Penetration Rate Of Renewable Energy Research Articles

Hierarchical multi-objective design of regional integrated energy system under heterogeneous low-carbon policies

Fossil-to-renewable energy system transition is an inevitable future trend considering carbon dioxide emissions mitigation burdens. However, huge investment costs and insufficient policy support are still the two main barriers to further expand renewable energy penetration. To transcend these barriers, from the perspective of both policy makers and energy suppliers, this study simultaneously integrates low-carbon policy formulations and regional integrated energy system (IES) reshaping to achieve an affordable decarbonization pathways. Mixed Integer Quadratically-Constrained Programs (MIQCP) models are constructed, and hierarchical multi-objective optimization is applied to quantify local government's decision-making costs and energy suppliers' system transition costs. A new rural community in Dalian (China) is taken as a case study to capture the relationship among energy structure adjustment, energy system reshaping, and renewable subsidy and carbon tax adjustment under different CO2 emission reduction regulations. The result shows that under the same CO2 emission reduction rate, portfolio policies can benefit both the policy maker and the energy supplier by balancing the local government revenue and expenditure, and reducing the annual total costs of IES. In addition, via IESs optimization, a higher renewable energy penetration rate could be obtained and the energy supplier could achieve a competitive cost within 40% CO2 emission reduction targets.

The real cost of deep peak shaving for renewable energy accommodation in coal-fired power plants: Calculation framework and case study in China

To fulfill the commitment to carbon emission reduction, the grid penetration rate of renewable energy in China has increased rapidly. High penetration of renewable energy brings a significant challenge to the peaking ancillary services providers. In northern China, coal-fired units still play a significant role in peak-shaving, especially in areas where pumped hydropower, gas-fired power, and controllable load are limited. The current peaking ancillary service market in China cannot effectively mobilize the enthusiasm of peaking power plants. Fair calculation of the peak-shaving costs of coal-fired power plants is significant for formulating an ancillary service market mechanism. Current research on peak-shaving costs calculation of coal-fired power fleets is limited to the operating coal consumption costs, wear-and-tear costs, and the additional environmental costs (do not contain pollutant tax and ashes treatment). However, this costs calculation lacks consideration of the additional peaking coal consumption costs, the additional peaking environmental costs with pollution tax and ashes treatment, and the power output loss caused by the peak-shaving process. Therefore, this study proposes a novel calculating framework that includes all the potential peak-shaving costs of the coal-fired generating units mentioned above. To evaluate the proposed framework, a case study was conducted in a coal-fired power plant in Dalian City, Liaoning Province, China, in 2020. The results show that the total costs of peak-shaving in 2020 was only 4.96 million Yuan according to the existing method. However, according to the proposed costs calculation framework, the peak-shaving costs in 2020 should be 16.97 million Yuan. The power grid compensated 12.83 million Yuan to the power plant, and the real peaking net profits was -4.14 million Yuan, which means coal-fired power units are unprofitable under the current peaking compensation mechanism. Compared with the existing traditional costs calculation method, the proposed method could provide a more comprehensive and accurate costs accounting for the deep peak-shaving process of coal-fired units. This study may help formulate the benchmark and reasonable compensation in the peak-shaving ancillary service market.

Impact of renewable energy penetration rate on power system frequency stability

The construction of large-scale renewable energy sources has caused challenges to frequency stability of power system. This paper presents a method to evaluate the frequency stability of power system with high penetration of renewables. Based on input-to-state stability (ISS) theory, security/stability indices reflecting the frequency stability of the system are established. In addition, a simplified analysis method of local input-to-state stability (LISS)/ local input-to-output stability (LIOS) attributes is proposed based on System Frequency Response (SFR) model. Case studies are performed to verify the validity of the proposed method, and the corresponding security/stability indices are calculated.

