Power Balance Of System Research Articles

Non-iterative multi-area coordinated energy and reserve allocation model for hybrid AC/DC power systems with flexible frequency operation

As the result of renewable energy natural intermittency, load shedding and renewables curtailment are inevitable to keep supply and demand balance in high penetration level power systems. Luckily, with accurate estimation and proper allocation of the reserve, power fluctuation can be smoothed appreciably. Therefore, this study presents a novel coordinated day-ahead economic dispatch model for both energy and reserve in bulk hybrid AC/DC power systems. Flexible frequency operation for each regional sub AC system is applied to estimate reserve demand, while renewable energy forecast error is described by the versatile probability distribution. Considering practical operation structure in China, a non-iterative bi-layer dispatch algorithm is proposed to share power and reserve between interconnected subsystems by applying DC tie-lines’ flexibility. This bi-layer structure is achieved through the upper layer deciding the boundary variables with aggregated generation information provided by the lower layer. Then each lower layer regional AC grid solves its own programming with the boundary variables. Simulation is carried out to verify the efficacy of the proposed dispatch model and distributed solution methodology.

CSP-IES economic dispatch strategy with generalized energy storage and a conditional value-at-risk model

To promote the efficient use of energy storage and renewable energy consumption in the integrated energy system (IES), an economic dispatch strategy for the concentrating solar power (CSP)-IES with generalized energy storage and a conditional value-at-risk (CVaR) model is proposed. First, considering the characteristics of energy storage and distributed power supply timing, a CSP-IES configuration is established by using a CSP plant to achieve thermal decoupling of the combined heat and power unit and by defining the thermal storage system of the CSP plant and the battery as the actual energy storage. Second, the fuzzy response of the logistic function is used to optimize the time-of-use tariff to guide load shifting, and the load shifting is defined as virtual energy storage. Third, the CSP-IES economic dispatch model is established to consider the carbon emission allowance model. Finally, considering the system uncertainty, a fuzzy chance constraint is used to relax the system power balance constraint, and then the trapezoidal fuzzy number is transformed into a deterministic equivalence class, and the CVaR model is used as a risk assessment index to quantify the risk cost of the system due to uncertainty. The CSP-IES economic dispatch model with CVaR is constructed. The feasibility and effectiveness of the proposed optimization model are verified by comparing various scenarios.

Multi-region dynamic economic dispatch with active power real-time balance constraint

In this paper, a multi-region dynamic economic dispatch model with power balance constraint is constructed to seek the actual reserve demand and reasonable reserve allocation method of the system by relying on the dynamic response process of the units to the power balance of the interconnected system. For this kind of dynamic optimization problem with differential equation constraints, a discrete-optimization rolling solution strategy based on scale-optimization is proposed. First, in the discrete part of the dispatching model, basing on the correlation between the continuous quantities discrete scale and the active real-time balancing effect of the dispatching scheme, a continuous quantities discrete scale optimization strategy is proposed to maintain the safe and economic operation of the system; then, for the convergence problem of the solution of the dispatching model after discretization, this paper introduces the idea of decentralized coordination optimization and the operator splitting quadratic programming (OSQP), and through the limited information exchange between the regional grid and the coordinator, the consistent coordination of consistent variables is achieved. The simulation results verify the effectiveness of the model and the solution strategy.

Energy Storage Optimization of Wind Solar Hybrid Power Generation System Based on Improved Grasshopper Algorithm

During the heating period, the solid thermal storage electric boiler is added to use the waste electricity for local heating, and the corresponding energy storage optimization model of wind solar hybrid power generation system is constructed with the maximum waste electricity contotalityption and the minimum power purchase cost as the objective function, and the contotalityption and waste electricity constraint, system power balance constraint, electric boiler power constraint, heat storage constraint, and regulation times constraint as constraint conditions. Improved moth algorithm is constructed to solve the optimization model, and a Pareto solution set with both economy and reliability is obtained. Optimal compromise solution is screened out from the Pareto solution set, and optimal configuration capacity of the thermal storage electric boiler and annual amount of electricity discarded in the system can be obtained. Thus, the power rejection in the system can be reduced, promoting widespread use of independent renewable energy power generation systems.

Forecasting China's electricity generation using a novel structural adaptive discrete grey Bernoulli model

The generation forecast helps to develop the scheduling plan of power sources, build a power balance system and ensure the adequacy of power supply to the power system at the macro level. Therefore, a novel structurally adaptive discrete grey Bernoulli model, called DHGBM(1,1), is proposed in this paper for the prediction of power generation. Firstly, the Hausdorff fractional order cumulative generation operation makes it possible to achieve new information prioritisation. As for the structure of the model, we have extended the nonlinear grey Bernoulli model with the introduction of a nonlinear dynamic structure term, which allows the model to simulate variable generation data and improves the adaptability of the model. In a comparative test of the algorithms, the well-performing differential evolution algorithm was used for hyperparameter optimisation of the model to obtain better predictive performance. Monte Carlo simulations and probability density analysis verified the excellent robustness of the model. In addition, through the simulation tests, we obtained a reasonable range of parameters for the structural terms, thus limiting the complexity of the model, and the phenomenon of model overfitting was effectively prevented. Finally, five actual cases of China's hydro, China's thermal, China's nuclear, China's wind power generation and China's electricity exports are predicted.

