This paper proposes and demonstrates procedures to optimally design tensegrity structures actuation, based on closed loop shape control requirements, while at the same time a feasible path for realizing a desired shap...
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This paper proposes and demonstrates procedures to optimally design tensegrity structures actuation, based on closed loop shape control requirements, while at the same time a feasible path for realizing a desired shape is synthesized. The procedures are employing different optimization based formulations of a set of requirements needed for shape control. The specific procedure demonstrated is based on a mixed integer linear programming formulation, one of the simplest possible. It is possible to formulate the design problem more generally, but then the computations become more involved, inhibiting a real time implementation of the procedure. The demonstration is for a simple planar tensegrity, but the procedures can be applied to more general structures without modification
This paper presents a mathematical problem formulation for energy management systems for smart homes. The flexibility can be provided by a home energy management system (HEMS) in a local energy community. The main con...
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ISBN:
(数字)9781665485371
ISBN:
(纸本)9781665485388
This paper presents a mathematical problem formulation for energy management systems for smart homes. The flexibility can be provided by a home energy management system (HEMS) in a local energy community. The main concept is to model the flexibility provision and flexibility procurement within the energy community that can be provided to the aggregator from active consumers. The integrated energy management model is coded as a standard mixed-integerlinearprogramming (MILP) model which can be solved by open-source tools like the PuLP package developed in Python. The simulation results confirm the performance of the proposed model in terms of flexibility provided by the centralized integrated energy system introduced in this paper.
Restoring a power system following a blackout is a critical undertaking, necessitating the efficient allocation of Black Start (BS) resources—generators capable of initiating without external power. This research int...
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ISBN:
(数字)9798350372403
ISBN:
(纸本)9798350372410
Restoring a power system following a blackout is a critical undertaking, necessitating the efficient allocation of Black Start (BS) resources—generators capable of initiating without external power. This research introduces an innovative approach to address a critical challenge in power system restoration—optimal black start allocation. Efficient allocation of resources when power systems face blackouts is crucial for rapid restoration. Leveraging the power of mixed integer linear programming (MILP), this study formulates and solves the black start allocation problem with the primary objective of minimizing allocation costs, all while satisfying many operational constraints. These constraints include ensuring power supply meets demand, adhering to generator output limits and ramping rates, and enforcing time-bound generator startup decisions. Furthermore, it maintains power flow equilibrium and network stability through branch flow and voltage magnitude constraints. This research offers a promising solution to enhance the resilience and reliability of power systems by optimizing the allocation of black start resources. This would reduce downtime ultimately and mitigate the far-reaching impacts of blackouts on society and the economy.
This paper presents an application of the Multi-Objective Branch-and-Bound based on Decomposition (MOBB/D) method for Branch-and-Cut, combining branch-and-bound and cutting-plane methods. Traditionally, multi-objectiv...
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ISBN:
(数字)9798350373332
ISBN:
(纸本)9798350373349
This paper presents an application of the Multi-Objective Branch-and-Bound based on Decomposition (MOBB/D) method for Branch-and-Cut, combining branch-and-bound and cutting-plane methods. Traditionally, multi-objective branch-and-bound methods for multi-objective mixed-integerlinearprogramming problems struggle with the large number of Pareto-optimal solutions. MOBB/D addresses this by decomposing multi-objective problems into single-objective subproblems using weight vectors and applying branch-and-bound to each, with information sharing between nearby subproblems. In this paper, we customize the MOBB/D method for Branch-and-Cut to achieve an efficient search by sharing cutting plane information in MOBB/D. We demonstrate our approach with a case study on garbage collection planning in Muroran City, Hokkaido, Japan. This case study combines facility location and route optimization within a multi-objective framework, balancing the burdens on residents and garbage collection workers. Numerical experiments compare execution times and solutions with and without cutting plane sharing, and visualize the impact of different objective balance preferences on route optimization. The results show substantial efficiency gains and provide practical insights for multi-objective optimization in urban planning.
In this paper, a probabilistic methodology for estimating the spinning reserve in microgrids is proposed. The spinning reserve amount is determined by maximizing the total profit while considering the unreliability of...
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ISBN:
(纸本)9781424452293
In this paper, a probabilistic methodology for estimating the spinning reserve in microgrids is proposed. The spinning reserve amount is determined by maximizing the total profit while considering the unreliability of units and uncertainties caused by nondispatchable units and load. In order to reduce the computation burden, various uncertainties are aggregated and rounding to an equivalent distribution. The optimization is solved by mixed integer linear programming.