Optimization of a weather-based energy system for high cooling and low heating conditions using different types of water-cooled chiller

A weather-based energy system consisting of a tri-generation unit, photovoltaics, and water-cooled chiller is proposed here for improving the energy and environmental performance. Together with capacities of other devices, the cooling ratio, and capacities of different types of chiller are optimized to find the ideal system configuration setting the energy and cost savings and renewable energy use as the objectives. In addition, daily and monthly operating modes with the optimal system composition are analyzed followed by a sensitivity analysis. The results show that increasing energy saving ratio improves the cost saving benefits, but the renewable energy penetration rate would decrease due to lower grid electricity consumption. The ideal system configuration in ratio optimization process has a higher gas turbine and chiller capacity resulting in higher performance than the system with capacity optimization process, or 2.7%, 1.6%, and 0.2%-unit higher of the considered indices. When increasing the specific cost of the chiller, cost saving ratio of the ideal system decreases, while the impacts on the energy savings and renewable energy use are lower. The analysis indicates that the price of grid electricity is the most sensitive factor, while the influence of carbon cost is slight.

Configuration optimization and selection of a photovoltaic-gas integrated energy system considering renewable energy penetration in power grid

Replacing a conventional energy system with an integrated energy system consisting of high-efficiency and renewable energy conversion devices could diminish the consumption of fossil fuels and mitigate environmental issues. A solar photovoltaics-gas integrated energy system using ground source heat pump and electric heater to generate cooling/heating is proposed for a low-cooling and high-heating region. To select the ideal configuration from Pareto solutions with energy, environmental and exergo-environmental optimization, the coefficient of variation and analytic hierarchy processes coupling decision-making method is used considering the variable renewable energy penetration rate in the power grid. The ideal performance between the improved and conventional methods are compared. The results demonstrate that the average energy, carbon and economic saving ratios of the Pareto solutions are 56.8%, 61.9%, and 52.0%. For each 10% increase of renewable energy penetration, the values reduce on average by 2.1%, 2.3%, and 0.5%, because of the lower fuel consumption. The ideal solution has a higher capacity of gas turbine, battery, and heat pump capacity, and the corresponding energy and carbon benefits are higher, but the exergo-environmental cost saving ratio is 8.5% lower with 0.03 $/kWh higher specific cost than in the conventional method.

A nonlinear model-based dynamic optimal scheduling of a grid-connected integrated energy system

In this study, a nonlinear model-based dynamic optimal coordinated scheduling strategy was developed for a grid-connected integrated energy microgrid on a university campus. This integrated energy system (IES) consists of power grid, photovoltaic/wind power generator, buildings, electric batteries, and heat pumps with thermal energy storages (HPTES). Peak load shifting index, a new indicator, is proposed for evaluating the capability of energy storages for peak-shaving and valley-filling of the grid power and thermal load, and the stability of the power grid with renewables. Comparison of the performances of IES under three scenarios shows that through adopting high-efficient HPTES together with an optimal coordinated scheduling strategy, the penetration rate of renewable energy and the stability of IES can be enhanced significantly; while the operation cost, peak power, grid interactive power, peak load shifting index and CO2 emissions can be reduced significantly. Moreover, compared with the optimal scheduling strategy previously developed based on a linear model, the optimal scheduling strategy developed based on a dynamic nonlinear model can help to reduce the grid-connected time of the IES containing HPTES. This study would be useful for increasing the penetration rate of renewables and the stability of grid, as well as reducing the grid-disconnected time of an IES at a low operation cost in practice.

Using multi-objective sparrow search algorithm to establish active distribution network dynamic reconfiguration integrated optimization

This study contributes to establish the dynamic reconfiguration integrated optimization model of active distribution network (ADN) and proposes a novel solving approach based on multi-objective sparrow search algorithm. Distributed generation and time-varying load have an important impact on promoting sustainable development and reducing energy loss. Therefore, this study aims to investigate the ADN integrated optimization problem in consideration of distributed generation and time-varying load to improve the ADN power quality, economic and energy benefits. First, a multi-objective sparrow search algorithm is proposed aiming at the multi-objective, multi-constraint, non-linear and high-dimensional ADN integrated optimization problem, and the superiority of the proposed algorithm is verified. Second, the mathematical model of ADN integrated optimization is constructed. Finally, multi-scenario test is conducted in the classic test system to verify the effectiveness of proposed method, and the compromise solution is determined through the technique for order of preference by similarity to ideal solution (TOPSIS). The result shows that the proposed method effectively reduces the power loss and node voltage deviation by 75.76% and 70.06%. Accordingly, this study is significance for improving the operational stability of ADN, increasing the penetration rate of renewable energy and promoting economic production.

