Stochastic unit commitment is one of the most powerful methods to address uncertainty.However, the existing scenario clustering technique for stochastic unit commitment cannot accurately select representative scenarios, which threatens the robustness of stochastic unit commitment and hinders its application.This paper provides a stochastic unit commitment with dynamic scenario clustering based on multi-parametric programming and Benders decomposition.The stochastic unit commitment is solved via the Benders decomposition, which decouples the primal problem into the master problem and two types of subproblems.In the master problem, the committed generator is determined, while the feasibility and optimality of generator output are checked in these two subproblems.Scenarios are dynamically clustered during the subproblem solution process through the multiparametric programming with respect to the solution of the master problem.In other words, multiple scenarios are clustered into several representative scenarios after the subproblem is solved, and the Benders cut obtained by the representative scenario is generated for the master problem.Different from the conventional stochastic unit commitment, the proposed approach integrates scenario clustering into the Benders decomposition solution process.Such a clustering approach could accurately cluster representative scenarios that have impacts on the unit commitment.The proposed method is tested on a 6-bus system and the modified IEEE 118-bus system.Numerical results illustrate the effectiveness of the proposed method in clustering scenarios.Compared with the conventional clustering method, the proposed method can accurately select representative scenarios while mitigating computational burden, thus guaranteeing the robustness of unit commitment.
With the integration of renewable energy, the power system faces new challenges such as increasing uncertainty and changing system operation mode. It is necessary to improve the computational efficiency of the unit commitment in the power system for real application. A transmission-constrained unit commitment model is proposed in this paper and the identification and elimination approach of the non-risky redundant transmission constraints is used to reduce the model scale of the transmission-constrained unit commitment problem. To validate the effectiveness and practicability of the identification and eliminating approach, a modified IEEE-118 case has been conducted.
As an important part of energy Internet carrier, demand side resources can participate in many interactions with power grid. In order to reduce the peak to valley load difference of power grid, from the perspective of tapping the combined peak shaving potential of air conditioning load and electric vehicles, guided by TOU price and direct load control, this paper proposes an optimal scheduling model with the minimum load difference and the maximum total revenue of users as the objective function. The results show that the joint optimal scheduling strategy can reduce the peak load and eliminate the “secondary peak load” caused by disorderly charging of electric vehicles.
There is a shortage of power supply in multi provincial power grid during peak load period. The response speed of interruptible load is fast, and it has the same excellent regulation performance as the standby on the generation side, which can meet the needs of fast transfer. Aiming at the situation of interruptible load participating in the joint market under the bilateral mode, this paper designs the joint clearing process of electric energy and reserve market considering interruptible load, and establishes the joint clearing model considering interruptible load participating in electric energy and reserve market with the goal of maximizing social welfare. Simulation results verify the effectiveness of the proposed model.
The existing research on orderly participation of air conditioning load in frequency regulation needs a relatively complete communication architecture, but it cannot be achieved on a large scale in practice. This paper proposes a decentralized control method for the air-conditioning load control to participate in the power system primary frequency regulation, so that the air-conditioning loads can respond to system frequency deviation in an orderly manner without communication. Firstly, the triggering frequency is set to prevent the air-conditioning load from being over- or under-adjusted based on the frequency response interval, which is determined according to the outdoor temperature. Secondly, the response priority is arranged according to the holding time to ensure an orderly response of the air-conditioning load without communication. Finally, a simulation example of a thousand air-conditioning loads under different control strategy proves that the proposed method can achieve better frequency regulation effect.
There are differences in resource distribution and power consumption among provinces in the regional power grid. To carry out trans-provincial peak-shaving auxiliary service market transactions can realize the cross-provincial mutual benefit of peak-shaving resources, thereby enhancing the capacity of regional power grid to absorb renewable energy. Based on the above concepts, aiming at the problem of insufficient peak-shaving resources in the provincial power grids, this paper puts forward the trading mechanism and security checking mechanism of trans-provincial peak-shaving auxiliary service. A market clearing pricing model for peak-shaving auxiliary service in low-load periods is constructed to motivate relevant units to provide peak-shaving auxiliary service with clear price signals. A simplified model of a regional power grid is simulated and analyzed. The results show that the trading mechanism and safety checking mechanism proposed in this paper are feasible and effective.
To accommodate more renewable energy sources, this paper proposes a strategy to incorporate renewable energy sources in operational reserve when unit commitment. Specifically, this paper analysis the prediction error of renewable energy sources, further incorporates them in operational reserve with reliability satisfied, and eventually operates unit commitment with such renewable energy sources included in operational reserve. To demonstrate the benefits of incorporating renewable energy sources in operational reserve, a modified IEEE-118 case its corresponding comparison results have been conducted.
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