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.

Energy-Efficient UAVs Coverage Path Planning Approach

Unmanned aerial vehicles(UAVs),commonly known as drones,have drawn significant consideration thanks to their agility,mobility,and flexibility features.They play a crucial role in modern reconnaissance,inspection,intelligence,and surveillance missions.Coverage path planning(CPP)which is one of the crucial aspects that determines an intelligent system’s quality seeks an optimal trajectory to fully cover the region of interest(ROI).However,the flight time of the UAV is limited due to a battery limitation and may not cover the whole region,especially in large region.Therefore,energy consumption is one of the most challenging issues that need to be optimized.In this paper,we propose an energy-efficient coverage path planning algorithm to solve the CPP problem.The objective is to generate a collision-free coverage path that minimizes the overall energy consumption and guarantees covering the whole region.To do so,the flight path is optimized and the number of turns is reduced to minimize the energy consumption.The proposed approach first decomposes the ROI into a set of cells depending on a UAV camera footprint.Then,the coverage path planning problem is formulated,where the exact solution is determined using the CPLEX solver.For small-scale problems,the CPLEX shows a better solution in a reasonable time.However,the CPLEX solver fails to generate the solution within a reasonable time for large-scale problems.Thus,to solve the model for large-scale problems,simulated annealing forCPP is developed.The results show that heuristic approaches yield a better solution for large-scale problems within amuch shorter execution time than the CPLEX solver.Finally,we compare the simulated annealing against the greedy algorithm.The results show that simulated annealing outperforms the greedy algorithm in generating better solution quality.

Development Trend of Energy and Key Points of Ecological Environment Protection in China's "14^(th) Five-Year Plan" Period

From the changes of total primary energy consumption and primary energy consumption structure,installed capacity and power generation of secondary energy(electricity),etc.,the development characteristics of China's energy structure in the"13^(th) Five-Year Plan"period was comprehensively studied.Combined with the complexity of the international situation,the diversification of the domestic energy system,the intelligence of the energy industry,etc.,the situation and challenges faced by China's energy development were deeply discussed in the four aspects of energy security,energy low-carbon transformation,energy system efficiency,and energy technology level.From the angle of ecological environment protection,the development of energy in the"14^(th) Five-Year Plan"period in China was analyzed,and some policies and measures were put forward.

基于EnergyPLAN模型的城市可再生能源应用规划研究

随着经济社会快速发展,能源应用与环境问题日益突出,以高比例可再生能源利用为主体的区域能源规划成为国内外研究热点。基于EnergyPLAN模型,以江苏省扬州市为研究对象,以当前能源消费、能源供给数据和城市政策规划目标为基础,以2035为目标,构建三种未来能源系统场景,定量分析目前发展模式下扬州可再生能源利用状况,并通过比较提出发展绿色城市能源应用规划的相关建议。

Low-carbon generation expansion planning considering uncertainty of renewable energy at multi-time scales

With the development of carbon electricity,achieving a low-carbon economy has become a prevailing and inevitable trend.Improving low-carbon expansion generation planning is critical for carbon emission mitigation and a lowcarbon economy.In this paper,a two-layer low-carbon expansion generation planning approach considering the uncertainty of renewable energy at multiple time scales is proposed.First,renewable energy sequences considering the uncertainty in multiple time scales are generated based on the Copula function and the probability distribution of renewable energy.Second,a two-layer generation planning model considering carbon trading and carbon capture technology is established.Specifically,the upper layer model optimizes the investment decision considering the uncertainty at a monthly scale,and the lower layer one optimizes the scheduling considering the peak shaving at an hourly scale and the flexibility at a 15-minute scale.Finally,the results of different influence factors on low-carbon generation expansion planning are compared in a provincial power grid,which demonstrate the effectiveness of the proposed model.

Station-and-network–coordinated planning of integrated energy system considering integrated demand response

The integrated energy system(IES)is an important energy supply method for mitigating the energy crisis.A station-and-network–coordinated planning method for the IES,which considers the integrated demand responses(IDRs)of flexible loads,electric vehicles,and energy storage is proposed in this work.First,based on load substitution at the user side,an energy-station model considering the IDR is established.Then,based on the characteristics of the energy network,a collaborative planning model is established for the energy station and energy network of the IES,considering the comprehensive system investment,operation and maintenance,and clean energy shortage penalty costs,to minimize the total cost.This can help optimize the locations of the power lines and natural gas pipelines and the capacities of the equipment in an energy station.Finally,simulations are performed to demonstrate that the proposed planning method can help delay or reduce the construction of new lines and energy-station equipment,thereby reducing the investment required and improving the planning economics of the IES.