Balance Control of SOC for MMC-BESS With Power Fluctuation Suppression, PCC Voltage Regulation, and Harmonic Mitigation in Grid-Connected Wind Farm

With the rapid increase in the penetration rate of renewable energy, the power quality of grid-connected wind farm is deteriorated seriously with power fluctuation and point of common coupling (PCC) voltage instability. The conventional solution is to use the energy storage device and the reactive power compensation apparatus to adjust separately, which complicates the system structure. Besides, an active power filter is needed additionally when harmonic pollution caused by local nonlinear load is serious. To solve these problems, this paper investigates the modular multilevel converter-based battery energy storage system (MMC-BESS), which can realize fluctuating power suppression, PCC voltage regulation, and harmonic mitigation simultaneously in grid-connected wind farm. Firstly, the topology and energy flow of MMC-BESS have been studied. Then, three-layer balance control of the state of charge (SOC) is proposed, which is essential to maintaining the normal operation of the device. Finally, the overall control of MMC-BESS applied in the grid-connected wind farm is given. Plenty of experimental results are obtained from a downscaled MMC-BESS prototype, which validate the effectiveness of the proposed control strategy.

A Fast Calculation Method for Long-term Security-constrained Unit Commitment of Large-scale Power Systems with Renewable Energy

With the increase in the penetration rate of renewable energy, the planning and operation of power systems will face huge challenges. To ensure the sufficient utilization of renewable energy, the reasonable arrangement for the long-term power generation plan has become more crucial. Security-constrained unit commitment (SCUC) is a critical technical means to optimize the long-term power generation plan. However, the plentiful power sources and the complex grid structure in large-scale power systems will bring great difficulties to long-term SCUC. In this paper, we propose a fast calculation method for long-term SCUC of large-scale power systems with renewable energy. First, a method for unit status reduction based on temporal decomposition is proposed, which will reduce plenty of binary variables and intertemporal constraints in SCUC. Then, an efficient redundant constraint identification (RCI) method is developed to reduce the number of network constraints. Furthermore, a joint accelerated calculation framework for status reduction and RCI is formed, which can reduce the complexity of long-term SCUC while ensuring a high-precision feasible solution. In case studies, numerical results based on two test systems ROTS2017 and NREL-118 are analyzed, which verify the effectiveness and scalability of the proposed calculation method.

Flexible optimal scheduling of power system based on renewable energy and electric vehicles

The increase in the penetration rate of renewable energy (RE) and the number of electric vehicles (EVs) has created problems for the balance of energy supply and demand of the power system. To solve this problem, it is necessary to evaluate the flexibility of the power system and optimize scheduling flexible resources to enhance the flexibility of the system. This paper proposes a power system flexibility optimization scheduling strategy considering RE and EVs. First, the models of RE and EVs charging load are established. Second, it analyzes the flexibility of the power system and proposes system flexibility evaluation indexes taking into account RE and EVs charging load. Finally, an optimal scheduling model of the power system is established. The improved particle swarm optimization (PSO) algorithm is used to solve it. The optimization results show that the proposed strategy can effectively improve the flexibility of the power system.

Impact of renewable energy penetration rate on power system transient voltage stability

Transient voltage stability of power system with high penetration of renewable energy faces challenges. This paper proposes a method for quantitatively evaluating the impact of renewable energy penetration rate on transient voltage stability. Based on input-to-state stability (ISS) theory, security and stability indices are constructed to evaluate the stability characteristics, and a quantitative transient voltage stability assessment framework for power system with high penetration of renewable energy is established. Case studies are performed on MATLAB/Simulink, and security/stability indices under different renewable energy penetration rates are calculated. Finally, the critical scale of renewable energy integration is obtained through the coupling relationship between stability characteristics and renewable energy penetration rate.

Research on the influence of resilient grid learning ability on power system

In recent years, as the penetration rate of renewable energy has become higher and higher, the amount of power electronic equipment access has increased, and the power system has shown obvious “double high” characteristics, this puts forward higher requirements for the safe and stable operation of the power system. Based on the current background and research, this paper starts with the concept of resilient grid and studies the influence of the learning ability of resilient grid on the power system. First of all, this article analyzes the driving factors of learning ability from two perspectives of scientific and technological progress and policy orientation. Among them, scientific and technological progress includes internal driving and external driving, and policy orientation includes macro-level and micro-level; Secondly, this paper studies the influence of various factors on the restoration of the distribution network and the power market, and proves it through calculation examples; Finally, this paper summarizes and looks forward to the significance and role of learning driving factors in the construction of new power systems.

