An evolution model with high proportion of renewable energy

In recent years, with a rapid growth of the generation of hydropower, wind and solar power, renewable energy has occupied more than 60% of the total installed capacity of power grids in Qinghai, Yunnan, Sichuan, Tibet and other areas. Along with the yearly increased power transmission from these provinces, the ultra-high voltage AC/DC hybrid power grids will be evolving to be the multi-DC asynchronous grid, which is a trend of future represented by the work done in Yunnan. Taking Yunnan province as an example, this article studies the operational problems related to the multi-DC asynchronous power-sending grid with high proportion of renewable energy, and describes a new secure and stable operational technology that has been applied into the grid in Yunnan. We case-study the effects of the operation after the application of such technology and evaluate its practical influences.

In this paper, a rolling planning model for high proportion renewable energy generation power systems is proposed, considering frequency security constraints, to address the frequency stability challenges posed by increased integration of wind and solar energy into the power grid under the “double carbon” goal. First, this study establishes a frequency response model for a thermal generation unit (TGU) and analyzes the impact of the high proportion of renewable energy on system frequency stability. Subsequently, a dynamic frequency security constraint is formulated, which can be used in generation planning to address the frequency issues. Second, a bi-level rolling planning model for high proportion renewable energy generation power systems considering dynamic frequency security constraints is established. The upper level focuses on investment decisions. The lower level incorporates frequency security constraints into the operational simulation to guarantee the frequency stability of the power system when making decisions on the size of newly built TGUs annually. Finally, case studies are conducted to demonstrate the validity and effectiveness of the proposed rolling planning model.

ABSTRACTThe rapid development of renewable energy has promoted the research of the integrated energy system. In particular, the joint optimal scheduling of renewable energy and traditional thermal power units is the key technology to solve the current renewable energy integration and the source network load balance. At present, the total installed capacity of cogeneration units is huge, which hinders the integration of renewable energy and the flexibility of the power grid regulation. Therefore, this paper proposes a robust optimal scheduling strategy for the plant‐level integrated energy system considering electricity‐heat balance. The wind power and solar energy are connected in parallel with the heating network of cogeneration units to decouple heat and power in a more economical and flexible way, while improving the integration of renewable energy. Based on the principle of Kang's robust optimization, robust optimization, a linear robust optimization probability density bias prediction optimization method for the plant‐level integrated energy system considering the electric‐heat balance is proposed in this paper. The dynamic nonlinear constraints in the output process of thermal and electrical loads are transformed into linear, which takes into account the conservatism of robust optimization and the economy of the objective function. The proposed optimization algorithm facilitates the integration of a high proportion of renewable energy into the power grid and is also applicable to other integrated energy systems with nonlinear constraint characteristics.

In the context of the “dual carbon” goal, a high proportion of renewable energy connected to the grid to replace traditional high-carbon units has become a general trend. Taking the high proportion of renewable energy power system as the research object, the medium and long term planning of the installed capacity of source, grid, load and storage of power system is carried out considering the two dimensions of investment and operation maintenance, and the optimization model of source, grid, load and storage of power system is established. A low-carbon dispatching model considering carbon emission and demand response of distribution network is also proposed. Firstly, considering the characteristics of distribution network receiving power from the main network, the carbon emission model of distribution network based on carbon emission flow theory is constructed, and the low-carbon index of distribution network is proposed. Secondly, the improved dynamic carbon emission factor of distribution network is proposed, which is used as a guide signal to provide reference for low-carbon electricity consumption of distribution network users. According to the characteristics of users in the distribution network, the industrial demand response model aiming at low dispatch cost and low carbon and the residential demand response model aiming at electricity consumption satisfaction and low carbon satisfaction are constructed respectively.

With the interconnection of regional grids and the increasing penetration of renewable energy, the order of the power system model is getting higher and higher, which brings great challenges to the accuracy and real‐time performance of electromagnetic transient (EMT) simulation. The simulation of power systems with a high proportion of renewable energy requires a sharp increase in the performance of the hardware platform and the parallelism of the simulation algorithm. To solve this problem, the paper proposes a fine‐grained parallel modelling method for power systems with a high proportion of renewable energy, which is inspired by the latency insertion method used in the design of large‐scale integrated circuits. And this method is implemented on GPU to achieve the component‐level and device‐level parallelized simulation of power systems with a high proportion of renewable energy. Finally, the correctness of the proposed algorithm and the CPU‐GPU cooperative architecture is verified based on an improved 118‐bus case. The cascade system of the improved 9‐bus case is used as an example to verify the superiority of the proposed algorithm in terms of simulation efficiency.

