this paper a novel cost function based on the relationship between operation cost of unit and generation load rate is employed in an agent-based model of Trans-provincial Centralized Bidding Trading Market of East China Grid. Simulation results are compared to real data to prove that the model is correct. Further analysis on simulation results point out the way to achieve an all-win game for power market members: generation companies improve their average load rates of the units by selling their electricity in the market, which makes units' cost drop and settlement price stay lower than benchmark price. Consequently electricity-demand provinces saved expenses, and units increase their profits. In conclusion, the trans-provincial electricity market of East China Power Grid is a successive case which improves the efficiency of the electricity industry by market-oriented measures.

Decentralized control of two DC microgrids interconnected with tie-line

This paper examines the interconnection of two DC microgrids(MGs) with tie-line. The voltages at respective MG buses are controlled to manage the powerflow across the tie-line. Formation of such a DC MG cluster ensures higher reliability of power supply andflexibility to manage distributed energy resources and loads in the system. Two MGs consist of photovoltaic and battery units interfaced by power electronic converters. The bus voltages of two DC MGs act as an indicator for the powerflow monitoring the supply-demand balance. A decentralized control approach is proposed to control each MG and bus voltage fluctuation in an allowable range. Furthermore,a mode adaptive decentralized control approach is proposed for seamless mode transition in order to assign microgrid operation modes and for the power management of DC MGs. The effectiveness of the proposed concept is validated by simulation and experimental results.

Model and application of renewable energy accommodation capacity calculation considering utilization level of inter-provincial tie-line

At present, the problem of abandoning wind and PV power in “Three North” region of China is particularly significant, and how to alleviate this problem has become the focus of universal attention. Calculation of renewable energy accommodation capacity is the basis to solve the problem of abandoning wind and PV power. Main problems of Chinese renewable energy accommodation is analyzed from power supply, power grid and load side aspects, and it focuses on the effect of inter-provincial tie-line to renewable energy accommodation capacity. At present, the inter-provincial tie-line utilization level is limited, which affected renewable energy accommodation to a certain extent. Based on the sequential production simulation model, a new kind of renewable energy accommodation capacity model is put forward considering the utilization level of inter-provincial tie-line. According to different system stability constraints and different electricity constraints of inter-provincial tie-line, 4 schemes are designed for comparative analysis, and the evaluation model is used to calculate renewable energy accommodation capacity of “Three North” region of China in 2020. Example analysis results verify validity of the model that releasing curve constraints, electricity constraints and stability constraints in turn can significantly enhance renewable energy accommodation capacity through effective use of inter-provincial tie-line transmission capacity. Research work in this paper can provide strong support for the planning and scheduling control of power grid.

Tie-line Power Flow Control Method for Gridconnected Microgrids with SMES Based on Optimization and Fuzzy Logic

In an active distribution grid,renewable energy sources(RESs)such as photovoltaic(PV)and energy storage systems(e.g.,superconducting magnetic energy storage(SMES))can be combined with consumers to compose a microgrid(MG).The high penetration of PV causes high fluctuations of tie-line power flow and highly affects power system operations.This can lead to several technical problems such as voltage fluctuations and excessive power losses.In this paper,a fuzzy logic control based SMES method(FSM)and an optimized fuzzy logic control based SMES method(OFSM)are proposed for minimizing the tie-line power flow.Consequently,the fluctuations and transmission power losses are decreased.In FSM,SMES is used with a robust fuzzy logic controller(FLC)for controlling the tie-line power flow.An optimization model is employed in OFSM to simultaneously optimize the input parameters of the FLC and the reactive power of the voltage source converter(VSC)of SMES.The objective function of minimizing the tieline power flow is incorporated into the optimization model.Particle swarm optimization(PSO)algorithm is utilized to solve the optimization problem while the constraints of the utility power grid,VSC,and SMES are considered.The simulation results demonstrate the effectiveness and robustness of the proposed methods.

Simultaneous Placement of Tie-lines and Distributed Generations to Optimize Distribution System Post-outage Operations and Minimize Energy Losses

This study proposes a new method which aims to optimally install tie-lines and distributed generations simultaneously.This is done to optimize the post-outage reconfiguration and minimize energy losses and energy not supplied of distribution systems.The number and location of tie-lines,as well as the number,size,and location of DGs,are pinpointed through teaching the learning-based optimization(TLBO)method.The objective function in the current research is to minimize the costs pertaining to the investment,operation,energy losses,and energies not supplied.In addition to the normal operational condition,fault operational condition is also evaluated.Therefore,the optimal post-fault reconfigurations for fault occurrences in all lines are established.Moreover,the operational constraints such as the voltage and line current limits are taken into account in both normal and post-fault operational modes.Finally,the modified IEEE 33-bus and 69-bus distribution test systems are selected and tested to demonstrate the effectiveness of the simultaneous placement of DGs and tie-line technique proposed in this paper.