Optimal configuration and diversification of wind turbines: A hybrid approach to improve the penetration of wind power

Literature indicates a decline in the market value of wind power with increasing market penetration. Two promising measures to mitigate this market value drop are system-friendly turbines and geographic diversification. This study analyzes the combined potential of these two measures, introduced in this paper as the hybrid approach, to simultaneously improve market values, and to reduce system costs and the overall subsidy need in Germany. Therefore, promising diversification regions and site optimal turbine configurations are identified. The corresponding market values, levelized cost of electricity and system costs are predicted for variable renewable energy penetration rates of up to 65% (2030). The analysis shows that the market value drop in diversified regions using system-friendly turbines is less severe. Furthermore, the hybrid approach results in system cost and subsidy savings. Additional sensitivities show that the dominant share of the hybrid approach benefits can be attributed to the use of system-friendly turbines as only a small fracture of the hybrid approach savings is realized when using standard turbines instead of system-friendly ones. This leads to the conclusion that geographic diversification alone is not a promising approach to improve system costs and overall market values in Germany.

Feasibility of Low Carbon Renewable Energy City Integrated with Hybrid Renewable Energy Systems

This study evaluated the energy saving potential of renewable energy generation systems based on integrated solar energy in an urban environment. The solar city concept was implemented using photovoltaic (PV) and solar thermal systems. As a case study, the Sejong national pilot smart city in South Korea was selected to evaluate the renewable energy penetration rate. For evaluating the proposed renewable energy systems, the electrical and thermal loads of the smart city were estimated using field measurement data. Then, the renewable energy penetration rate of the city was evaluated. The HomerPro software was used to analyze the PV generation and operating energy consumption of the natural gas (NG) generator with a district heating network. The thermal load-supporting potential of the solar thermal system was estimated using the TRNSYS software. The results showed that the proposed urban integrated renewable energy system could meet over 30% of the renewable energy penetration rate and the levelized cost of energy and total net present cost was 7% lower than the base case system (i.e., NG generator). The proposed system also exhibited 38% less CO2 emissions than the base case system.

Research of renewable energy penetration rate in integrated energy stations

A multi-energy plant combines renewable energy generation equipment, a charging station and a charging station with storage. This paper discusses integrated power systems that make full use of existing substations and support the construction of data centers, energy storage, 5g base stations, photovoltaic power plants, wind farms, gas turbines, etc., to create an advanced integrated energy system that enables the integration and sharing of resources and increases energy efficiency. The simulation results confirm that the integrated power plant system plays an important role in increasing the share of renewable energy production. Self-generation and control can in principle achieve 100% solar electricity consumption, and energy storage devices play a key role in renewable energy consumption.

마이크로그리드 간 P2P 에너지 거래를 위한 거래 운영 알고리즘

Research on microgrids for efficient use of distributed resources and renewable energy is being actively conducted. In domestic, FIT(Feed-in-Traiff) was applied to increase the penetration rate of renewable energy and distributed resources, and research is being conducted to enable efficient operation through predict of power generation, demand forecast and anomaly detection algorithm by combining with AI to improve the stability of MG operation. A electric power transaction model between MGs, like P2P(peer to peer) trading, has been proposed, but it is still incomplete. In this paper, we propose electric power transaction model between MGs. A correlation and dependence between weather elements and loads is performed and a load prediction model is proposed. In addition, we propose a transaction calculation algorithm that determines the transaction unit price for P2P energy transactions between MGs and a power transaction model which is an optimal matching algorithm for transactions between MGs where both sellers and buyers generate profits.

