Optimal Distribution Strategy Research Articles

Torque Distribution Strategy Based on Deep Learning for Parallel Hybrid Electric Vehicle

In order to improve the fuel economy of hybrid electric vehicle (HEV), an improved deep recurrent neural network-based energy management strategy model (IDRNN-EMS) is proposed to learn optimal torque distribution strategy for the single-axle parallel hybrid electric vehicle (HEV). Specifically, we formulate EMS as time series prediction problem to meet the requirement of deep recurrent neural network (DRNN). Then, skip connection structure is introduced into deep recurrent neural network to improve the training efficiency of our proposed model. We provide comprehensive simulation evidence showing that the improved model with skip connection is easier to optimize in public platform TensorFlow. Comparing with the DRNN-EMS model, our improved model with ship connection yields remarkable performance in terms of fuel economy and accuracy.

Input-output dynamic model for optimal environmental pollution control

This paper describes the allocation of a wastewater treatment fund within a region based on a dynamic input-output model. Considering the complexity of the input-output process, many indeterminate factors must be included in the model. For example, with the aging of machines, an unexpected loss will be caused by the retention of raw materials during an operation; this can be realistically considered as a random variable, because of the sufficiently large amount of historical data. By contrast, actions such as a temporary transfer or inexperienced operators can only be regard as uncertain variables, because of a lack of historical data. First, the pollution control model is formulated in an uncertain environment by including both human uncertainty and objective randomness. Second, an optimal control model subject to an uncertain random singular system is established; this model can be transformed into an equivalent optimization problem. To solve such a problem, recurrence equations are presented based on Bellman’s principle, and these were successfully applied to address the optimal control problem in two special cases. Moreover, two algorithms are formulated for solving the pollution control problem. Finally, the optimal distribution strategies of the pollution control fund used to control the emissions of COD and NH3-H, which are two indicators of wastewater in China, were obtained through the proposed algorithms.

Direct Selling, Reselling, or Agency Selling? Manufacturer’s Online Distribution Strategies and Their Impact

ABSTRACTWe investigate a manufacturer’s three possible online strategies while the manufacturer also distributes its product through an independent retailer in a traditional channel. Under direct selling, the manufacturer sells its products to online consumers directly. Under reselling, the manufacturer sells its product through an e-tailer. Under agency selling, the manufacturer sells its products to consumers through an online agent’s website and pays the agent a commission fee. We show that it is optimal for the manufacturer to choose direct selling if the operating cost for the online channel under direct selling is sufficiently low relative to that under reselling as well as the online agent’s commission fee. Similarly, reselling through an e-tailer is optimal to the manufacturer if the operating cost for the online channel under reselling is sufficiently low. Furthermore, agency selling should be chosen if the online agent’s commission fee is sufficiently low. However, a strategy with a low online cost (including the operating costs under direct selling and reselling, and the commission fee under agency selling) may lead to a low profit for the traditional retailer, which eventually causes a low total profit for the supply chain. Nonetheless, consumers generally benefit from the manufacturer’s optimal online distribution strategy because of low prices and high quantities.

Optimisation of the distribution of power from a photovoltaic generator between two pumps working in parallel

In this work, a method for distributing the power generated in a photovoltaic pumping system equipped with two equal pumps, working in parallel is analysed.For this purpose, a system equipped with two pumping groups 0.75 kW each was investigated. Experimental tests at five different working frequencies (30 to 50 Hz), and at six pumping heads (18 to 48 m) were carried out.The main objective of this paper is to establish a strategy for the distribution of the generated power that maximises the flow rate from the set of two pumps. This distribution depends both on the available electric power and on the pumping head.The results show some differences between higher and lower pumping heads, but in both cases for lower power values, the strategy involves the operation of a single pump with the limitation that the power assigned to this pump cannot exceed the maximum value (Pmax). However, if the available power exceeds a certain value, referred to as Pe, it must then be distributed at 50% between the two pumps. Thus, there is no power distribution ratio other than 0 and 50% that maximises the flow rate, except that required to limit the power assigned to one of the pumps to Pmax.It was proven that the optimal distribution strategy for the available power depends on whether Pe > Pmax (for higher pumping heads) or Pe < Pmax (in case of lower heads). In practice, it is easy to determine which case applies using a simple pumping test.