Energy hub-based optimal planning for integrated energy systems considering part-load characteristics and synergistic effect of equipment

Integrated energy systems(lESs)represent a promising energy supply model within the energy internet.However,multi-energy flow coupling in the optimal configuration of IES results in a series of simplifications in the preliminary planning,affecting the cost,efficiency,and environmental performance of IES.A novel optimal planning method that considers the part-load characteristics and spatio-temporal synergistic effects of IES components is proposed to enable a rational design of the structure and size of IES.An extended energy hub model is introduced based on the“node of energy hub”concept by decomposing the IES into different types of energy equipment.Subsequently,a planning method is applied as a two-level optimization framework-the upper level is used to identify the type and size of the component,while the bottom level is used to optimize the operation strategy based on a typical day analysis method.The planning problem is solved using a two-stage evolutionary algorithm,combing the multiple-mutations adaptive genetic algorithm with an interior point optimization solver,to minimize the lifetime cost of the IES.Finally,the feasibility of the proposed planning method is demonstrated using a case study.The life cycle costs of the IES with and without consideration of the part-load characteristics of the components were$4.26 million and$4.15 million,respectively,in the case study.Moreover,ignoring the variation in component characteristics in the design stage resulted in an additional 11.57%expenditure due to an energy efficiency reduction under the off-design conditions.

Energy-Optimal Braking Control Using a Double-Layer Scheme for Trajectory Planning and Tracking of Connected Electric Vehicles

Most researches focus on the regenerative braking system design in vehicle components control and braking torque distribution,few combine the connected vehicle technologies into braking velocity planning.If the braking intention is accessed by the vehicle-to-everything communication,the electric vehicles(EVs)could plan the braking velocity for recovering more vehicle kinetic energy.Therefore,this paper presents an energy-optimal braking strategy(EOBS)to improve the energy efficiency of EVs with the consideration of shared braking intention.First,a double-layer control scheme is formulated.In the upper-layer,an energy-optimal braking problem with accessed braking intention is formulated and solved by the distance-based dynamic programming algorithm,which could derive the energy-optimal braking trajectory.In the lower-layer,the nonlinear time-varying vehicle longitudinal dynamics is transformed to the linear time-varying system,then an efficient model predictive controller is designed and solved by quadratic programming algorithm to track the original energy-optimal braking trajectory while ensuring braking comfort and safety.Several simulations are conducted by jointing MATLAB and CarSim,the results demonstrated the proposed EOBS achieves prominent regeneration energy improvement than the regular constant deceleration braking strategy.Finally,the energy-optimal braking mechanism of EVs is investigated based on the analysis of braking deceleration,battery charging power,and motor efficiency,which could be a guide to real-time control.

Research on the development and planning of renewable energy in Tibet

With the rapid social and economic development of the Tibet Autonomous Region,the situation in regard to energy supply and demand is increasingly tense.Meanwhile,the development of renewable energy in Tibet has been given considerable practical significance by its peculiar ecological environment.Given the complementarity of renewable energies in Tibet,using the method of factor analysis,we derived four major factors:level of economic development,social development,industrial development,and energy endowment,which help to evaluate development conditions in different regions of Tibet.Treating these four factors equally,we used the hierarchical clustering method to determine the order of regional development.Thus we acquire a three-stage planning project for renewable energy.In the first stage,Lhasa plays a leading role in promoting the development of renewable energy,particularly that based on solar and wind energy.There are two phases in the second stage,the first being to simultaneously develop solar and wind energy in Xigaze and Nyingchi.The second is to develop solar and wind energy in accordance with the time of year in Qamdo,Nagqu,and Ali,with 1.145billion kWh electricity to be generated.The third stage is to develop energy production in Lhoka Prefecture,with 1.369billion kWh electricity to be generated.At the end of the three-stage project,consumption of available electricity will have reached 4.045 billion kwh,with major social and economic benefits.

Energy Aware Data Collection with Route Planning for 6G Enabled UAV Communication

With technological advancements in 6G and Internet of Things(IoT), the incorporation of Unmanned Aerial Vehicles (UAVs) and cellularnetworks has become a hot research topic. At present, the proficient evolution of 6G networks allows the UAVs to offer cost-effective and timelysolutions for real-time applications such as medicine, tracking, surveillance,etc. Energy efficiency, data collection, and route planning are crucial processesto improve the network communication. These processes are highly difficultowing to high mobility, presence of non-stationary links, dynamic topology,and energy-restricted UAVs. With this motivation, the current research paperpresents a novel Energy Aware Data Collection with Routing Planning for6G-enabled UAV communication (EADCRP-6G) technique. The goal of theproposed EADCRP-6G technique is to conduct energy-efficient cluster-baseddata collection and optimal route planning for 6G-enabled UAV networks.EADCRP-6G technique deploys Improved Red Deer Algorithm-based Clustering (IRDAC) technique to elect an optimal set of Cluster Heads (CH) andorganize these clusters. Besides, Artificial Fish Swarm-based Route Planning(AFSRP) technique is applied to choose an optimum set of routes for UAVcommunication in 6G networks. In order to validated whether the proposedEADCRP-6G technique enhances the performance, a series of simulationswas performed and the outcomes were investigated under different dimensions.The experimental results showcase that the proposed model outperformed allother existing models under different evaluation parameters.