In considering of high proportion of renewable energy supply in 2050, the accelerating of energy consumption gross, source and environment can affect the energy system restrict affection are stronger. Add wind and solar to electricity energy with large amount of energy source exploitation. The energy source amount per person is lower. Considering the renewable energy amount and supply, primary energy storage and structure problem is standing out. Before the wide spread of renewable energy, Using the high-carbon energy in China can pollute seriously. Chinese energy supply and demand problem is research key point. This paper researches Chinese energy supply and demand pattern system and evaluation methodology, gives out the inner and outer influencing elements. And evaluate Chinese energy supply and demand pattern from energy gross, structure, distribution and transportation. Use energy supply synthesize radar comparison chart in certain time period. From energy security, economy, clean and efficiency, analyze the benefit comparisons of Chinese energy supply and demand pattern. This energy supply and demand pattern model will give one certain theoretical analysis and practice reference to the further high proportion of renewable energy.

response to the problems that the existing studies have not fully considered the role of hydrogen storage in the longtime and large-scale new energy consumption and the existing energy systems containing hydrogen storage have not fully considered the severe weather conditions in the scheduling, a medium-term and long-term optimal scheduling for community integrated energy system with high proportion of renewable energy and multi-type energy storage is proposed. Firstly, a typical day selection method and a typical day sequence formation method are proposed based on the traditional multi-scenario method and the year-round weather conditions; secondly, a medium-term and long-term operation state description method for hydrogen energy storage considering the internal characteristics of typical days and the external arrangement sequence of typical days is proposed; again, the architecture of the integrated energy system containing hydrogen and thermal energy storage is introduced. Based on the internal characteristics of a typical day and the external linkage of a typical day, a medium-term and long-term optimal scheduling model and solution method for the community integrated energy system with high proportion of renewable energy and multi-type energy storage are proposed. Finally, the effectiveness and practicality of the proposed method are verified through the analysis of calculation cases.

Since the importance of developing renewable energy has been highlighted these days, the penetration level of renewable energy in power systems continues to increase worldwide. Meanwhile, due to the lack of efficient means for renewable accommodation, the renewable energy consumption is far less than its power generation and thus leads to severe renewable energy curtailment. With the deregulation of the power industry around the world, market-oriented electricity trading is regarded as a potential means to promote the consumption of renewable energy. However, a well-worked electricity market adapting to renewable energy accommodation requires corresponding support policies, market mechanisms, and trading products， which has been seldom summarized in the previous works. In this paper, typical incentive policies to promote renewable energy accommodation, trading mechanisms to support the direct trading of electricity, and risk coping mechanisms to hedge potential market risks are discussed. Finally, by analyzing the existing trading modes and comparing their applicabilities in different kinds of electricity markets, suggestions are provided for the construction of an electricity market with a high proportion of renewable energy.

Chapter 9 - Modeling flexibility in electric power market

The UHVDC sending-end power grid with high proportion of renewable energy has serious transient voltage stability problems. Firstly, the structure of renewable power systems and the overvoltage protection logic of the convertor-based renewable generators are introduced. Then, the transient overvoltage characteristic of the high renewable power-penetrated UHVDC sending-end power grid under the DC blocking fault and the commutation failure is analyzed. And the mechanism of renewable generator cascading overvoltage tripping is analyzed in the meantime. On this basis, the transient voltage security index system based on the multiple-two-element table, consisting of the local index for a single node and the global index for the whole system, is established under the single fault and the multiple-fault set respectively. Finally, the effectiveness of the proposed indexes is shown by some case studies of Qinghai Power Grid in China.

