With the rapid development of new energy generation technology, the pressure of new energy consumption in the power grid is increasingly prominent. At the same time, with the development of multi-energy conversion technology, the degree of coupling between power grids and other types of energy networks is increasing. How to use the flexibility resources of different energy networks to dissipate the blocked new energy has become an urgent issue to be studied. This paper proposes a multi-timescale trading strategy that takes into account the multi-energy demand response to participate in the consumption of blocked new energy sources. First, a multi-type demand response model for cold, heat and electric loads is established with full consideration of the characteristics of integrated energy system (IES). Secondly, a price-based integrated demand response (IDR) day-ahead optimal scheduling model based on master-slave game theory is established in the day-ahead time scale, considering the equilibrium of interests of all parties in the process of new energy consumption. At the intra-day time scale, an incentive-based IDR intra-day rolling optimization scheduling model is developed to address the impact of the deviation from the new energy day-ahead forecast on system optimization.
Finally, the effectiveness of the strategy proposed in this paper is verified by case simulation. This work is supported by National Key R&D Program of China (No. 2018YFE0208400).
With the improvement of the interconnection of power grid, resisting the cascading faults becomes a key problem. In a certain scenario, the key current-carrying branch accidents of power grid will lead to overload cascading faults, threatening the safe operation of the system, which is of great significance to the screening and identification of such critical lines. On the basis of improving the DC power flow model of reactive voltage, the dynamic evolution model of overload-type cascading faults is deduced and constructed. The model takes into account the adjusting effects of power balance and voltage stability devices and the corrective control measures of the system, and accurately simulates the dynamic evolution of the cascading faults of the interconnected system after branch failures, so as to analyze the influence of cascading faults on the system function and structure. On this basis, the importance evaluation index of current-carrying branches of power grid is proposed, and the importance index of each current-carrying branch is obtained through large-scale cascading fault simulation calculation, and finally the effective identification of key branches of power grid is realized. Taking the IEEE 39-bus system as an example, the effectiveness of the proposed model and method is verified.
This work is supported by National Key R&D Program of China (No. 2018YFE0208400) and Shandong Provincial Natural Science Foundation(No.ZR2020ME195).
In view of the demand of offshore oil and gas engineering for the stability of energy supply, many energy supply systems coordinated by offshore generator units and onshore power grid have been established one after another. The establishment of a coordinated and optimized operation mode of offshore generator units and onshore power grid can improve the reliability of energy supply and reduce carbon emissions. Therefore, this paper proposes an energy-reserve cooperative optimal scheduling model of offshore multi-platform and onshore power grid energy supply system. At the same time, to cope with the independence between the offshore multi-platform energy supply system and the onshore power system, a distributed solution framework of the cooperative dispatch model is proposed on the basis of alternating direction method of multiplier (ADMM). In order to ensure the convergence of the distributed solution algorithm, the second-order cone relaxation technology is used to relax the power flow constraints of offshore platform, and the model is transformed into a convex optimization model. The results of the numerical example show that, the cooperative energy supply system with offshore multi-platform and onshore power grid can effectively promote the consumption of renewable energy while protecting the information privacy of shore power system and offshore platforms.
This work is supported by National Key Research and Development Program of China(No. 2018YFB0904800)and Research Project of CNOOC Limited: Research and Demonstration of Key Technologies about Shore Power System in Bohai Oil and Gas Field (Phase One) (No.YXKY-ZX 06 2020).
The randomness and anti-peak shaving characteristics of wind and solar output make it more difficult for the power grid to absorb renewable generation. Using the flexible and adjustable characteristics of the source side and the load side, the bilateral participation rules of source and load are designed to guide the source and load to carry out bidirectional power coordination across time to support the efficient consumption of renewable energy. First, the basic rules and principles of bilateral participation of the source-load are sorted out, transaction subjects, varieties and models are clarified, and their participation rules are designed. Secondly, according to the bilateral participation rules of source and load, a joint optimal dispatch model of day-ahead energy and reserve is constructed taking into account the bilateral participation of source-load, so as to help the consumption of renewable energy and reduce the electricity cost of industrial users. Thirdly, to solve the problem of multi-scenario mixed integer programming, an improved progressive hedging decomposition algorithm is used to solve the problem, and the convergence of the model is ensured through the heuristic variable "fix-screen-relax". Finally, an example analysis is carried out on the basis of the IEEE 118-node system, which verifies the effectiveness of the proposed joint clearing model of energy and reserve in promoting energy consumption.
This work is supported by National Key R&D Program of China (No. 2018YFB0905200) and State Grid Corporation of China Research Program (No. SGNW0000DKJS2100269).