Energy-Efficient Trajectory Planning for UAV-Aided Secure Communication

Wireless communication with unmanned aerial vehicles(UAVs) has aroused great research interest recently. This paper is concerned with the UAV's trajectory planning problem for secrecy energy efficiency maximization(SEEM) in the UAV communication system. Specifically, we jointly consider the secrecy throughput and UAV's energy consumption in a three-node(fixed-wing UAV-aided source, destination, and eavesdropper) wiretap channel. By ignoring the energy consumption on radiation and signal processing, the system's secrecy energy efficiency is defined as the total secrecy rate normalized by the UAV's propulsion energy consumption within a given time horizon. Nonetheless, the SEEM problem is nonconvex and thus is intractable to solve. As a compromise, we propose an iterative algorithm based on sequential convex programming(SCP) and Dinkelbach's method to seek a suboptimal solution for SEEM. The algorithm only needs to solve convex problems, and thus is computationally efficient to implement. Additionally, we prove that the proposed algorithm has Karush-KuhnTucker(KKT) point convergence guarantee. Lastly, simulation results demonstrate the efficacy of our proposed algorithm in improving the secrecy energy efficiency for the UAV communication system.

Power generation expansion planning approach considering carbon emission constraints

Decarbonization of the power sector in China is an essential aspect of the energy transition process to achieve carbon neutrality.The power sector accounts for approximately 40%of China’s total CO_(2) emissions.Accordingly,collaborative optimization in power generation expansion planning(GEP)simultaneously considering economic,environmental,and technological concerns as carbon emissions is necessary.This paper proposes a collaborative mixedinteger linear programming optimization approach for GEP.This minimizes the power system’s operating cost to resolve emission concerns considering energy development strategies,flexible generation,and resource limitations constraints.This research further analyzes the advantages and disadvantages of current GEP techniques.Results show that the main determinants of new investment decisions are carbon emissions,reserve margins,resource availability,fuel consumption,and fuel price.The proposed optimization method is simulated and validated based on China’s power system data.Finally,this study provides policy recommendations on the flexible management of traditional power sources,the market-oriented mechanism of new energy sources,and the integration of new technology to support the attainment of carbon-neutral targets in the current energy transition process.

The Five-Year Plan: A new tool for energy saving and emissions reduction in China

China has achieved economic growth while great carbon emissions reduction in recent years. Amid China's effort to reduce emissions, the Five-Year Plans have guided and motivated local and foreign forces from the government, industries, and society to work together. This paper showed that a mediumehigh economic growth gate, industry structure adjustment, and energy structure adjustment, which are guaranteed under the Five-Year Plan, all contribute to energy saving in China. The economy entered a stable growing phase during the 12 th Five-Year Plan, while the economic growth rate declined to 7.8% from 11.2% in the 11 th Five-Year Plan. Simultaneously, the CO_2 emissions growth rate declined from8.32%(2009-2012 mean) to 1.82%(2012e2014 mean). Industrial structure adjustment canceled out nearly one-third of the CO_2 emissions caused by economic growth. Under the 13 th Five-Year Plan, China will continue its energy saving efforts on the green development path, with greener quotas, a stricter implementation process, and more key projects.

Energy-Efficient Process Planning Using Improved Genetic Algorithm

Nowadays,energy consumption which closely contacts with environmental impacts of manufacturing processes has been highly commented as a new productivity criterion.However,little attention has paid to the development of process planning methods that take energy consumption into account.An energy-efficient process planning model that incorporates manufacturing time and energy consumption is proposed.For solving the problem,an improved genetic algorithm method is employed to explore the optimal solution.Finally,a case study for process planning is given.The experimental result generates interesting effort,and therefore allows improving the energy efficiency of manufacturing processes in process planning.

Energy-Efficiency Economics as a Resource for Energy Planning

The objective of this work is a multi-criteria decision-making assessment that aims to facilitate the Energy-Efficiency Economics, introducing the Analytic Hierarchy Process (AHP) as part of power-system planning tool for an energy-efficiency application. It addresses to include qualitative aspects in the decision-making agendas of energy-efficiency projects. The manuscript details the limitations of non-rigorous financial analysis and proposes an alternative for including energy-efficiency measures in discussions pertaining to the financial opportunities available to any investor, and it presents the methodology that supports the qualitative aspects and the software package used to execute this methodology. As case study a complete example including a sensitivity analysis is presented.