To accelerate the low-carbon transformation of the power industry, a range of carbon emission reduction policies and technologies have emerged. However, the current China's carbon emissions trading (CET) policy is inadequate in encouraging power generation enterprises to take proactive measures towards emission reduction due to challenges like fixed and low carbon prices. The high proportion of renewable energy in electricity consumption also faces significant challenges due to the unpredictable nature of wind and PV energy. Therefore, this paper applies stepped CET mechanism, energy storage system (ES) system and carbon capture and storage (CCS) mechanism together to hybrid renewable energy system, aiming to study their synergistic carbon emission reduction effect. Firstly, the paper constructs the stepped CET model considering incentives and penalties. Secondly, the stepped CET model, ES system and CCS are jointly introduced into the hybrid renewable energy system. Finally, a scenario analysis is conducted to investigate the synergistic effect of various carbon emissions reduction policies and technologies in the operation of power generation systems. The results show that: i) compared with traditional CET, the stepped CET increases renewable energy consumption by 0.12% and reduces carbon emissions by 0.6%; ii) the introduction of stepped CET and ES equipment together consumes an additional 36.1% of renewable energy and reduces carbon emissions by 32.4%; iii) based on stepped CET model and ES equipment, the introduction of CCS system reduces carbon emissions by 29.4%.

The transition towards zero and net-zero buildings necessitates identifying sustainable and effective renewable energy systems to reduce the impacts of operational energy. This study analyses the environmental impacts of multiple microgrids that consist of a photovoltaic plant and a hybrid hydrogen/battery energy storage system in a grid-connected building. To this end, a three-step simulation process was proposed. The first step involved modelling the energy consumption of the building during operation. Following that, the size of components was optimised. Lastly, a comparative life cycle assessment was conducted to evaluate different self-sufficient ratios (SSR). The results show that as SSR increase, the optimised capacities of all components generally increase, although this relationship is complex, particularly as the system approaches full renewable capacity. The climate change impact initially decreases to its lowest values but then increase again towards achieving full self-sufficiency. Furthermore, the results highlight the importance of considering multiple environmental impact categories when designing renewable energy systems. A sensitivity analysis reveals that countries with carbon-intensive electricity grids can reduce climate change impacts by increasing their renewable energy penetration. However, for countries with a high proportion of renewable energy, a higher SSR may not lead to a lower climate change impact but rather exacerbate it.

As the renewable energy generation continues to grow rapidly, the traditional power system is transitioning to a new power system with a high proportion of renewable energy. Consequently, the static voltage stability problem is becoming increasingly prominent. To address this issue, voltage support by the renewable energy generation is necessary. In this paper, we first analyze static voltage stability based on single source infinite system model. Then, we establish a simplified method to calculate the reactive power demand based on the short-circuit ratio. The method is further extended to multi-infeed renewable energy power systems using impedance matrix theory. Finally, we validate the effectiveness of the proposed method by simulating the IEEE 39 node system and a multi-infeed renewable energy power system.

The increasingly complex power grid structure and the volatility caused by the high proportion of renewable energy have brought great challenges to the traditional static security assessment of power grids. To solve this problem, a multi-source data-driven power grid static security risk assessment method is proposed in this paper. Firstly, the historical operation data of the power grid, including the grid structure of the system, load power, generator power and weather information, are used to build a multi-source data set. Then, a static security assessment model is constructed using long-term and short-term memory neural network and deep neural networks, and the multi-source data sets are used for off-line training. According to the output results of the assessment model, a three-level static security risk assessment index system is then developed. Finally, the proposed method is tested through a provincial 500kV power grid. The example results show that the method proposed in this paper can effectively realize the assessment of power grid static security risks, which can be used to assist the system operators for future intelligent dispatch and control.

Denmark is a small Scandinavian country with a land area of 43,000 km2 and a population of about 5.5 million, and it is known for its high proportion of renewable energy for energy consumption. In the past 20 years, the proportion of total energy generated from renewable sources has increased from approximately 5 per cent to 17 per cent. In 2007, renewable energy production was calculated to be 130.2 petajoules (PJ), with wind power and biomass production accounting for 25.8 PJ and 90.5 PJ, respectively (see Figure 4.5.1). In biomass production, straw accounted for 18.3 PJ, wood 41.2 PJ, renewable waste 30.1 PJ and fish oil 0.8 PJ. In 2007, wind power accounted for 19.7 per cent of domestic electricity supply, a significant increase from only 1.9 per cent in 1990 (Danish Energy Agency, 2008). Therefore, the Danish government established a target of increasing the share of renewable energy to at least 30 per cent of total energy consumption by 2025 (Danish Energy Authority, 2007).