The extreme weather caused by climate change will have large impact on building load and energy supply strategy of combined cooling, heating and power (CCHP) system. Firstly, taking a hospital in Shanghai as the main research object, the regional climate model (PRECIS) is used to predict the temperature change of the area in the future to 2100. Secondly, the TRNSYS software is utilized to build energy consumption model of the hospital for calculating the annual hourly load under climate change. Next, the operation optimization model of CCHP system with the consideration of load variation is formulated. Finally, the operation scheme of the energy supply system adapting to climate change is generated. Load-prediction results demonstrated that the fluctuation variation trend of the cooling and heating load of targeted building caused by the extreme high temperature might lead to the imbalance between energy provision and requirement, e.g., the insufficient cold supply under the hot summer and the excessive heat supply under the warm winter. Compared with the traditional optimization model, the coordinated operation scheme generated by proposed model is capable of enhancing the user experience, reducing the cost and increasing the benefit.
This work is supported by National Key R&D Program of China (No. 2018YFE0208400).
The uncertainty of the electricity purchase and sale sides is the key factor restricting the operation of the electricity sales company. This paper uses the third-party insurance mechanism to avoid market fluctuations and demand response to improve returns, and puts forward an optimized operation model for electricity sales companies under the spot market. Firstly, the deviation assessment model and premium model are established, the deviation assessment model of the user limit penalty mechanism and demand response contract on the user utility in the bilateral long association contract are quantified, and the optimal operation model is verified with the data of local users. The example results show that the electricity sales company can guide the users to respond positively through the stepped demand response incentive mechanism; the introduced insurance mechanism can effectively disperse and transfer the risk of electricity fluctuation, and realize the win-win value between the electricity sales company and the users.
This work is supported by National Natural Science Foundation of China(No. 52077146).
The implementation of peak-valley time-of-use (TOU) price strategy can effectively reduce the peak-valley difference of load and save investment for power grid, but the load characteristics in different seasons are quite different, which affects the formulation of the optimal peak-valley TOU price strategy. Therefore, this paper mainly studies the peak-valley TOU price pricing strategy and period partitioning model considering multiple seasonal characteristics. Firstly, the demand response architecture proposed in this paper is described in combination with the main innovations of this paper. Secondly, the k-means method is adopted to obtain the load curve of typical days in each season, and the improved moving boundary technology is adopted to partition the load curve of typical days in each season. The optimization model for peak-valley period partitioning is established by setting the period partitioning constraint factors and adopting the Davies-Bouldin index (DBI) as the objective function. Then, the price elasticity of demand considering seasonal characteristics and the pea-valley TOU price optimization model considering multiple seasonal characteristics are established, and the particle swarm optimization (PSO) algorithm is used to solve the model. RTS is used to verify and analyze the algorithm and model, which verifies the effectiveness and correctness of the method and model proposed in this paper.
This work is supported by Natural Science Foundation of Anhui Province (No. 2108085UD08) and Fundamental Research Funds for the Central Universities (No. PA2021KCPY0053).
The transient overvoltage caused by the DC blocking fault of the UHVDC transmission system and the short-circuit fault of the AC system has a serious impact on the stability of the system. Quantitative assessment of the transient performance index has important guiding significance for the dispatching operation of AC/DC power system. This paper analyzes the mechanism of transient overvoltage in AC system, deduces the calculation method of transient overvoltage on the basis of reactive power compensation and short-circuit ratio, and then defines the transient voltage evaluation index Rr. Research shows that, as the index Rr decreases, the transient voltage of the commutation bus at the sending end will increase after a system fault, and commutation failures will also occur at the receiving end. Finally, on the basis of the CIGRE benchmark HVDC standard test system, the effectiveness of the proposed index Rr is verified.
This work is supported by State Grid Science and Technology Project (No. 5230HQ21000S).
In order to reduce the risk of subsequent commutation failure in HVDC transmission system, the commutation failure mechanism is analyzed, and combined with symmetrical and asymmetric fault detectors, an improved scheme of current deviation control which can be adjusted according to the severity of fault is proposed. The suppression effect of the slope of current deviation control on commutation failure is analyzed. It is found that the larger the slope of slope function in current deviation control is, the more sensitive it is to input current deviation, and the larger the commutation margin increment is, the more conducive it is to suppress subsequent commutation failure. Finally, the proposed control scheme is realized on the basis of CIGRE HVDC Standard Test System in PSCAD / EMTDC simulation software. The simulation results show that the current deviation control method proposed in this paper can effectively reduce the risk of subsequent commutation failure of HVDC system and improve the operation characteristics of HVDC system.
This work is supported by State Grid Corporation of China Research Program (No.52130420001S).
In order to enhance the business support ability and save economic cost of power distribution internet of things, this paper proposes an optimal deployment method of the distribution edge computing terminals for software defined network (SDN). Base stations of power wireless private network are rich in data flow and service flow. Using the location of wireless base stations to deploy distribution edge computing terminals has significant advantages. This paper introduces the edge computing architecture of power distribution internet of things for software defined network, and establishes the models of business, intelligent terminal and edge computing terminal. Further, considering the communication mode constraints of edge computing terminal, intelligent terminal and SDN controller, and the constraints of service delay and hardware configuration of edge computing terminal, aiming at the sum of annual average equipment cost and annual average operation cost, this paper establishes an optimal deployment model of distribution edge computing terminals. Finally, the effectiveness of the proposed method is verified by the simulation results of a multi-scenario example.