Energy Planning: Brazilian Potential of Generation of Electric Power from Urban Solid Wastes—Under “<i>Waste Production Liturgy</i>” Point of View

The use of Urban Solid Waste (USW) as sources of energy has acquired rising importance in current discussions of alternative energy supplies, in particular in Brazil. This paper brings to these discussions an examination of the concept of solid wastes, including their historic origins and formation, taking their social, economic and cultural characteristics into account, including point view of waste production liturgy. Consequently, a spendthrift society slanted towards the decreasing marginal utility of assets must make efficient use of its USW in order to reduce excessive output. Besides that, this document presents the Brazilian potential of urban solid waste to produce electric power.

A Trajectory Planning-Based Energy-Optimal Method for an EMVT System

In this paper,a trajectory planning-based energy-optimal method is proposed to reduce the energy consumption of novel electromagnetic valve train(EMVT).Firstly,an EMVT optimization model based on state equation was established.Then,the Gauss pseudospectral method(GPM)was used to plan energy-optimal trajectory.And a robust feedforward-feedback tracking controller based on inverse system method is proposed to track the energy-optimal trajectory.In order to verify the effectiveness of the energyoptimal trajectory,a test bench was established.Finally,co-simulations based on MATLAB Simulink and AVL Boost were carried out to illustrate the effect of energyoptimal trajectories on engine performance.Experimental results show that the robust tracking controller can achieve good position tracking performance.And these energyoptimal trajectories can save up to 40%of the energy consumption compared with the conventional camshaft valve trajectories.

Study on Objectives and Strategies for Energy Conservation and Emission Reduction in Transportation Industry during the 13th Five-Year Plan Period in Beijing

Facing increasing passenger and cargo transport demand and limited re-source in the 13th Five-Year period, how to make a breakthrough and substantial progress has become a key issue on planning and the Top-level Design. In this paper we judged and analyzed the current development and potential demand of the energy saving and emission reduction in Beijing traffic industry. Through application of energy and emission prediction model which based on the vehicle activity data, the development goals of “one drop, double control, and triple upgrade” have been put forward. In order to achieve the goal, “5 + 1” development strategies should be implemented, and we also proposed the thinking and recommendations on sustainable development of transportation.

Economic development, energy demand, and carbon emission prospects ofChina's provinces during the 14th Five-Year Plan period: Application ofCMRCGE model

This study focuses on a national regional coordinated development strategy and adopts China Multi-Regional Computable General Equilibrium model to analyze the economic and social development, energy demand, and carbon emissions of the provinces during the 14th Five-Year Plan (FYP, 2021 2025) period based on the economic development and energy demand since the New Normal. The main conclusions are the following: 1) Under the guidance of the regional coordinated development strategy, 13 provinces/municipalities are expected to have a per capita gross domestic product (GDP) of more than US$15,000, and 16 provinces/municipalities will have a per capita GDP of US$10,000 15,000. All provincial economies are expected to achieve steady and rapid development by the end of the 14th FYP. 2) The total energy consumption of the provinces is expected to reach 5.45 Gtce (excluding Tibet) in 2025, and the average annual growth rate is approximately 1.5%. The growth of energy demand will remain in low speed. The key point of energy demand will gradually shift from the eastern to the middle area, while the proportion of energy use in the western provinces will remain stable, which is consistent with the economic development stage and regional coordinated development strategy. 3) The annual average carbon intensity (mainly considering carbon emissions from energy use) of the provinces will approximately with most provinces dropping by over 4.0%. The trend of a considerable decline in carbon intensity, as observed in recent years, is expected to continue.

Investigation of Plans Shape and Glazing Percentage for the Energy Efficiency of Residential Buildings

The room’s plan shape,the area of the window,and the impact of the materials are significant parameters in determining the thermal needs of buildings.In traditional houses of the hot and dry climate of Iran,the plan shape of the room,the ratio of the window area to the floor area,and the comparison between traditional and prevalent materials have been less studied.This study investigated the thermal performance of seven different models of the plan shape,five different ratios of window area to plan area,and three material structures in a selected room of Yazd City using EnergyPlus software.Seven models have different plan shapes but the same floor area,whose thermal balance process calculations have been performed by the CTF method.The results show that the best thermal comfort conditions for the residents are at the window area to floor area ratio of 12%for the brick buildings and 15%for the buildings with thermal insulation and proposed materials.The lowest cooling and heating needs are obtained in a room with an east-west extension and a length-to-width ratio of about 1.38,which indicates the proper plan shape of the selected room.This research can be considered as a climatic strategy to improve the energy efficiency of residential buildings in Yazd.