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Since the power generation structures and load characteristics in each province in China are quite different, the distribution of peak regulating resources and demands are extremely imbalance. Restricted by a low power marketization degree, peak regulating resource shortages, and transmission channel blocks, the efficient utilization of new energy is facing greater pressures. In order to improve the mutual aid in regional power grids and to obtain more precise simulation results, this paper proposes a two-layer optimization dispatching model, considering the mutual aid of peak regulation resources between each province. It determines the optimal startup mode and the units' power output in each province and obtains the power output arrangements for all the units and the technical and economic indicators. The model and the solution method are original and innovative. And it effectively solved the unequal distribution problem between the peak regulating demands and resources of each provincial power grid. Finally, taking an actual regional power grid in China as an example, the simulation results show that the proposed model can significantly improve the utilization rate of new energy, which verifies the effectiveness and feasibility of the proposed model and methods presented in this paper. [ABSTRACT FROM AUTHOR]

Clean energy has become one of the more broadly acceptable options for the future transformation of existing energy systems. The energy transformation also requires comprehensive preparatory actions. Organizing a multi-chain clean energy value chain into a complex clean energy network system is likely to be critical to the successful utilization of clean energy in the future. This article proposes a novel concept for a clean energy value co-creation system covering the entire clean energy value chain with division on power generation, energy storage, and end utilization sections. This article mainly analyzes the self-organizing evolution mechanism and value co-creation of the clean energy value co-creation system (CEVCS), which is therefore critical to the further development of the renewable energy industry. First, this article analyzes the connotation and basic structure of CEVCS and introduces the self-organizing characteristics of CEVCS. Second, the self-organizing evolution mechanism of CEVCS is discussed, which is analyzed from four aspects: evolutionary power, evolutionary path, evolutionary form, and evolutionary process. Third, this paper analyzes the information cooperative evolution process of CEVCS, defines the value order parameter, and studies how the constituent elements of CEVCS realize value creation through a synergy mechanism based on the theory of synergy. Then the dissipative structure model and information resource collaborative model of CEVCS are presented. Finally, the conclusions are given in the end. The proposed CEVCS concept would support the effective operation of the clean energy value chain within municipalities by establishing virtual energy cooperatives aimed at meeting energy needs and supporting community development. [ABSTRACT FROM AUTHOR]

Regional hybrid energy system (RHES) is an effective way to accommodate clean energy and reduce its uncertainty. It is also an important development direction for energy market reform, playing an important role in the field of energy supply and demand. Based on electricity price, thermal price, and the relationship between load supply and demand, the paper proposes an optimal scheduling model for regional energy systems to promote clean energy consumption. Firstly, the typical structure and system modules of the integrated regional energy system are introduced in detail, and the two subsystem operating models of electricity and heating are given. Secondly, a multi‐objective function that combines the economics and stability of the system is constructed. The model maximizes the economic benefits and minimizes the net load fluctuations on the basis of maximizing the consumption of clean energy. The multi‐objective singularity is realized by fuzzy membership function. The decision‐making risk caused by the uncertainty of clean energy output is analyzed by introducing robust optimization theory. Finally, the effectiveness of the proposed model is verified based on a region in northwestern China. The results show that the proposed multi‐objective model can combine different optimization demands together, maximize the economic characteristics of clean energy while properly controlling risks, and provide reasonable support for decision makers to develop optimal operation plans. [ABSTRACT FROM AUTHOR]

Developing new energy is an important way to optimize energy structure, which makes significant sense on improving energy efficiency, reducing carbon emission, and lowering external dependence degree. New energy power generation costs are generally higher than conventional ones at this time. They would quickly decrease because of their scale effects, as technology improving and the scale expanding. Referring to the developing trend of new energy power generation costs, this paper sets the minimize generation costs and pollutant emission as optimization objectives, selects primary energy consumption and new installed generation capacity of each year as decision variables, and establishes an optimization model for new energy and energy structure. By setting and calculating the optimal energy structure, new energy developing scale, generation capacity and building sequences, we can get comparative results of power generation costs under three different scenarios, namely reference scenario, energy security scenario and low-carbon scenario. And use a sensitive analysis to clear the effect of total energy consumption and non-fossil energy consumption proportion. A simulation result shows resource and environmental benefits would be greater than new energy exploration and utilization costs. The larger scale, greater benefits and the less operation cost of the energy system as well as the lower external dependence degree will occur. Therefore, China should adhere to low-carbon energy structure developing direction, to improve energy conversion and utilization efficiency, to strengthen investment in new energy and finally achieve energy development strategies and goals. [ABSTRACT FROM AUTHOR]