측정오차로 인한 계통 영향 최소화를 위한 전력 민감도 기반 STATCOM 운영

In recent, renewable energy has received considerable attention worldwide due to the ‘Global Warming of 1.5oC’. There are still many challenges to be solved, however, to increase the penetration rate of renewable energy in the power system. Above all, most of the renewable energy DGs even aggravate the grid voltage from the intermittency of variable renewable energy sources rather than regulate the voltage as the conventional generators did. This paper proposes power-sensitivity-based STATCOM operation to minimize grid impact from measurement noise. The proposed method realizes seamless control of the voltage by compensating with the reactive power when the power generation or load consumption is changed. To achieve the proposed method, the reactive power references of the STATCOMs are operated based on the power sensitivities. As the result, it can be accomplished that constant voltage control even if high penetration of renewable energies. The proposed method is verified with several case studies that are based on a microgrid with practical data from a real island power system. The verification is carried out using the power system computer aided design and electromagnetic transient including DC (PSCAD/EMTDCTM) simulation software.

Power to gas: an option for 2060 high penetration rate of renewable energy scenario of China.

Replacing conventional fossil fuel power plants with large-scale renewable energy sources (RES) is a crucial aspect of the decarbonization of the power sector and represents a key part of the carbon-neutral strategy of China. The high penetration rate of renewable energy in the electricity system, however, implies the challenges of dealing with the intermittency and fluctuation of RES. Power to gas (P2G), which can convert surplus renewable power into a chemical form of energy (i.e., synthetic gas), can help handle this challenge and supply new energy carriers for various energy sectors. By modeling three potential 2060 energy mix scenarios in China, this paper aims to describe the possible contribution of the high penetration rate of renewable energy combined with P2G in the future sustainable energy system. Different schemes are listed and compared, and the results are used in a basic economic evaluation of the synthetic gas production cost for the P2G plants. Ideally, nearly 18 million tons of carbon dioxide would be recycled and transformed into methane (around 9.37 km3) annually in China. Considering a zero price for the excess renewable power and future costs of the components, the levelized cost of energy (LCOE) of the final production of methane is estimated at 0.86 $/m3SNG.

Dynamic economic emission dispatch considering renewable energy generation: A novel multi-objective optimization approach

This study contributes to construct the mathematical model of hybrid dynamic economic emission dispatch (HDEED) considering renewable energy generation and propose a novel solving approach based on enhanced moth-flame optimization algorithm. Renewable energy power generation technology has an important impact on reducing pollutant emissions and promoting sustainable development. Therefore, this study aims to investigate the HDEED problem in consideration of renewable energy generation and improve the economic and environmental benefits of the power system. First, a moth-flame optimization algorithm based on position disturbance updating strategy (MFO_PDU) was proposed aiming at the non-convex, non-linear and high-dimensional characteristics of HDEED problem. Second, the mathematical model of HDEED on the basis of Wind-Solar-Thermal integrated energy was constructed, while taking into account the valve point effect, equality constraints and inequality constraints. Finally, three cases including test systems of different scales were formulated and employed to verify the proposed approach, and the compromise solution was determined through membership function. The results revealed that the fuel cost obtained by the MFO_PDU algorithm was 11.31%, 4.01% and 5.27% smaller than those of HHO, TSA and MFO algorithms for small-scale test system. Accordingly, the research outcomes contribute in reducing the fuel cost and pollutant emissions of power generation system, and further improving the utilization and penetration rate of renewable energy.

Chance-Constrained Economic Dispatch Considering Curtailment Strategy of Renewable Energy

Chance-constrained economic dispatch (CCED) is widely used to cope with uncertainties brought by renewable energy sources. In CCED, security of power system is guaranteed by restricting risks under permitted level. As the penetration rate of renewable energy increases rapidly, the CCED model may be infeasible because of inadequate system reserve and/or transmission congestion under certain circumstances. Therefore, the curtailment of renewable energy is indispensable to guarantee security in some scenarios for power systems with high penetration of renewable energy. To address this crucial issue, this paper proposes a novel CCED model, where generation of conventional units and curtailment strategies of renewable energy are co-optimized to minimize total operational cost and restrict operational risks. An efficient solution method is developed to schedule generation and curtailment sequentially, in which tractable optimization models are formulated for each step. Numerical tests demonstrate that the proposed model can significantly reduce the probability of emergency control of curtailment compared with conventional CCED models. Furthermore, this solution method also outperforms scenario-based method with significantly improved computational efficiency and higher-quality solution.