The progressing energy transition induces a growing need for redispatch congestion management, and, thereby, a fair distribution of its respective costs among the different system operators. In this light, a very rece...
详细信息
ISBN:
(纸本)9798400700323
The progressing energy transition induces a growing need for redispatch congestion management, and, thereby, a fair distribution of its respective costs among the different system operators. In this light, a very recent paper uses the Shapley value as such a fair allocation rule to assign redispatch congestion costs to system operators. However, this approach is based on DC optimal power flow (OPF) and requires the sharing of detailed grid models from all system operators. This is not preferred by them due to data privacy concerns. W.r.t. real-world implementation, the present paper extends the method by using AC OPF problem formulations for more realistic results, and solving them by using a distributed optimization algorithm, i.e., Augmented Lagrangian based Alternating Direction Inexact Newton method (aladin), for preserving data privacy. Simulation results of an illustrative example show great potential of the proposed distributed approach in the aspects of both solution accuracy and computing time. This makes the presented approach generically feasible for real applications in the energy transition.
Although the AC optimal power flow (OPF) has shown great potential for operating distribution networks, its formulation as a single problem might not be scalable (solvable fast enough to be relevant). This is exacerba...
详细信息
ISBN:
(纸本)9781728185507
Although the AC optimal power flow (OPF) has shown great potential for operating distribution networks, its formulation as a single problem might not be scalable (solvable fast enough to be relevant). This is exacerbated by the added complexity when multiple voltage levels and the unbalanced nature of distribution networks are considered. distributed solution algorithms can help by breaking down a single OPF problem into multiple smaller problems. This paper explores the use of a three-phase AC OPF, solved in a distributed fashion by adopting the alternating direction method of multipliers (ADMM) algorithm, to manage residential PV systems in MV-LV distribution networks. The performance of the ADMM-based OPF is assessed using a test MV-LV feeder and compared with the conventional approach (solved as a single problem). Results show that the proposed algorithm is accurate, suggesting it has the potential to outperform the conventional approach when handling large-scale distribution networks.
A predictable distributedalgorithm is proposed to solve the stochastic energy management problem of a microgrid system with renewable energy under real-time price schemes. System uncertainties, including wind power a...
详细信息
ISBN:
(纸本)9789881563804
A predictable distributedalgorithm is proposed to solve the stochastic energy management problem of a microgrid system with renewable energy under real-time price schemes. System uncertainties, including wind power and load, are modeled as two-dimension policy-based structure to response from the deviation of the realized and expectation value. Due to the randomness of the uncertainties, a chance constraint on energy balance is considered which allows the mismatch of supply and demand to fluctuate in an acceptable range. The numerical experiments are provided and the effectiveness of the proposed algorithm is analyzed. According to the simulation results, the probabilistic energy balance is guaranteed and the proposed algorithm with two-dimension model has better economic performance or shorter operation time comparing to other algorithms.
The increase in the penetration rate of distributed renewable energy sources has brought unprecedented challenges to the economic and stable operation of the active distribution network (ADN). To improve the operating...
详细信息
The increase in the penetration rate of distributed renewable energy sources has brought unprecedented challenges to the economic and stable operation of the active distribution network (ADN). To improve the operating efficiency and total benefits of the ADN, it is necessary to establish an optimization model considering the stakeholders' market behavior and the game relationship among them under the market environment. In this paper, a multi-stakeholder potential game model in the ADN considering the bounded rationality of small users is proposed. The game relationships among five stakeholders, including the distributed photovoltaic generation aggregators, the distributed wind power aggregators, the energy storage operators, the large users and the load aggregators, are modeled on an hourly time scale. Existing research has proved that the game equilibrium of the potential game model must exist. Based on the information transfer and the strategy update mode on the social network, a demand response evolutionary game model for small users is established. Moreover, a distributedalgorithm is designed to obtain the pure strategy equilibrium. Finally, a case with five stakeholders and 160 small users is used to verify the rationality and feasibility of the proposed model.
The virtual power plants are aggregations of distributed generators, grid -connected devices in user side. The operation of virtual power plants affects the economic benefits and environmental benefits. However, due t...
详细信息
The virtual power plants are aggregations of distributed generators, grid -connected devices in user side. The operation of virtual power plants affects the economic benefits and environmental benefits. However, due to the stochastic and fluctuating nature of power generation from renewable energy sources, the optimal scheduling problem for the virtual power plant containing high -dimensional random variables is difficult to solve. The conic power flow constraints are considered in the virtual power plant day -ahead optimal scheduling models to maximize the revenue by virtue of optimizing the flexible resources such as energy storage system and interruptible load. To quantify the uncertainties in the optimization problem, this paper proposes a network statebased power scenario reduction strategy for renewable energy generation, where typical scenarios are selected by the state of the grid voltage. The proposed day -ahead scheduling model is a mixed -integer, nonlinear, large-scale, stochastic optimization problem with high dimensional random variables, which is difficult to be solved directly by traditional centralized method. By temporally decoupling the charging and discharging model of energy storage systems, a distributed optimization algorithm is proposed based on multi -temporal power flow decoupling optimization model. The simulation results show that the proposed distributed optimization algorithm has high accuracy and good convergence, the virtual power plant can achieve day -ahead optimal scheduling and effectively promote renewable energy accommodation under the security and reliability of the grid.
A predictable distributedalgorithm is proposed to solve the stochastic energy management problem of a microgrid system with renewable energy under real-time price schemes. System uncertainties, including wind power a...
详细信息
A predictable distributedalgorithm is proposed to solve the stochastic energy management problem of a microgrid system with renewable energy under real-time price schemes. System uncertainties, including wind power and load, are modeled as two-dimension policy-based structure to response from the deviation of the realized and expectation value. Due to the randomness of the uncertainties, a chance constraint on energy balance is considered which allows the mismatch of supply and demand to fluctuate in an acceptable range. The numerical experiments are provided and the effectiveness of the proposed algorithm is analyzed. According to the simulation results, the probabilistic energy balance is guaranteed and the proposed algorithm with two-dimension model has better economic performance or shorter operation time comparing to other algorithms.
暂无评论