An economic analysis method and optimal design model of the PV microgrids for industries are proposed in this paper. The economic indexes to evaluate the economic performance of the microgrids include levelized energy cost, emission reduction benefits and payback period. The optimal model considering local solar insolation level and detailed investment costs is established and applied to obtain the optimal configuration of the PV microgrids for four different operation strategies by Particle Swarm Optimization(PSO) method. The simulation results based on three months running data of a 500kW PV microgrid for industries in Guangdong, China, show that the optimal design by the proposed method can meet the technical indicators as well as the economic optimum, and thus effectively optimizing the microgrid with PVs for industries in both economic and environmental way. In addition, the proposed battery tank can not only be used to maximize the utilization of renewable energy, but also enhance the system’s ability of peak load shifting. Besides, the sensitivity of the impact of different parameters and different installed sites on the system is also performed. The results provide a reference for the application of similar projects and basis for the decision-makers of the microgrid with PVs for industries.

An economic analysis method and optimal design model of the PV microgrids for industries are proposed in this paper. The economic indexes to evaluate the economic performance of the microgrids include levelized energy cost, emission reduction benefits and payback period. The optimal model considering local solar insolation level and detailed investment costs is established and applied to obtain the optimal configuration of the PV microgrids for four different operation strategies by Particle Swarm Optimization(PSO) method. The simulation results based on three months running data of a 500kW PV microgrid for industries in Guangdong, China, show that the optimal design by the proposed method can meet the technical indicators as well as the economic optimum, and thus effectively optimizing the microgrid with PVs for industries in both economic and environmental way. In addition, the proposed battery tank can not only be used to maximize the utilization of renewable energy, but also enhance the system’s ability of peak load shifting. Besides, the sensitivity of the impact of different parameters and different installed sites on the system is also performed. The results provide a reference for the application of similar projects and basis for the decision-makers of the microgrid with PVs for industries.

Surplus distributed photovoltaic (PV) power sold to the grid with a new compensation price brings opportunities and challenges for optimal microgrid operation. This paper aims at maximizing the net operating earnings of a microgrid. Firstly, the impact of PV compensation price on the operation of microgrid is analyzed, and a decision-making scheduling model considering the subsidies of PV surplus power is established. Then the sequential quadratic programming (SQP) algorithm is utilized to solve the established model. Finally, some case studies are done based on the real data from an actual microgrid system, the differences of microgrid economic benefit with the gird accessed to residential, commercial and industrial areas are compared respectively. The sensitivity analysis is also performed to study the impact of PV capacity and on-grid price on the economic benefits of a microgrid.

Surplus distributed photovoltaic (PV) power sold to the grid with a new compensation price brings opportunities and challenges for optimal microgrid operation. This paper aims at maximizing the net operating earnings of a microgrid. Firstly, the impact of PV compensation price on the operation of microgrid is analyzed, and a decision-making scheduling model considering the subsidies of PV surplus power is established. Then the sequential quadratic programming (SQP) algorithm is utilized to solve the established model. Finally, some case studies are done based on the real data from an actual microgrid system, the differences of microgrid economic benefit with the gird accessed to residential, commercial and industrial areas are compared respectively. The sensitivity analysis is also performed to study the impact of PV capacity and on-grid price on the economic benefits of a microgrid.

Cross-regional redeployment (or relocation) of government officials has a significant effect on the local economic development and environmental protection. Based on the panel data of 31 provinces (municipalities) in China from 2001 to 2016 and the environmental pollution index obtained by Entropy method, the dynamic panel regression model was applied to verify the relationship between the officials' cross-regional redeployment and environmental pollution. The results show that environmental pollution was positively correlated with officials' relocation and their tenure after the redeployment. As the officials' tenure increases to the critical value, the positive correlation between the official's tenure and environmental pollution would change. By measuring this threshold, we find that the average critical value for China was 5.14 years, which were the same as the average tenure of Chinese officials. Moreover, the result also illustrates the difference between central eastern China and western China, with the average threshold being 4.01 years and 5.89 years, respectively. In addition, the impact of officials' cross-regional redeployment on the environment would also be affected by the initial condition of the region. According to the result, the environmental governance within the central eastern regions was better than that in the western region. In the last part of this paper, we proposed measures and suggestions, such as changing the incentive policies of officials, perfecting the local policies and the cultivate and exchange system of cadres, as well as strengthen the power of social supervision, for the sake of facilitating the healthy and green development of the regional economy.

Cross-regional redeployment (or relocation) of government officials has a significant effect on the local economic development and environmental protection. Based on the panel data of 31 provinces (municipalities) in China from 2001 to 2016 and the environmental pollution index obtained by Entropy method, the dynamic panel regression model was applied to verify the relationship between the officials' cross-regional redeployment and environmental pollution. The results show that environmental pollution was positively correlated with officials' relocation and their tenure after the redeployment. As the officials' tenure increases to the critical value, the positive correlation between the official's tenure and environmental pollution would change. By measuring this threshold, we find that the average critical value for China was 5.14 years, which were the same as the average tenure of Chinese officials. Moreover, the result also illustrates the difference between central eastern China and western China, with the average threshold being 4.01 years and 5.89 years, respectively. In addition, the impact of officials' cross-regional redeployment on the environment would also be affected by the initial condition of the region. According to the result, the environmental governance within the central eastern regions was better than that in the western region. In the last part of this paper, we proposed measures and suggestions, such as changing the incentive policies of officials, perfecting the local policies and the cultivate and exchange system of cadres, as well as strengthen the power of social supervision, for the sake of facilitating the healthy and green development of the regional economy.