An Optimal Torque Distribution Strategy for Four-Motorized-Wheel Electric Vehicle Considering Energy Conversation

In this paper, an optimal torque distribution strategy (OTDS) for four-motorized-wheel electric vehicle (4MWEV) is proposed aiming at improving the tractive efficiency and braking energy recovery performance. Based on the motor efficiency map, the objective functions of tractive efficiency and braking energy recycling are established first. Under driving conditions, genetic algorithm (GA) is proposed to obtain the optimal torque distribution ratio of front and rear axles considering the constraints of motor characteristics and desired torque. During braking conditions, an exhaustive search method (ESM) is proposed to improve the energy recovery performance considering the constraints of motor characteristics, battery, braking theory and ECE Regulations. For the realization of efficient and accurate computation, a control scheme of off-line optimization and on-line allocation based on the optimal torque distribution ratio map is presented, which stores the optimal ratios in all available motor operating regions into two-dimensional lookup tables. Finally, co-simulation experiments based on MATLAB/Simulink and Carsim are conducted to verify the effectiveness of the proposed OTDS under NEDC and UDDS driving cycles. Comparing to the typical torque distribution strategy (TTDS), the simulation results demonstrate that the proposed OTDS can enhance the energy-saving performance by 7.01% under NEDC and 6.69% under UDDS.

Fragmental weight-conservation combining scheme for statistical signal transmissions under fast time-varying channels

Statistical Signal Transmission (SST) is a technique based on orthogonal frequency-division multiplexing (OFDM) and adopts cyclostationary features, which can transmit extra information without additional bandwidth. However, the more complicated environment in 5G communication systems, especially the fast time-varying scenarios, will dramatically degrade the performance of the SST. In this paper, we propose a fragmental weight-conservation combining (FWCC) scheme for SST, to overcome its performance degradation under fast time-varying channels. The proposed FWCC scheme consists of three phases: 1) incise the received OFDM stream into pieces; 2) endue different weights for fine and contaminated pieces, respectively; 3) combine cyclic autocorrelation function energies of all the pieces; and 4) compute the final feature and demodulate data of SST. Through these procedures above, the detection accuracy of SST will be theoretically refined under fast time-varying channels. Such an inference is confirmed through numerical results in this paper. It is demonstrated that the BER performance of proposed scheme outperforms that of the original scheme both in ideal channel estimation conditions and in imperfect channel estimation conditions. In addition, we also find the experiential optimal weight distribution strategy for the proposed FWCC scheme, which facilitates practical applications.

Optimal Margin Distribution Additive Machine

In recent years, sparse additive machines have attracted increasing attention in high dimensional classification due to their flexibility and representation interpretability. However, most of the existing methods are formulated under Tikhonov regularization schemes associated with the hinge loss, where the distribution information of observations is neglected usually. To circumvent this problem, we propose an optimal margin distribution additive machine (called ODAM) by incorporating the optimal margin distribution strategy into sparse additive models. The proposed approach can be implemented by a dual coordinate descent algorithm and its empirical effectiveness is confirmed on simulated and benchmark datasets.

Disintermediation: the optimal distribution strategy for small wineries

Disintermediation: the optimal distribution strategy for small wineries

Disintermediation: the optimal distribution strategy for small wineries

This study examines the utilisation of the disintermediation strategy by a family owned New Zealand wine business. A longitudinal case study approach was used to gather qualitative data about their distribution strategy. The key finding is that this business originally earnt 95% of total revenue through selling directly to end consumers by disintermediating their supply chain. Today, that figure has reduced to 80% of total revenue and the distribution strategy now includes some indirect retail and restaurant channels. This change in distribution strategy over time has been driven primarily by consumer demand. Whilst the disintermediation strategy initially allowed the business to maximise profits, gain distribution efficiencies, and enhance customer relationships, it did not fully meet the needs of all consumers. We discuss the rationale of the various direct and intermediated channels utilised by this business and suggest that these will be useful for other small wine businesses that want to achieve similar benefits through a combination of channel strategies.

Optimal Distribution Strategy for Movie Product

Motion picture companies are increasingly providing movies online. We develop a model to examine optimal distribution strategies for the movie studio. The studio can release the movie through the traditional channel (i.e. theatre) or online channel and has to decide the distribution strategy. When the studio is vertically integrated with the exhibitor, our results indicate that in the presence of a relatively low cost of using a traditional channel, the dual-channel strategy exists and generates the highest profit. However, when the cost is relatively high, the online channel strategy becomes the best strategy. When the studio is not vertically integrated with the exhibitor, when the studio’s commission share is low, the studio will adopt the dual-channel strategy if the traditional channel cost is low and the quality difference is large. If not, the studio will adopt the online channel strategy. When the studio’s commission share is moderate, the studio will adopt the dual-channel strategy if the traditional channel cost is low and the quality difference is large, the studio will adopt the dual-channel strategy if the traditional channel cost is low and the quality difference is moderate, otherwise, the studio will adopt the online channel strategy. When the studio’s commission share is large, the studio has more motivation to adopt traditional strategy.

