Stochastic programming based coordinated expansion planning of generation,transmission,demand side resources,and energy storage considering the DC transmission system

With the increasing penetration of wind and solar energies,the accompanying uncertainty that propagates in the system places higher requirements on the expansion planning of power systems.A source-grid-load-storage coordinated expansion planning model based on stochastic programming was proposed to suppress the impact of wind and solar energy fluctuations.Multiple types of system components,including demand response service entities,converter stations,DC transmission systems,cascade hydropower stations,and other traditional components,have been extensively modeled.Moreover,energy storage systems are considered to improve the accommodation level of renewable energy and alleviate the influence of intermittence.Demand-response service entities from the load side are used to reduce and move the demand during peak load periods.The uncertainties in wind,solar energy,and loads were simulated using stochastic programming.Finally,the effectiveness of the proposed model is verified through numerical simulations.

Coordinated Planning Transmission Tasks in Heterogeneous Space Networks:A Semi-Distributed Approach

This paper studies the coordinated planning of transmission tasks in the heterogeneous space networks to enable efficient sharing of ground stations cross satellite systems.Specifically,we first formulate the coordinated planning problem into a mixed integer liner programming(MILP)problem based on time expanded graph.Then,the problem is transferred and reformulated into a consensus optimization framework which can be solved by satellite systems parallelly.With alternating direction method of multipliers(ADMM),a semi-distributed coordinated transmission task planning algorithm is proposed,in which each satellite system plans its own tasks based on local information and limited communication with the coordination center.Simulation results demonstrate that compared with the centralized and fully-distributed methods,the proposed semi-distributed coordinated method can strike a better balance among task complete rate,complexity,and the amount of information required to be exchanged.

Multi-stage power source and grid coordination planning method considering grid uniformity

Given the increasing uncertainties in power supply and load,this paper proposes the concept of power source and grid coordination uniformity planning.In this approach,the standard deviation of the transmission line load rate is considered as the uniformity evaluation index for power source and grid planning.A multi-stage and multi-objective optimization model of the power source and grid expansion planning is established to minimize the comprehensive cost of the entire planning cycle.In this study,the improved particle swarm optimization algorithm and genetic algorithm are combined to solve the model,thus improving the efficiency and accuracy of the solution.The analysis of a simple IEEE Garver’s 6-node system shows that the model and solution method are effective and feasible.Moreover,they are suitable for the coordinated planning of the power source and grid under a diversified nature of power supply and load.

Motion Planning Based Coordinated Control for Hydraulic Excavators

Hydraulic excavator is one type of the most widely applied construction equipment for various applications mainly because of its versatility and mobility. Among the tasks performed by a hydraulic excavator, repeatable level digging or flat surface finishing may take a large percentage. Using automated functions to perform such repeatable and tedious jobs will not only greatly increase the overall productivity but more importantly also improve the operation safety. For the purpose of investigating the technology without loss of generality, this research is conducted to create a coordinate control method for the boom, arm and bucket cylinders on a hydraulic excavator to perform accurate and effective works. On the basis of the kinematic analysis of the excavator linkage system, the tip trajectory of the end-effector can be determined in terms of three hydraulic cylinders coordinated motion with a visualized method. The coordination of those hydraulic cylinders is realized by controlling three electro-hydraulic proportional valves coordinately. Therefore, the complex control algorithm of a hydraulic excavator can be simplified into coordinated motion control of three individual systems. This coordinate control algorithm was validated on a wheeled hydraulic excavator, and the validation results indicated that this developed control method could satisfactorily accomplish the auto-digging function for level digging or flat surface finishing.

IMMUNE GENETIC ALGORITHM FOR THE PATH PLANNING OF TIGHTLY COORDINATED TWO-ROBOT MANIPULATORS

A novel algorithm, the immune genetic algorithm based on multi-agent, isproposed for the path planning of tightly coordinated two-robot manipulators, which constructsmainly immune operators accomplished by three steps: defining strategies and methods of multi-agent,calculating virtual forces acting on an agent, and constructing immune operators and performingimmunization during the evolutionary process. It is illustrated to be able to restrain thedegenerate phenomenon effectively and improve the searching ability with high converging speed.