海南三亚亚龙湾国家旅游度假区以冰蓄冷技术为依托,兴建区域供冷中心和区域供冷管网,由供冷中心通过供冷管网向区域范围内的酒店用户提供高质量的低价冷量,在不影响用户原有制冷系统、不需用户再投资的情况下,充分利用低谷电能实现集约化的区域能源供应和电力移峰填谷,从而实现节能和环保的目的,促进地区旅游产业与环境和谐发展.

海南三亚亚龙湾国家旅游度假区以冰蓄冷技术为依托,兴建区域供冷中心和区域供冷管网,由供冷中心通过供冷管网向区域范围内的酒店用户提供高质量的低价冷量,在不影响用户原有制冷系统、不需用户再投资的情况下,充分利用低谷电能实现集约化的区域能源供应和电力移峰填谷,从而实现节能和环保的目的,促进地区旅游产业与环境和谐发展.

Under a spot pricing based electricity market environment，a centralized charging strategy of plug-in hybrid electric vehicles（PHEVs）is proposed based on demand side response.A mathematical model is established taking into account the valley-filling effect of supply side and the userscost.A dynamic estimation interpolation based algorithm is designed to optimize the mathematical model.Finally，a simulation based on an areas predicted data of year2020is made to show that，the proposed centralized charging strategy can not only lower the peak-valley difference，but also save userscost，and achieve a win-win result.

Under a spot pricing based electricity market environment，a centralized charging strategy of plug-in hybrid electric vehicles（PHEVs）is proposed based on demand side response.A mathematical model is established taking into account the valley-filling effect of supply side and the userscost.A dynamic estimation interpolation based algorithm is designed to optimize the mathematical model.Finally，a simulation based on an areas predicted data of year2020is made to show that，the proposed centralized charging strategy can not only lower the peak-valley difference，but also save userscost，and achieve a win-win result.

Demand response and dynamic retail pricing of electricity are key factors in a smart grid to reduce peak loads and to increase the efficiency of the power grid. Air-conditioning and heating loads in residential buildings are major contributors to total electricity consumption. In hot climates, such as Austin, Texas, the electricity cooling load of buildings results in critical peak load during the on-peak period. Demand response (DR) is valuable to reduce both electricity loads and energy costs for end users in a residential building. This paper focuses on developing a control strategy for the HVACs to respond to real-time prices for peak load reduction. A proposed dynamic demand response controller (DDRC) changes the set-point temperature to control HVAC loads depending on electricity retail price published each 15 minutes and partially shifts some of this load away from the peak. The advantages of the proposed control strategy are that DDRC has a detailed scheduling function and compares the real-time retail price of electricity with a threshold price that customers set by their preference in order to control HVAC loads considering energy cost. In addition, a detailed single family house model is developed using OpenStudio and Energyplus considering the geometry of a residential building and geographical environment. This HVAC modeling provides simulation of a house. Comfort level is, moreover, reflected into the DDRC to minimize discomfort when DDRC changes the set-point temperature. Our proposed DDRC is implemented in MATLAB/SIMULINK and connected to the EnergyPlus model via building controls virtual test bed (BCVTB). The real-time retail price is based on the real-time wholesale price in the ERCOT market in Texas. The study shows that DDRC applied in residential HVAC systems could significantly reduce peak loads and electricity bills with a modest variation in thermal comfort.

Based on the time process characteristic and economic efficiency characteristic of the civilian active load system's interaction demand response，a behavior analysis mode of active load's interaction response is proposed.A demand response operation-decision model is developed to maximize the profits of users and power industries，even with social welfare taken into account.Then an evaluation index system is proposed that can represent and identify the physical features of the interactive response behavior among usersenergy demands，electricity demands and the cooperation between distributed renewable energy and grid by the decoupling response behaviors between users' energy consuming load and electric load.Finally，the effectiveness of the model and index system proposed is verified by an analysis of the residential and commercial quarters active load system's response behavior in the heavy space cold load grid，respectively，the active load system consisting of cold storage air conditioning and distributed wind generation in the heavy air-conditioning cold load grid.

Based on the time process characteristic and economic efficiency characteristic of the civilian active load system's interaction demand response，a behavior analysis mode of active load's interaction response is proposed.A demand response operation-decision model is developed to maximize the profits of users and power industries，even with social welfare taken into account.Then an evaluation index system is proposed that can represent and identify the physical features of the interactive response behavior among usersenergy demands，electricity demands and the cooperation between distributed renewable energy and grid by the decoupling response behaviors between users' energy consuming load and electric load.Finally，the effectiveness of the model and index system proposed is verified by an analysis of the residential and commercial quarters active load system's response behavior in the heavy space cold load grid，respectively，the active load system consisting of cold storage air conditioning and distributed wind generation in the heavy air-conditioning cold load grid.

