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...
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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.
The economic dispatch problem (EDP) in power systems is usually formulated as a category of convex optimization problems in which the collective cost function is expressed as the sum of all individual objectives of ge...
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The economic dispatch problem (EDP) in power systems is usually formulated as a category of convex optimization problems in which the collective cost function is expressed as the sum of all individual objectives of generators. It is inclined to be solved through a distributed way, which is to minimize the total generation cost while meet the demands under generator capability restrictions. In this paper, we consider this class of convex optimization problems that involve coupling linear constraint and individual box constraints. In order to make information communication of network decentralized, reliable and computationally inexpensive, an asynchronous distributed primal-dual optimizationalgorithm is proposed over stochastic networks. This algorithm allows nodes to use asynchronous communication strategy to update their state, and the step-sizes for seeking the optimum solution are uncoordinated constants. The asynchronous operation for generators takes link failures of networks into account. Under strongly convex assumption on objective functions, it is proved that the proposed algorithm can seek the exact optimal solution with probability one if the expectation of communication network is undirected connected. The effectiveness of the proposed optimizationalgorithm over stochastic networks is illustrated by provided simulation results.
The operation of MV-LV networks with high penetrations of residential PV systems will require the active management of PV settings (curtailment). The conventional three-phase AC optimal power flow (OPF) has shown grea...
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ISBN:
(纸本)9781665435970
The operation of MV-LV networks with high penetrations of residential PV systems will require the active management of PV settings (curtailment). The conventional three-phase AC optimal power flow (OPF) has shown great potential, however, its formulation as a single problem might not be scalable (i.e., solvable fast enough to be relevant). The added complexity due to multiple voltage levels and unbalance can further exacerbate this. An alternative is to break down the single OPF problem into multiple smaller subproblems but considering the interactions at their interfaces. Here, the distributed optimization algorithm alternating direction method of multipliers (ADMM) is adopted to solve a three-phase AC OPF that calculates PV settings in MV-LV networks to avoid voltage and congestion problems. Its performance is assessed for different numbers of LV networks (subproblems). Results show that the proposed algorithm is not only accurate but much faster than the conventional approach for large 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...
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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...
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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.
By using combined tools from smooth approximation technique and exact penalty method, a smooth distributed continuous-time algorithm is designed in this paper to solve a kind of convex problem in multi-agent networks ...
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ISBN:
(纸本)9781728111643
By using combined tools from smooth approximation technique and exact penalty method, a smooth distributed continuous-time algorithm is designed in this paper to solve a kind of convex problem in multi-agent networks with undirected topology. One of the remarkable features of this paper lies in the fact that a convergence rate O ( 1=t(2)) could be yielded by using the proposed distributedalgorithm if, some suitable conditions are satisfied. Specifically, by using the smooth approximation method, a kind of distributedalgorithm is proposed to deal with the optimization problem with non-smooth cost functions or cost functions having nonLipschitz gradient. The asymptotic convergence property and the convergence rate of the proposed distributedalgorithm are analyzed under certain mild conditions. A numerical simulation is conducted to validate the effectiveness of the theoretical analysis.
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...
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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...
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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.
Economic dispatch problem (EDP) is one of the fundamental optimization problems in power systems, which involves a coupling linear constraint and several individual box constraints. In this paper, we propose a distrib...
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Economic dispatch problem (EDP) is one of the fundamental optimization problems in power systems, which involves a coupling linear constraint and several individual box constraints. In this paper, we propose a distributed stochastic gradient descent algorithm based on consensus theory to solve the EDP under directed network, where the convex cost function for each generator only needs to satisfy the condition that the function is strictly convex with Lipschitz continuous gradient. The proposed algorithm utilizes stochastic gradient descent to update values of generators for dealing with the noise which is incurred during the gradient estimation, and the step-sizes are heterogeneous. Under strictly convex assumption on objective functions, the algorithm can seek the exact optimal solution with probability one at the rate of (O(ln K/root K)), where K is the number of iteration. Furthermore, the algorithm is also suitable and effective to the network with communication delays if the communication delays are bounded. Simulation results illustrate the effectiveness of the algorithm.
Economic dispatch problem (EDP) is an elementary optimization problem of power systems whose purpose is to minimize the total generation cost while meeting total demands and complying with individual generator output ...
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Economic dispatch problem (EDP) is an elementary optimization problem of power systems whose purpose is to minimize the total generation cost while meeting total demands and complying with individual generator output constraints. This paper proposes a distributed optimization algorithm with noisy gradient based on stochastic gradient-push approach to solve the EDP on time-varying directed communication networks potentially with time delays. It shows that the proposed algorithm can be ensured to solve the EDP when the time-varying directed communication networks are uniformly jointly strongly connected. The algorithm with asynchronous step-sizes can deal with the finite time-varying delays on communication links as well. The generation cost functions are considered as strictly convex and strongly convex functions respectively with convergence rate of O((lnk)/root k) and O ((ink)/ k). Simulation results are provided to validate the availability of the algorithm.
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