The increasing development of information and communication technologies in power grid makes it possible to optimize the energy management of numerous physical users with cloud-based service, while users' concerns...
详细信息
The increasing development of information and communication technologies in power grid makes it possible to optimize the energy management of numerous physical users with cloud-based service, while users' concerns about privacy security have attracted increasingly more attention. To attack this challenge, this paper proposes the information masking (IM) method for the energy management problem in the form of mixed-integer quadratic programming (MIQP). Additionally, the feasibility and optimality of the recovered solution in the IM of MIQP is proven and given in the form of two lemmas. Next, the implementation mechanism of IM is designed based on a cloud-edge framework. Furthermore, the general requirements of the IM of MIQP are elaborated with respect to privacy security and computational cost to better accommodate practical applications. Finally, the optimal schedule of microgrid with on-site generators and flexible demand resources is modelled and simulated to demonstrate the feasibility and effectiveness of the proposed methodology.
This paper addresses the coordinated operation between wind farms and reservoir hydropower plants in networks with weak transmission capacity. The joint operation of the energy sources is captured by a Virtual Power P...
详细信息
This paper addresses the coordinated operation between wind farms and reservoir hydropower plants in networks with weak transmission capacity. The joint operation of the energy sources is captured by a Virtual Power Plant (VPP) representation. With the aim of maximising renewable energy penetration while ensuring a suitable VPP integration, a supervisory controller for the energy dispatch layer is proposed. To deal with the variable nature of both resources, the controller has been designed into a model predictive control framework including mixed-integer quadratic programming (given the hybrid considered model) for solving the related optimisation problem, and complementary techniques as constraints softening and time-varying weighting. The results indicate that the predictive control approach achieves a better Independent System Operator (ISO) reference tracking that, together with reservoir management, are the most important factors to ensure a suitable VPP incorporation to the main grid. As a case study, a sub-network of the Argentinian power system is tackled. The controller performance is quantitatively and qualitatively assessed under uncertain conditions and compared with other approaches over a nine-year period. By means of the proposed power management policy, the ISO's effort to balance the sub-network is reduced 56% with regard to other approaches without any water spillage. (C) 2020 Elsevier Ltd. All rights reserved.
Battery storage system design has become a crucial task for nanogrids and microgrids planning, as it strongly determines the techno-economic viability of the project. Despite that, most of developed methodologies for ...
详细信息
Battery storage system design has become a crucial task for nanogrids and microgrids planning, as it strongly determines the techno-economic viability of the project. Despite that, most of developed methodologies for optimally planning this kind of systems still present some important issues like high computational burden or insufficient results. This paper develops a novel methodology for battery storage system planning in nanogrids and microgrdis, which aims at overcoming the main issues presented by other methodologies. To achieve this goal, our proposal originally combines different software, clustering techniques and optimization tools. As salient features of the developed approach, it is worth remarking its efficiency, versatility, ability to manage with different time horizons and comprehensiveness. A prospective nanogrid in the region of Cuenca, Ecuador, serves as illustrative case study to show the capabilities, efficiency and effectiveness of the proposed approach as providing sufficient guidelines for its universal applicability. Among other relevant results, our proposal is able to determine that, for the studied grid, the daily operating cost can be reduced up to 17% by using Nickel-Cadmium batteries, however, the usage of Lead-Acid and Sodium-Sulfur technologies resulted more attractive through the project lifetime due to their longer lifetimes and relatively low capital costs.
There are usually many sources for the supply of raw material to a pulp or paper mill in Sweden. Optimization of this supply is therefore a challenging task, and can only be managed properly if all aspects of risk are...
详细信息
There are usually many sources for the supply of raw material to a pulp or paper mill in Sweden. Optimization of this supply is therefore a challenging task, and can only be managed properly if all aspects of risk are considered. In our study, these risks are related to when the weather reduces the load-bearing capacity of the ground or the roads. A stochastic and a deterministic model have been formulated, and they have been solved with mixed-integer quadratic programming and tested with data from a Swedish forest company. The results of this study show that the option value is greater than zero and that both the optimal policy and the option value change whenever the storage cost is altered. This shows that the optimal planning policy obtained from the stochastic model differs from the solution of the deterministic model.
We devise a model predictive control algorithm for impulsive linear systems with autonomous flow dynamics and controlled jumps. Thereby the moments of jumps are not fixed, but rather considered as decision variables. ...
详细信息
We devise a model predictive control algorithm for impulsive linear systems with autonomous flow dynamics and controlled jumps. Thereby the moments of jumps are not fixed, but rather considered as decision variables. To this end, the complete system dynamics is formulated as a mixed-logical dynamical system after an appropriate discretization step. The resulting optimization problem contains both discrete and continuous decision variables, giving rise to a mixed-integerprogramming problem. The objective of the optimization is to steer the states into a target set. The stability is addressed through an appropriate cost function together with invariance conditions, as well as by introducing terminal constraints which are only enforced within a certain distance to the target set, thus, providing a trade-off between guaranteed convergence to the target set and computational complexity.
This paper proposes a new algorithm for solving mixed-integer quadratic programming (MIQP) problems. The algorithm is particularly tailored to solving small-scale MIQPs such as those that arise in embedded hybrid Mode...
详细信息
This paper proposes a new algorithm for solving mixed-integer quadratic programming (MIQP) problems. The algorithm is particularly tailored to solving small-scale MIQPs such as those that arise in embedded hybrid Model Predictive Control (MPC) applications. The approach combines branch and bound (B&B) with nonnegative least squares (NNLS), that are used to solve quadraticprogramming (QP) relaxations. The QP algorithm extends a method recently proposed by the author for solving strictly convex QP's, by (i) handling equality and bilateral inequality constraints, (ii) warm starting, and (iii) exploiting easy-to-compute lower bounds on the optimal cost to reduce the number of QP iterations required to solve the relaxed problems. The proposed MIQP algorithm has a speed of execution that is comparable to state- of-the-art commercial MIQP solvers and is relatively simple to code, as it requires only basic arithmetic operations to solve least-square problems.
One of the most widespread modern control strategies is the discrete-time Model Predictive Control (MPC) method which requires the solution of the quadraticprogramming problem. For systems with binary input variables...
详细信息
One of the most widespread modern control strategies is the discrete-time Model Predictive Control (MPC) method which requires the solution of the quadraticprogramming problem. For systems with binary input variables the quadratic problem is replaced by more challenging mixed-integer quadratic programming (MIQP) problem. The objective of this work is the implementation of MIQP problem solver in a low power embedded computing platform with limited computational power and limited memory. The MIQP problem is solved using branch-and-bound method and the solution of the relaxed original quadratic problems with equality and inequality constraints solved in the nodes of a binary tree is found with interior-point algorithm. A simulation study of the reserve constrained economic dispatch problem for power generators with prohibited zones is presented. Simulation results show the applicability of the proposed solver for small size MIQP problems.
To solve the optimization control problem of small unmanned helicopter nonlinear system, this paper proposes a method that models and lower-orders based on hybrid systems, obtains the maximal controlled invariant sets...
详细信息
ISBN:
(纸本)9787900719706
To solve the optimization control problem of small unmanned helicopter nonlinear system, this paper proposes a method that models and lower-orders based on hybrid systems, obtains the maximal controlled invariant sets by states constraint, then solves the optimization problem by mixedintegerquadraticprogramming in the sets. Finally, a model is modeled and simulated, the result proves the validity and efficiency.
暂无评论