Multi-stage expansion planning of energy storage integrated soft open points considering tie-line reconstruction

With the rapid development of flexible interconnection technology in active distribution networks(ADNs),many power electronic devices have been employed to improve system operational performance.As a novel fully-con-trolled power electronic device,energy storage integrated soft open point(ESOP)is gradually replacing traditional switches.This can significantly enhance the controllability of ADNs.To facilitate the utilization of ESOP,device loca-tions and capacities should be configured optimally.Thus,this paper proposes a multi-stage expansion planning method of ESOP with the consideration of tie-line reconstruction.First,based on multi-terminal modular design characteristics,the ESOP planning model is established.A multi-stage planning framework of ESOP is then presented,in which the evolutionary relationship among different planning schemes is analyzed.Based on this framework,a multi-stage planning method of ESOP with consideration of tie-line reconstruction is subsequently proposed.Finally,case studies are conducted on a modified practical distribution network,and the cost-benefit analysis of device and multiple impact factors are given to prove the effectiveness of the proposed method.

SDN+IP视频网络与SDI矩阵的混合管控

SDN+IP视频网络系统在国内已有几个案例,与SDI矩阵共同存在于电视中心,讨论如何有效管控这两种特性迥异的技术设备,使其安全方便地应用于电视播出中心。剖析了SDN+IP的结构层次,揭示了工作机理,在应用层面探讨SDN+IP视频系统与SDI矩阵的混合架构,其中TIE-LINE的应用彻底隐去了两种技术混合组网的复杂性,使系统更安全可靠。

An Adaptive Many-objective Robust Optimization Model of Dynamic Reactive Power Sources for Voltage Stability Enhancement

The deployment of dynamic reactive power sourcecan effectively improve the voltage performance after a disturbance for a power system with increasing wind power penetration level and ubiquitous induction loads.To improve the voltage stability of the power system,this paper proposes an adaptive many-objective robust optimization model to deal with thedeployment issue of dynamic reactive power sources.Firstly,two metrics are adopted to assess the voltage stability of the system at two different stages,and one metric is proposed to assess the tie-line reactive power flow.Then,a robustness index isdeveloped to assess the sensitivity of a solution when subjectedto operational uncertainties,using the estimation of acceptablesensitivity region(ASR)and D-vine Copula.Five objectives areoptimized simultaneously:①total equipment investment;②adaptive short-term voltage stability evaluation;③tie-line power flow evaluation;④prioritized steady-state voltage stabilityevaluation;and⑤robustness evaluation.Finally,an anglebased adaptive many-objective evolutionary algorithm(MaOEA)is developed with two improvements designed for the application in a practical engineering problem:①adaptive mutationrate;and②elimination procedure without a requirement for athreshold value.The proposed model is verified on a modifiedNordic 74-bus system and a real-world power system.Numerical results demonstrate the effectiveness and efficiency of theproposed model.

Automatic Generation Control of Multi-area Power System with Network Constraints and Communication Delays

Newly proposed power system control methodologies combine economic dispatch(ED) and automatic generation control(AGC) to achieve the steady-state cost-optimal solution under stochastic operation conditions. However, a real power system is subjected to continuous demand disturbance and system constraints due to the input saturation, communication delays and unmeasurable feed-forward load disturbances. Therefore, optimizing the dynamic response under practical conditions is equally important. This paper proposes a state constrained distributed model predictive control(SCDMPC)scheme for the optimal frequency regulation of an interconnected power system under actual operation conditions, which exist due to the governor saturation, generation rate constraints(GRCs), communication delays, and unmeasured feed-forward load disturbances. In addition, it proposes an algorithm to handle the solution infeasibility within the SCDMPC scheme, when the input and state constraints are conflicting. The proposed SCDMPC scheme is then tested with numerical studies on a three-area interconnected network. The results show that the proposed scheme gives better control and cost performance for both steady state and dynamic state in comparison to the traditional distributed model predictive control(MPC) schemes.

Single and multi-area multi-fuel economic dispatch using a fuzzified squirrel search algorithm

Multi-Area Multi-Fuel Economic Dispatch (MAMFED) aims to allocate the best generation schedule in each area and to offer the best power transfers between different areas by minimizing the objective functions among the available fuel alternatives for each unit while satisfying various constraints in power systems. In this paper, a Fuzzified Squirrel Search Algorithm (FSSA) algorithm is proposed to solve the single-area multi-fuel economic dispatch (SAMFED) and MAMFED problems. Squirrel Search Algorithm (SSA) mimics the foraging behavior of squirrels based on the dynamic jumping and gliding strategies. In the SSA approach, predator presence behavior and a seasonal monitoring condition are employed to increase the search ability of the algorithm, and to balance the exploitation and exploration. The suggested approach considers the line losses, valve point loading impacts, multi-fuel alternatives, and tie-line limits of the power system. Because of the contradicting nature of fuel cost and pollutant emission objectives, weighted sum approach and price penalty factor are used to transfer the bi-objective function into a single objective function. Furthermore, a fuzzy decision strategy is introduced to find one of the Pareto optimal fronts as the best compromised solution. The feasibility of the FSSA is tested on a three-area test system for both the SAMFED and MAMFED problems. The results of FSSA approach are compared with other heuristic approaches in the literature. Multi-objective performance indicators such as generational distance, spacing metric and ratio of non-dominated individuals are evaluated to validate the effectiveness of FSSA. The results divulge that the FSSA is a promising approach to solve the SAMFED and MAMFED problems while providing a better compromise solution in comparison with other heuristic approaches.