Optimal Consensus-Based Distributed Control Strategy for Coordinated Operation of Networked Microgrids

A two-layer optimal consensus-based distributed control strategy is proposed for the coordinated operation of networked microgrids (MGs). Several networked MG operation objectives are optimized using the proposed control strategy, including frequency/voltage regulation, proportional active power sharing, and smooth MG islanding/reconnection operation. The global objective function of networked MGs is decomposed into a series of local objectives assigned to participating distributed energy resources (DERs). In the decomposed optimization, each control layer is realized in a distributed manner in which DER state variables reach consensus along with optimizing their assigned local objective functions. Each control layer in the two-layer control strategy is formulated as an optimal consensus problem in which the optimality and asymptotical stability of the system equilibrium point for each control layer are demonstrated. The effectiveness of the proposed control strategy is validated in a modified IEEE 33-bus distribution system using the PSCAD/EMTDC platform.

Reliability - Based Distributed Generation Optimization in Demand Response Planning

Energy is an important material basis for social development. People should pursue the optimal distribution of distributed power generation in the transmission system, establish a new power algorithm, and form the optimal power distribution scheme. The economy and safety of power operation can be guaranteed, and the distribution mode of distribution network becomes more reasonable. On this basis, it is hoped that the study of this paper can provide some constructive suggestions for the power generation of the transmission system, and various demand can be satisfied.

A New Dual Axle Drive Optimization Control Strategy for Electric Vehicles Using Vehicle-to-Infrastructure Communications

In this article, we proposed an optimal torque distribution strategy for pure electric vehicles based on Vehicle-to-Infrastructure (V2I) communication. V2I communication is used to obtain road surface adhesion coefficient, road roughness, and other information. Different speed and torque requirements for different road surface are analyzed. Then, according to motor map characteristics, a dual motor torque optimization distribution control strategy is proposed and a dual motor optimal torque distribution control method for adaptive road surface is established. Finally, the hardware-in-the-loop test system is used to verify the control strategy. New European Driving Cycle is used to simulate the control strategy. The off-line simulation results show that under adaptive road surfaces, the energy optimization rate is improved. To a certain extent, this article can provide a value reference to optimal power distribution strategy for modern smart pure electric vehicles.

Time and Power Allocation for Energy Efficiency Maximization in Wireless-Powered Full-Duplex Relay Systems

In this paper, we propose an optimal time and power allocation scheme in a wireless power supply full-duplex (FD) relay system, where we consider the number of relay antennas in the energy harvesting stage. At the same time, the energy efficiency optimization problem of the system is structured, where optimization issues related to time allocation factors and power allocation are established. For the FD dual-antenna and the FD single-antenna energy harvesting system, energy efficiency function is proven to be a concave function over the time-switch factor, and the optimal time-switching factor is theoretically obtained using the Lambert function. Then, according to the given value range of the optimal time switching factor, the optimal power distribution scheme is obtained by analyzing the derivative function of the system energy efficiency and using the properties of the Lambert function. The time-switching factor and transmission power are optimally selected at the wireless power supply FD relay. Results reveal that the performance of energy efficiency of the dual-antenna energy harvesting at the FD relay outperforms that of the single-antenna. Moreover, our results demonstrate that FD relay systems always substantially boost the energy efficiency compared with half-duplex (HD) relay systems.

Profit Distribution Strategy of Cooperation Construction Supply Chain under Carbon Tax Policy

Based on the background of carbon tax policy, this paper studies the optimal emission reduction decision and profit distribution strategy of the secondary construction supply chain composed of a general contractor and a subcontractor. By establishing the profit distribution model of the construction supply chain, the optimal emission reduction, the construction supply chain and the maximum profits of enterprises under the two conditions of decentralization and centralization are obtained, and then the comparative analysis of the two is conducted to obtain the reasonable range of the profit distribution proportion of the construction supply chain under the centralized situation. The results show that the full partnership has a positive effect on enterprises to take action to reduce emissions, and the reasonable profit distribution proportion is helpful to the construction of supply chain profit and the improvement of enterprises’ profit.

