As traditional fossil energy sources such as coal cause serious environmental pollution, it is a major trend to promote the construction of a 'clean' power system with new energy sources as the mainstay. Howev...
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As traditional fossil energy sources such as coal cause serious environmental pollution, it is a major trend to promote the construction of a 'clean' power system with new energy sources as the mainstay. However, the uncertainty of intermittent energy output and its high proportion of grid connection bring challenges to the scheduling operation of the power system. In this paper, the authors propose a two-stage robust dispatching strategy for the combined wind-photovoltaic-fired-pumped storage system to improve the capacity of renewable energy (RER). The outer layer of the model is based on minimizing the start-stop cost of thermal power units to obtain the start-stop scheme of thermal power units, and the inner layer of the model integrates the system operation cost, pollutant emission cost, deviation penalty, and other constraints of wind power and PV output to obtain the dispatching scheme with the lowest overall operation cost under the worst scenario of wind power and PV fluctuation. The model is solved alternatively by column constraint generation algorithm (C&CG) and strong pairwise theory. The feasibility and effectiveness of the proposed method was verified based on the improved 30-machine test system as an example.
With the increasing energy crisis and environmental pollution, renewable energy sources, such as wind power and photovoltaics, are widely utilized in distribution networks. Moreover, to achieve the "Dual Carbon&q...
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ISBN:
(纸本)9798350375794;9798350375800
With the increasing energy crisis and environmental pollution, renewable energy sources, such as wind power and photovoltaics, are widely utilized in distribution networks. Moreover, to achieve the "Dual Carbon" goal as soon as possible, active distribution networks are gradually becoming the main development direction of distribution networks. However, the natural strong uncertainty of wind and solar power poses great challenges to the economic operation of active distribution networks. Therefore, this article presents a two-stage adjustable robust optimization model for active distribution networks, aimed at achieving economic dispatch of active distribution networks under the uncertain wind and solar prediction error. Firstly, in the day-ahead stage, assuming no error in wind and solar forecast, the initial day-ahead scheduling strategy is obtained. Subsequently, if there is a deviation between the actual output of the renewable energy sources and the previous predicted value, intraday adjustments will be made in the second stage. For the convenience of solving, the column constraint generation algorithm is utilized to decompose the complex min-max-min model, and the model is linearized by dual theory, Big-M method, and second-order cone relaxation method. The calculation results show that the method proposed in this article can effectively reduce system operating costs, improve wind and solar energy consumption rate, and achieve a reasonable balance between robustness and economy.
Introduction: In recent years, with the rapid development of renewable energy generation, the stability of the power grid has been greatly reduced. In response to this problem, integrating the user side transferable l...
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Introduction: In recent years, with the rapid development of renewable energy generation, the stability of the power grid has been greatly reduced. In response to this problem, integrating the user side transferable load into the power market has become the key to the development of future power grid. At present, large transferable loads have entered the electricity market in some pilot areas of China, but the relevant research on small and medium-sized transferable users entering the electricity market is still ***: This paper proposes the concept of generation load aggregators. A two-stage generation load aggregator robust optimization model is developed to obtain the scheduling scheme with the lowest operating cost under the worst scenario. The model consists of distributed renewable power, transferable load, self-provided power, energy storage, etc. Uncertainties of renewable energy and load are introduced in the model. By using the column constraint generation algorithm and strong pairwise theory, the original problem is decomposed into the main problem and sub-problems to be solved alternately, so as to obtain the scheduling scheme with the lowest operating cost in the worst scenario under different ***: The solved results are compared with those without the generation load aggregator, illustrating the role of the generation load aggregator in relieving peak and valley pressure on the grid from the load side, reducing the cost of electricity for loads, and promoting the consumption of renewable energy. The comparison with the deterministic optimization algorithm shows a significant decrease in the total cost and validates the performance of the selected solution algorithm. The boundary conditions for the use of energy storage by generation load aggregators for peak and valley reduction under the time-sharing tariff mechanism are also ***: This study can provide reference for the investors of generation load aggregators w
Hybrid AC/DC distribution networks with the high-efficiency consumption and high-proportion access of new energy have become a crucial trend for future modern distribution networks. High penetration of renewable energ...
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Hybrid AC/DC distribution networks with the high-efficiency consumption and high-proportion access of new energy have become a crucial trend for future modern distribution networks. High penetration of renewable energy brings various controllable resources along with uncertainties to hybrid AC/DC distribution networks, making conventional single objective optimization fail to meet optimal operation requirements of flexibility and reliability. In this paper, considering uncertainties of distribution generations and loads, a multi-objective robust optimization model based on various controllable devices is proposed. To increase resource utilization, the proposed method comprehensively and properly models the full variety of possible control means (i.e., flexible distribution switch, voltage source converter, energy storages, et al). Utilizing the abundant control means, a multi-objective optimization which minimizes network losses, voltage deviations and operation cost simultaneously is modeled. Then, based on the multi-objective model, a two-stage robust optimization based on second order cone method and column constraint generation algorithm is proposed to achieve the solution, which can deal with the fluctuation of loads and renewable energy quickly and effectively. Outdoing traditional single objective robust optimization, our multi-objective robust optimization based on various controllable resources can decease the network losses, increase the profits and improve voltage profiles significantly, which obviously improves the safety, flexibility and economy simultaneously. Finally, compared with existing robust optimization, the proposed method is tested in numerous case studies to verify its effectiveness and advantages in a modified IEEE 33-node system.
Micro-energy grid for CCHP users can make full use of local renewable energy and integrated demand response (IDR) resources to meet the electric, cooling, heating and other load demands in electricity market. In this ...
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Micro-energy grid for CCHP users can make full use of local renewable energy and integrated demand response (IDR) resources to meet the electric, cooling, heating and other load demands in electricity market. In this paper, aiming at the uncertainties of renewable energy output and electric, cooling and heating load in micro-energy grid, a mode of IDR resources flexibly participating in day-ahead scheduling and intra-day real-time regulation stage in micro-energy grid is established, and a two-stage robust scheduling optimization model with IDR considered is constructed. In the model, the cost and constraints of IDR resources participating in two-stages is considered, and the uncertain budget parameter is introduced for regulating economy and robustness of the system. In day-ahead stage, the day-ahead scheduling cost is taken as the goal to determine the output of each unit, energy storage and IDR resource response mode. Based on the optimization results of day-ahead stage, each regulation quantity of the system is determined with the goal of minimizing the real-time regulation cost within a day. Strong duality theory and column constraint generation algorithm is used to transform and solve the robust optimization problem of min-max-min structure. The results show that the robust optimization model can improve the system's ability to resist uncertain risks, and the integrated demand response can improve the economy of the robust optimization model and the self-sufficiency of micro-energy grid.
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