"Photovoltaic + energy storage" is considered as one of the effective means to improve the efficiency of clean energy utilization. In the era of energy sharing, the "photovoltaic - energy storage - utilization (PVESU)" model can create a more favorable market environment. However, the various uncertainties in the construction of the PVESU project have become the main obstacles to the development of the PVESU model. This paper aims to evaluate the risk level of China's PVESU projects through an improved Cloud-TODIM (Cloud-an acronym in Portuguese for Interative Multi-criteria Decision Making) method. First of all, 18 critical risk factors are identified using the constructed five-dimensional risk analysis model. Secondly, the improved method is used to calculate the weight of the comprehensive criteria and rank 14 PVESU alternatives. Finally, the accuracy and feasibility of the hybrid method are verified by sensitivity analysis tests concluding the loss decay coefficient adjustment and comparison analysis with the Cloud-TOPSIS(Cloud-Technique for Order of Preference by Similarity to Ideal Solution) method. Meanwhile, in terms of energy storage, some suggestions are made for the future development of China's PVESU project. This study can also provide insightful enlightenment for PVESU project investors, risk management professionals and decision makers. • The highlights stated are as follows: • Construct an evaluation system of Photovoltaic - Energy storage - Utilization (PVESU) project risk assessment. • Contribute to adding five-dimensional risk analysis method to select critical risk factors. • Propose an improved Cloud-TODIM method to analyze the risk level of PVESU projects. • Extend the research on integrated projects on the field of clean energy and energy storage. [ABSTRACT FROM AUTHOR]

Micro-grid operation mode, which is the combination of a power grid and distributed generation, is the main way for saving investment, reducing energy consumption, and improving a power system's reliability and flexibility, but it has many risks in the process of implementation. In this article, the micro-grid generation structure of a wind farm was established, a processing flow chart of an intelligent management system was drawn, and a risk management model of a micro-grid wind farm was built from the angle of cost risk, including construction of cost risk and operation cost risk models. The construction cost risk model, grid-connected operation, and isolate-operation cost risk model of a micro-grid wind farm were set up by using a mathematical model that consisted of an objective function and constraint conditions. The accuracy of the model was verified through empirical analysis. This provides a reference and mirror for solving grid-connected wind energy problems and gives an important basis for wind energy risk policy-making, and for avoiding the risks in the process of planning, design, and operation management of a wind farm. [ABSTRACT FROM AUTHOR]

• Two novel concepts of UPIoTs and non-grid-connected wind power are explored in China. • ISM is improved with G1 method to overcome the shortcomings of traditional method. • 26 influence factors about how UPIoTs has impacts on wind power are identified. • The relationship between identified factors is researched by proposed model. • Suggestions about how to promote the consumption of wind power are proposed. In the last decade, the scale and speed of development for wind power in China presented an explosive growth and has been maintaining a leading position worldwide. However, rapid development, with addition of the nature of clean energy itself, is followed by the problem of energy consumption such as wind curtailment. To improve the energy efficiency, a new pattern of wind power generation, namely the non-grid-connected wind power, is gradually accessible to the public. At the same time, proposes a novel concept of ubiquitous power Internet of things (UPIoTs) to improve the energy-using environment and quality. In the context of above proposal, to research how UPIoTs promotes the consumption of wind power especially has become a crucial task. The purpose of this paper is to identify influence factors through literature review and expert interview on the basis of relationship between the referenced two. During the process of exploring effects among factors, the improved interpretative structural modeling (ISM) coupled with fuzzy order relation analysis method (fuzzy G1 method) is constructed and adopted to make up for the shortcomings of traditional method. According to the results, three factors are considered as the most influential and some suggestions are given from these three aspects, aiming at making a contribution to the solutions in theory and in practice. [ABSTRACT FROM AUTHOR]

The optimal operation of microgrids is a comprehensive and complex energy utilization and management problem. In order to guarantee the efficient and economic operation of microgrids, a three-layer multi-agent system including distributed management system agent, microgrid central control agent and microgrid control element agent is proposed considering energy storage units and demand response. Then, based on this multi-agent system and with the objective of cost minimization, an operation optimization model for microgrids is constructed from three aspects: operation cost, environmental impact and security. To solve this model, dynamic guiding chaotic search particle swarm optimization is adopted and three scenarios including basic scenario, energy storage participation and demand response participation are simulated and analyzed. The results show that both energy storage unit and demand response can effectively reduce the cost of microgrid, improve the operation and management level and ensure the safety and stability of power supply and utilization. [ABSTRACT FROM AUTHOR]