Charging–Discharging Control Strategy for a Flywheel Array Energy Storage System Based on the Equal Incremental Principle

The widely used flywheel energy storage (FES) system has such advantages as high power density, no environment pollution, a long service life, a wide operating temperature range, and unlimited charging–discharging times. The flywheel array energy storage system (FAESS), which includes the multiple standardized flywheel energy storage unit (FESU), is an effective solution for obtaining large capacity and high-power energy storage. In this paper, the strategy for coordinating and controlling the charging–discharging of the FAESS is studied in depth. Firstly, a deep analysis is conducted on the loss generated during the charging–discharging process of the FESU. The results indicate that the loss is related to the charging–discharging of power. To solve the problems of over-charging, over-discharging, and overcurrent caused by traditional charging–discharging control strategies, this paper proposes a charging–discharging coordination control strategy based on the equal incremental principle (EIP). This strategy aims to minimize the total loss and establish a mathematical model of optimal coordination control with the constraints of total charging–discharging power, rated power limit, over-charging, over-discharging, and overcurrent. Based on the EIP, the optimal distribution scheme of power charging–discharging is determined. Secondly, this paper gives the specific implementation scheme of the optimal coordinated control strategy. Lastly, the charging–discharging coordinated control strategy is verified by examples. The results show that the coordinated control strategy can effectively reduce the loss during the charging–discharging process and can prevent over-charging, over-discharging, and overcurrent of the system. Overall, it has a better control effect than the existing charging–discharging control strategies.

Control of Generalized Discrete-Time SIS Epidemics via Submodular Function Minimization

In this letter, we study a novel control method for a generalized SIS epidemic process. In particular, we use predictive control to design optimal protective resource distribution strategies which balance the need to eliminate the epidemic quickly against the need to limit the rate at which protective resources are used. We expect that such a controller may be useful in mitigating the spread of biological diseases which do not confer immunity to those who have been infected previously, with sexually transmitted infections being a prominent example of such. Technically, this letter provides a novel contribution in demonstrating that the particular combinatorial optimal control problem used to design resource allocations has an objective function which is submodular, and so can be solved in polynomial time despite its combinatorial nature. We test the performance of the proposed controller with numerical simulations, and provide some comments on directions for future work.

A framework for end-of-life photovoltaics distribution routing optimization

Transportation cost accounts for a significant portion among the total cost of photovoltaics (PV) recycling. The transportation cost can be significantly reduced with a well-planned vehicle routing. A generic mathematical framework was developed to generate the optimal distribution scheme for transporting retired PV. A static and a dynamic recycling algorithms were created as the optimization tool in the framework. As for the output, the framework generates the optimal distribution scheme, the transportation cost of the optimal scheme, as well as the amount of End-of-life PV that each PV recycling center receives. A case study was included to test the effectiveness of the proposed framework. The optimal costs generated by two algorithms were compared with the baseline cost. As a result, the cost can be reduced by 53% when compared with the baseline. In addition, the static algorithm can obtain a result with decent accuracy and low computational cost.

Improved cuckoo search load distribution (ICS‐LD) and attack detection in cloud environment

SummaryFor the purpose of obtaining an answer to a spoofing IP issue and related problems in the cloud computing (CC) environment, a novel path identifier is recommended, in which a new packet approach with a new identifier (ID) is produced to every user or client system. For the purpose of identification of the spoofing attack, any watermark image pattern is introduced. Following this, the hypervisor is employed to ascertain plausible trust relationships among the VMs by considering personal sources that can be trusted along with utilizing empirical Bayesian inference (EBI) for the purpose of combining the VMs. With a restricted budget of resources for the maximized detection of attacks, an optimal detection load distribution strategy by improved cuckoo search (ICS) over VMs can be used, which thus provides the intended solution to the hypervisor. The ICS algorithm directs a hypervisor so as to assert among the VMs the optimal load distribution, taking into consideration real time, which causes maximization of the DDoS attacks and detection of transmission control protocol (TCP) flood attacks. Lastly, a fuzzy extreme learning machine (FELM) classifier is proposed in order to detect the attacks.

Distributed MPC for Coordinated Energy Efficiency Utilization in Microgrid Systems

To improve the renewable energy utilization of distributed microgrid systems, this paper presents an optimal distributed model predictive control strategy to coordinate energy management among microgrid systems. In particular, through information exchange among systems, each microgrid in the network, which includes renewable generation, storage systems, and some controllable loads, can maintain its own system-wide supply and demand balance. With our mechanism, the closed-loop stability of the distributed microgrid systems can be guaranteed. In addition, we provide evaluation criteria of renewable energy utilization to validate our proposed method. Simulations show that the supply demand balance in each microgrid is achieved while, at the same time, the system operation cost is reduced, which demonstrates the effectiveness and efficiency of our proposed policy.