Optimal control based coordinated taxiing path planning and tracking for multiple carrier aircraft on flight deck

Coordinated taxiing planning for multiple aircraft on flight deck is of vital importance which can dramatically improve the dispatching efficiency.In this paper,first,the coordinated taxiing path planning problem is transformed into a centralized optimal control problem where collision-free conditions and mechanical limits are considered.Since the formulated optimal control problem is of large state space and highly nonlinear,an efficient hierarchical initialization technique based on the Dubins-curve method is proposed.Then,a model predictive controller is designed to track the obtained reference trajectory in the presence of initial state error and external disturbances.Numerical experiments demonstrate that the proposed“offline planningþonline tracking”framework can achieve efficient and robust coordinated taxiing planning and tracking even in the presence of initial state error and continuous external disturbances.

A deep reinforcement learning method for multi-stage equipment development planning in uncertain environments

Equipment development planning(EDP)is usually a long-term process often performed in an environment with high uncertainty.The traditional multi-stage dynamic programming cannot cope with this kind of uncertainty with unpredictable situations.To deal with this problem,a multi-stage EDP model based on a deep reinforcement learning(DRL)algorithm is proposed to respond quickly to any environmental changes within a reasonable range.Firstly,the basic problem of multi-stage EDP is described,and a mathematical planning model is constructed.Then,for two kinds of uncertainties(future capabi lity requirements and the amount of investment in each stage),a corresponding DRL framework is designed to define the environment,state,action,and reward function for multi-stage EDP.After that,the dueling deep Q-network(Dueling DQN)algorithm is used to solve the multi-stage EDP to generate an approximately optimal multi-stage equipment development scheme.Finally,a case of ten kinds of equipment in 100 possible environments,which are randomly generated,is used to test the feasibility and effectiveness of the proposed models.The results show that the algorithm can respond instantaneously in any state of the multistage EDP environment and unlike traditional algorithms,the algorithm does not need to re-optimize the problem for any change in the environment.In addition,the algorithm can flexibly adjust at subsequent planning stages in the event of a change to the equipment capability requirements to adapt to the new requirements.

New Rural Community Planning to Cope with the Coordinated “Threezation”

The paper targets at reasonable planning and construction of new rural communities on the basis of coordinated "three-zation"(new urbanization, industrialization and agricultural modernization, hereinafter referred to as "three-zation"). Through summarizing the connotations of new rural community construction coping with the coordinated "three-zation", and analyzing the role of new rural community in the "three-zation", planning and design of Gaocun Community was taken for example to propose strategies for the planning and construction of new rural communities, and promotion of the coordinated "three-zation".

Overall Framework and Module of Distribution Network Coordinated Planning Considering Distributed Generation

Combining with the characteristics of China's energy and the strategy of sustainable development, analyzing the pros and cons which caused by the appearance of DG and their operation connecting to grid, this paper points out that the two sides can achieve win-win under a reasonable combination between DG and distribution system, so as to optimize the allocation of resources, improve the utilization ratio of resource, and obtain maximum social benefit, harmoniously promote the development of power industry, economy and environment. As a word, this paper puts forward a new model of distribution network planning including DG and brings in penalty factorto guide the investment and construction of DG. Last of all, this paper presents the adoption of the coordination development coefficients which is to evaluate the power planning.

Coordinated dynamic mission planning scheme for intelligent multi-agent systems

Mission planning was thoroughly studied in the areas of multiple intelligent agent systems,such as multiple unmanned air vehicles,and multiple processor systems.However,it still faces challenges due to the system complexity,the execution order constraints,and the dynamic environment uncertainty.To address it,a coordinated dynamic mission planning scheme is proposed utilizing the method of the weighted AND/OR tree and the AOE-Network.In the scheme,the mission is decomposed into a time-constraint weighted AND/OR tree,which is converted into an AOE-Network for mission planning.Then,a dynamic planning algorithm is designed which uses task subcontracting and dynamic re-decomposition to coordinate conflicts.The scheme can reduce the task complexity and its execution time by implementing real-time dynamic re-planning.The simulation proves the effectiveness of this approach.