区别于传统能效项目,需求响应项目的执行效果取决于项目的参与率和用户响应特性及能力。总结目前国内外各类需求响应项目中用户响应特性方面的研究进展,对其影响因素进行归类研究;介绍负荷价格弹性、替代弹性和弧弹性等3种定量用户价格响应特性的方式,并对其影响因素从时间跨度、行业类别和其他差异化特性等3方面进行分析;此外,从需求响应支撑技术、需求响应项目设计等两个大方面分析其对用户需求响应特性和能力的影响。最后,结合中国国情对于用户响应特性建模和需求响应项目设计方面提出设想和建议。

区别于传统能效项目,需求响应项目的执行效果取决于项目的参与率和用户响应特性及能力。总结目前国内外各类需求响应项目中用户响应特性方面的研究进展,对其影响因素进行归类研究;介绍负荷价格弹性、替代弹性和弧弹性等3种定量用户价格响应特性的方式,并对其影响因素从时间跨度、行业类别和其他差异化特性等3方面进行分析;此外,从需求响应支撑技术、需求响应项目设计等两个大方面分析其对用户需求响应特性和能力的影响。最后,结合中国国情对于用户响应特性建模和需求响应项目设计方面提出设想和建议。

Demand side management encourages the users in a smart grid to shift their electricity consumption in response to varying electricity prices. In this paper, we propose a distributed framework for the demand response based on cost minimization. Each user in the system will find an optimal start time and operating mode for the appliances in response to the varying electricity prices. We model the cost function for each user and the constraints for the appliances. We then propose an approximate greedy iterative algorithm that can be employed by each user to schedule appliances. In the proposed algorithm, each user requires only the knowledge of the price of the electricity, which depends on the aggregated load of other users, instead of the load profiles of individual users. In order for the users to coordinate with each other, we introduce a penalty term in the cost function, which penalizes large changes in the scheduling between successive iterations. Numerical simulations show that our optimization method will result in lower cost for the consumers, lower generation costs for the utility companies, lower peak load, and lower load fluctuations.

博弈论作为一种先进的优化工具,主要用于研究多个利益相关主体如何进行优化决策的问题。随着智能电网的快速发展,现代电力系统在发电、配电、用电等多个环节的参与者呈多样化特征。在此环境下,博弈论为多决策主体优化问题提供了新的解决途径。论文首先介绍了博弈论的基本概念和分类,然后从电力系统规划、电力市场、调度、控制等方面阐述并总结了博弈论的四项典型应用示例。最后,从可再生能源发电、微电网、需求响应、电网演化和博弈均衡求解方法等多个方面论述了值得深入研究的关键科学问题。希望该文的工作对推动博弈论在电力系统中的应用能够起到积极作用。

博弈论作为一种先进的优化工具,主要用于研究多个利益相关主体如何进行优化决策的问题。随着智能电网的快速发展,现代电力系统在发电、配电、用电等多个环节的参与者呈多样化特征。在此环境下,博弈论为多决策主体优化问题提供了新的解决途径。论文首先介绍了博弈论的基本概念和分类,然后从电力系统规划、电力市场、调度、控制等方面阐述并总结了博弈论的四项典型应用示例。最后,从可再生能源发电、微电网、需求响应、电网演化和博弈均衡求解方法等多个方面论述了值得深入研究的关键科学问题。希望该文的工作对推动博弈论在电力系统中的应用能够起到积极作用。

A planning model for the grid-connected hybrid power system based on the game theory is proposed through analysis of the characteristics of the wind power， photovoltaic generation and storage batteries in power industries. The players in the game model， i.e. wind power， photovoltaic generation and storage battery， maximize their own profits by choosing their capacities individually， taking into account the life cycle cost， the system reliability and the environment profits， etc. This paper discusses five different game scenarios， one non-cooperative game and four cooperative games， and illustrates the existence of their equilibriums. The analysis of the corresponding equilibriums indicates that the coalition values are all positive， and the payoffs of all the four cooperative games are larger than that of the non-cooperative game. It is also shown that the cooperation of wind power and photovoltaic generation is the best way to realize the reliable and cost effective generation.

A planning model for the grid-connected hybrid power system based on the game theory is proposed through analysis of the characteristics of the wind power， photovoltaic generation and storage batteries in power industries. The players in the game model， i.e. wind power， photovoltaic generation and storage battery， maximize their own profits by choosing their capacities individually， taking into account the life cycle cost， the system reliability and the environment profits， etc. This paper discusses five different game scenarios， one non-cooperative game and four cooperative games， and illustrates the existence of their equilibriums. The analysis of the corresponding equilibriums indicates that the coalition values are all positive， and the payoffs of all the four cooperative games are larger than that of the non-cooperative game. It is also shown that the cooperation of wind power and photovoltaic generation is the best way to realize the reliable and cost effective generation.