This work is supported by the Key Research and Development Program of Guangdong Province (No. 2019B111109002).
With the normalization of unmanned aerial vehicle (UAV) inspection of transmission lines, the problems of real-time detection of fault images and accuracy of blurred target detection are difficult to meet the actual work requirements. This paper proposes a real-time detection method for transmission line faults, which is based on edge computing and improved YOLOv5s algorithm. This method is based on YOLOv5s model, and the model is reconstructed on the basis of Ghost lightweight module to realize the convolution operation process of obtaining data features, which improves the detection speed of the model. The loss function based on KL (Kullback-Leibler) divergence distribution is used as the target box localization loss function to improve the accuracy of blurred image detection. The improved YOLOv5s algorithm is deployed in the Huawei Atlas 200 DK edge module to detect three types of faults: insulator self-explosion, shock hammer falling-off, and bird’s nest. The mAP can reach 84.75%, and the detection speed is 34 frame/s. The results show that the improved algorithm can improve the detection accuracy of blurred fault target images while ensuring the real-time detection, and meet the inspection requirements of transmission lines equipped with edge devices by UAV.
This work is supported by National Natural Science Foundation of China (No. 52007103) and Major Science and Technology Projects in Hubei Province of China (No. 2020AEA012).
In order to solve the problems of low detection efficiency of existing channel hidden danger detection methods of transmission line GIM (grid information model) model and missing detection of optimization algorithm, a fast detection method of channel hidden danger, which is based on the principle of equal line length point aggregation and sphere inclusion, is proposed. Firstly, according to the equal line length interval sampling, the conductor is transformed from the spatial curve to the discrete point set, so that the discrete point set is evenly distributed on the power line, so as to solve the problem of uneven distribution of discrete point set and poor accuracy of special gear in the traditional equal level interval sampling method; Secondly, in the process of batch point hidden danger detection, the sphere inclusion principle is introduced to judge the potential hidden dangers of ground objects, and the adjacent point search calculation is skipped for the ground objects that do not have the potential hidden dangers, so as to realize the rapid detection of channel hidden dangers. Experiments show that this method can ensure the distribution of sampling points in both ordinary and special gears, and control the positioning tolerance of the nearest point within the target range; In terms of detection efficiency, the hidden danger detection time can be optimized to 6.9% of the original time on the premise of ensuring the detection accuracy.
This work is supported by State Grid Corporation of China Research Program(No. 5700-202156170A-0-0-00).
The operation mode of gas turbine (GT) in the traditional combined heat and power dispatching greatly limits the peak-shaving capability of the system. A method for optimal dispatch of concentrating solar power (CSP) station participation in heating is proposed. The thermal inertia of the heating network and heating area in the scheduling process is considered. First, a model for the CSP station to participate in the electric heating combined system regulation is built to enhance the peak-regulation capability of the source-side gas turbine unit. Secondly, the thermal inertia model of the heating network and building clusters is constructed, the potential of virtual energy storage is tapped, and the coordinated and optimized operation of the two types of thermal inertia and the CSP station is realized under the conditions of satisfying various constraints. Five comparison scenarios are constructed in the simulation analysis to verify the effectiveness of the coordination between the thermal inertia of the heating network and heating area and the heat storage system of the CSP station in improving the operating economy of the system, improving the efficiency of wind power and reducing the carbon emissions of the system.
This work is supported by National Natural Science Foundation of China (No. 52007103).
Aiming at the problem that the individual rationality of the agent in the integrated energy system is not fully considered, and the power system pays more and more attention to the consumption of renewable energy and the reduction of carbon emissions, this paper proposes an optimal operation strategy of wind-solar-CHP multi-agent energy system considering the bargaining power. In this paper, the integrated energy system is divided into wind, photovoltaic and CHP agents, and their cooperative operation model is constructed, and hydrogen production technology and ladder-type carbon trading mechanism are added to the CHP agent. Then, according to Nash bargaining theory, a wind-solar-CHP multi-agent cooperative operation model is established. Due to the nonconvexity of the proposed cooperative operation model, it is decomposed into the system operation cost minimization problem (P1) and the transaction payment problem (P2). In P2, a bargaining power model considering economic and environmental gains is proposed. Each agent realizes the fair distribution of income according to its own bargaining power. Finally, in order to protect the privacy of cooperation, the alternating direction method of multiplier (ADMM) is used to solve P1 and P2. The results show that the optimal operation strategy of wind-solar-CHP considering bargaining power can not only realize the fair distribution of cooperative benefits, but also effectively alleviate the problems of wind curtailment, solar power curtailment and carbon emissions. In addition, the power-to-hydrogen technology can better promote the low-carbon economic operation of the system than the power-to-gas technology.
This work is supported by Natural Science Foundation of Shandong Province (No. ZR2020QE215).