CAD Model-Based Intelligent Inspection Planning for Coordinate Measuring Machines

As the market competition among enterprises grows intensively and the demand for high quality products increases rapidly, product quality inspection and control has become one of the most important issues of manufacturing, and improving the efficiency and accuracy of inspection is also one of problems which enterprises must solve. It is particularly important to establish rational inspection planning for parts before inspecting product quality correctly. The traditional inspection methods have been difficult to satisfy the requirements on the speed and accuracy of modern manufacturing, so CAD-based computer-aided inspection planning （CAIP） system with the coordinate measuring machines （CMM） came into being. In this paper, an algorithm for adaptive sampling and collision-free inspection path generation is proposed, aiming at the CAD model-based inspection planning for coordinate measuring machines （CMM）. Firstly, using the method of step adaptive subdivision and iteration , the sampling points for the specified number with even distribution will be generated automatically. Then, it generates the initial path by planning the inspection sequence of measurement points according to the values of each point＇s weight sum of parameters, and detects collision by constructing section lines between the probe swept-volume surfaces and the part surfaces, with axis-aligned bounding box （AABB） filtering to improve the detection efficiency. For collided path segments, it implements collision avoidance firstly aiming at the possible outer-circle features, and then at other collisions, for which the obstacle-avoiding movements are planned with the heuristic rules, and combined with a designed expanded AABB to set the obstacle-avoiding points. The computer experimental results show that the presented algorithm can plan sampling points＇ locations with strong adaptability for different complexity of general surfaces, and generate efficient optimum path in a short time and avoid collision effectively.

Dual-manipulator Coordinate Motion Planning Scheme for Robot Satellite

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ORGANIZING MACRO ECONOMIC REGIONS AND ENHANCING INTER-PROVINCIAL COORDINATION AND PLANNING IN CHINA

This paper elaborates upon the purpose of macro economicroponalization and inter-provincial planning and coordination under thesocialist market system. It descnbes the characteristics and orgarnzationalforms of macro economic regions and the principle of macro economic regionalization. The six macro economic regions-Northeast China, NorthChina, Northwest China, Middle-East China, Southwest China and South China-are divided in the paper. At the end, the paper describes somemajor programs, which requires cooperation among various involvedprovinces.

Fuzzy Q learning algorithm for dual-aircraft path planning to cooperatively detect targets by passive radars

The problem of passive detection discussed in this paper involves searching and locating an aerial emitter by dualaircraft using passive radars. In order to improve the detection probability and accuracy, a fuzzy Q learning algorithrn for dual-aircraft flight path planning is proposed. The passive detection task model of the dual-aircraft is set up based on the partition of the target active radar＇s radiation area. The problem is formulated as a Markov decision process （MDP） by using the fuzzy theory to make a generalization of the state space and defining the transition functions, action space and reward function properly. Details of the path planning algorithm are presented. Simulation results indicate that the algorithm can provide adaptive strategies for dual-aircraft to control their flight paths to detect a non-maneuvering or maneu- vering target.

A Multirobotic Planning Based on Expert System

A robotic planning system using the technique of expert system for multirobotic coordi-nated motion with collision-avoidance has been developed.Its general architecture and theroles of its components are introduced in this paper.The task planning diagram of this sys-tem is also briefly explained.A mechanism for multirobotic planning has been proposed.Two examples of traffic control system,i.e.two-robot coordinated pathfinding system withcollision-avoidance have been demonstrated.In order to avoid the collision,some controlstrategies are applied.The results of this planning system are valuable and helpful for plan-ning the multirohotic coordinated motion with collision-avoidance.

Scenario-based modeling and solving research on robust weapon project planning problems

Weapon project planning(WPP) plays a critical role in the process of national defense development and establishment of the future national defense force. WPP faces the backgrounds of various uncertainties, intense inter-influence of weapon systems and involves modelling, assessment, and optimization procedures.The contents of this paper are mainly divided into three parts: first,the WPP processes are analyzed, and related elements are formulated to transform the qualitative problem to mathematics form;second, the value evaluation model of WPP solutions is proposed based on two criteria of total capability gap and total capability dispersion; third, two robustness optimization models are constructed based on the absolute robustness criterion and the robustness deviation criterion to support the robustness optimization process under multi-scenario. Finally, a case is studied to examine the feasibility and effectiveness of the proposed models and approaches.