Monoculture induced threats such as "pass the hash" attacks can spread more easily through a system of similar components. Introducing a few different and more robust components in the system has the potenti...
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Monoculture induced threats such as "pass the hash" attacks can spread more easily through a system of similar components. Introducing a few different and more robust components in the system has the potential to mitigate such situations. In this paper, we propose a constrained resource allocation optimization framework exploring the binary decision diagram (BDD) and mixed integer linear programming techniques. An illustrative example is provided.
The current ownership of Electric Vehicles (EVs) in China is experiencing rapid growth, which presents new challenges to the distribution of electric grid loads. At present, the pricing strategies and demand response ...
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ISBN:
(数字)9798350375855
ISBN:
(纸本)9798350375862
The current ownership of Electric Vehicles (EVs) in China is experiencing rapid growth, which presents new challenges to the distribution of electric grid loads. At present, the pricing strategies and demand response mechanisms of EV charging aggregators are of great practical importance, as they guide EV users to charge their vehicles during off-peak hours and alleviate the grid load during peak hours. This paper presents a leader-follower game model in which the aggregator, acting as the leader, sets electricity prices to encourage EV users to charge during off-peak periods, thereby reducing the pressure on the electricity supply during peak periods. In addition, a mixed integer linear programming method is employed to solve the model, ensuring global optimality of the strategy. Empirical evidence indicates that electricity prices should be adaptively adjusted in accordance with seasonal fluctuations and changes in demand in order to maximize the aggregator's revenue and minimize the user's charging costs. This approach is conducive to the deployment of electric vehicles and the advancement of smart grids.
This paper discusses the implementation of a guidance system based on mixed integer linear programming (MILP) on a modified, autonomous T-33 aircraft equipped with Boeing's UCAV avionics package. A receding horizo...
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This paper discusses the implementation of a guidance system based on mixed integer linear programming (MILP) on a modified, autonomous T-33 aircraft equipped with Boeing's UCAV avionics package. A receding horizon MILP formulation is presented for safe, real-time trajectory generation in a partially-known, cluttered environment. Safety at all times is guaranteed by constraining the intermediate trajectories to terminate in a loiter pattern that does not intersect with any no-fly zones and can always be used as a safe backup plan. Details about the real-time software implementation using CPLEX and Boeing's OCP platform are given. A test scenario developed for the DARPA-sponsored software enabled control capstone demonstration is outlined, and simulation and flight test results are presented
This problem includes fuzzy parameters, choosing suppliers according to their quality raw materials and supplier contracts. There is a trade-off between raw material quality, its purchasing and reprocessing costs. If ...
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This problem includes fuzzy parameters, choosing suppliers according to their quality raw materials and supplier contracts. There is a trade-off between raw material quality, its purchasing and reprocessing costs. If decision maker (DM) wishes to work with a supplier which supplies a low quality raw material, this raw material can be in need of reprocessing. To avoid the reprocessing costs, a supplier which serves a high quality raw material can be chosen but at this time the DM has to face a high purchasing cost. An integrated fuzzy supply chain network system is considered to accomplish problems aforementioned trade-offs above.
Significant capacity of wind power producers (WPPs) compared to the total installed generation grants a dominant position to these producers in the market environment. Accordingly, The present study concerns the optim...
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ISBN:
(数字)9781665419574
ISBN:
(纸本)9781665419581
Significant capacity of wind power producers (WPPs) compared to the total installed generation grants a dominant position to these producers in the market environment. Accordingly, The present study concerns the optimal offering strategy of a strategic WPP. The price-maker WPP offers to day-ahead (DA) and intraday (ID) markets to manipulate prices in order to attain further profits. Also, it compensates its deviations of production in the balancing (BAL) market. The proposed framework is a bi-level model that can be formulated as a mathematical program with equilibrium constraints (MPEC). By utilizing the strong duality theorem, Karush-Kuhn-Tucker (KKT) conditions, and the Fortuny-Amat method the problem is transformed into a mixed-integerlinearprogramming (MILP) model. Demand bids, rival producers' offerings, and wind production are incorporated into the model through scenarios. A 3-bus system and IEEE 24-bus RTS are used as case studies to delineate the efficiency of the methodology.
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