Ecological and Environmental Protection Requirements in China s Regional Coordinated Development Strategy in the New Era

Starting from the historical evolution of China s regional coordinated development policy and practice,three stages of"enlightenment stage","development stage"and"maturity stage",as well as the connotation,characteristics and content of implementing regional coordinated development strategy were analyzed.On this basis,from different aspects of industrial distribution,pollutant characteristics and regional environmental protection policy,the existing ecological and environmental protection problems in China s regional coordinated development in the new era were analyzed,and some suggestions for the next step were put forward.It is necessary to follow the"four ones"concept from the overall point of view,implement"three lines and one list"from the perspective of the width of the access red line,strengthen"joint prevention and control"from the perspective of the depth of regional regulation,deepen the"planning environmental impact assessment"from the perspective of the breadth of industrial distribution,and promote the"green-way model"from the perspective of ecological low carbon.

MOTION PLANNING OF MULTIPLE MOBILE ROBOTS COOPERATIVELY TRANSPORTING A COMMON OBJECT

Many applications above the capability of a single robot need the cooperation of multiple mobile robots, but effective cooperation is hard to achieve. In this paper, a master slave method is proposed to control the motions of multiple mobile robots that cooperatively transport a common object from a start point to a goal point. A noholonomic kinematic model to constrain the motions of multiple mobile robots is built in order to achieve cooperative motions of them, and a “Dynamic Coordinator” strategy is used to deal with the collision avoidance of the master robot and slave robot individually. Simulation results show the robustness and effectiveness of the method.

Quadratic Programming-based Approach for Autonomous Vehicle Path Planning in Space

Path planning for space vehicles is still a challenging problem although considerable progress has been made over the past decades.The major difficulties are that most of existing methods only adapt to static environment instead of dynamic one,and also can not solve the inherent constraints arising from the robot body and the exterior environment.To address these difficulties,this research aims to provide a feasible trajectory based on quadratic programming（QP） for path planning in three-dimensional space where an autonomous vehicle is requested to pursue a target while avoiding static or dynamic obstacles.First,the objective function is derived from the pursuit task which is defined in terms of the relative distance to the target,as well as the angle between the velocity and the position in the relative velocity coordinates（RVCs）.The optimization is in quadratic polynomial form according to QP formulation.Then,the avoidance task is modeled with linear constraints in RVCs.Some other constraints,such as kinematics,dynamics,and sensor range,are included.Last,simulations with typical multiple obstacles are carried out,including in static and dynamic environments and one of human-in-the-loop.The results indicate that the optimal trajectories of the autonomous robot in three-dimensional space satisfy the required performances.Therefore,the QP model proposed in this paper not only adapts to dynamic environment with uncertainty,but also can satisfy all kinds of constraints,and it provides an efficient approach to solve the problems of path planning in three-dimensional space.

Coordinated RES and ESS Planning Framework Considering Financial Incentives Within Centralized Electricity Market

Coordinated investment and operations within renewable portfolio standards is one of the key technologies to meet the renewable energy target and realize the economic operations of the power system.This paper proposes a unified framework of coordinated planning and financial incentives.Joint investment in renewable energy and energy storage and joint optimization of energy and ancillary services are integrated into a unified framework.Various factors are taken into consideration by the social planner in the centralized electricity market,such as the sitting and sizing of renewable energy and energy storage,charge and discharge efficiency of the energy storage,transmission network constraints,reserve capacity,and financial incentives.This framework provides a tool for the social planner to determine the optimal planning scheme of renewable energy and energy storage.The conclusion derived is that the sum of market revenue and financial subsidies of renewable energy and energy storage is exactly equal to their investment cost which is obtained by the Karush-Kuhn-Tucker(KKT)condition of maximizing social welfare problems.A numerical result based on the modified IEEE-39 bus test system demonstrates the effectiveness of the unified framework.The impact of financial incentives,reserve capacity,and production costs on capital investment are studied.