Co-planning of transmission and energy storage by iteratively including extreme periods in time-series aggregation

The co-planning problem of transmission and energy storage system (ESS) requires a large amount of historical and forecasted input data to account for the volatility of renewable energy and loads. However, the large input data usually make the planning problem difficult to solve, so time series aggregation is often used to reduce the computational complexity. Nevertheless, it is difficult to guarantee the reliability of operation on the whole input data. Therefore, this paper proposes an iterative method to select extreme scenarios, and designs two indicators to select extreme scenarios, considering the system power balance and peak shaving capacity situation. Based on these two indicators, the periods of maximum load shedding and the periods of maximum renewable energy curtailment will be selected as extreme scenarios in the results of the operational optimization problem. We iteratively add extreme scenarios to the set of scenarios of the planning problem until the reliability of system operation can be adequately met. At the same time, in order to ensure the effectiveness of extreme scenarios, the operation statuses of thermal units in those periods are also taken into account. Our method is tested on an IEEE RTS-24 system with some modification. The results show that our method can guarantee the reliability of the whole system and is superior to the method that simply selects extreme scenarios. Meanwhile, we also perform a sensitivity analysis of the price of energy storage.

Coordination control method to block cascading failure of a renewable generation power system under line dynamic security

The large application of renewable energy generation (REG) has increased the risk of cascading failures in the power system. At the same time REG also provides the possibility of new approaches for the suppression of such failures. However, the capacity and position of the synchronous generator (SG) involved in regulation limit the power regulation speed (PRS) of REG to the overload line which is the main cause of cascading failures, while the PRS of SG is related to the position and shedding power. REG and SGs have difficulty in achieving effective cooperation under constraints of system power balance. Particularly, the dynamic variation of line flow during power regulation causes new problems for the accurate evaluation of line thermal safety under overload. Therefore, a new strategy for quantitatively coordinating shedding power and power regulation to block cascading failures in the dynamic security domain is proposed in this paper. The control capability and dynamic security domain of the overload line are modeled, and the coordination control method based on power regulation is then proposed to minimize shedding power. The algorithm for the optimal control scheme considers the constraints of load capacity, power source capacity and bus PRS. The correctness of the proposed method is verified using case studies.

A planning scheme for energy storage power station based on multi-spatial scale model

With the continuous development of renewable energy, it has become important to make efficient use of renewable energy. However, the uncertainty and randomness of renewable energy can cause instability in the operation of power systems and can lead to the problem of abandoning PV power and wind power. To reduce the waste of renewable energy and increase the use of renewable energy, this paper proposes a provincial-city–county spatial scale energy storage configuration model based on the power supply and load situation of the power grid in recent years, which can better adapt to different scenarios. The objective function has been redesigned to take into account the differences in investment returns in different regions, with the objective of minimizing costs, making full use of energy storage devices to reduce the abandonment of renewable energy, achieving efficient use of renewable energy and ensuring system power balance. The proposed model further takes into account the difference in dispatching capacity of different regions and effectively reduces the occurrence of load cutting according to regional characteristics. Finally, the reasonableness of the model is verified by simulation with power grid data for a typical day in spring and a typical day in autumn in a region of China.

A Study on the Interaction Between “State Learning” and International Structure from the Perspective of Comparative Politics: A Case of Japan’s Taika Era Reforms and China’s Westernization Movement in the Qing Dynasty

This paper attempts to take Japans Taika Era Reforms and China’s Westernization Movement in the Qing Dynasty as positive and negative cases to explore the role of “state learning” under the pressure of different international structures and how it leads to changes in state formation. In the positive case of Japan’s Taika Era Reforms, the international structure is not a balance of power system, so Japan’s “state learning” behavior is not dominated by the consequence logic and adaptive logic of the balance of power system. Japan’s Taika Era Reforms are more due to the “elite struggle” Reformists, desire to obtain political power and “state learning” within the country, which enables Japan to feedback to the international structure through “state learning”. This case shows that the international structural pressure of the balance of power cannot effectively explain all the situations of the transformation of state formation. In the negative case of China’s Westernization Movement in the Qing Dynasty, although the pressure of the international structure forced the emergence of “state learning”, the “elite struggle” reformers in the country could not have a stable power base and their willingness to “state learning” was not strong, which led to the change of the state formation that could not be positively fed back to the international structure. The hypothesis of “cognitive structure institutional change interaction” in this paper can effectively explain that “state learning” is a situation in which China and Japan have different behaviors in the face of different international structural pressures and highlight the importance of “state learning” will and the struggle between elites within the country.

Real‐time supply‐demand schedule update and operation for generators and battery energy storage system based on forecasted and actual photovoltaic power outputs

AbstractThe photovoltaic (PV) power output might be frequently curtailed to maintain electricity supply‐demand balance in future power systems. In our previous study, we proposed a new method for updating the battery energy storage system (BESS) charge/discharge and the generator unit commitment (UC) schedules based on the forecasted and actual PV power outputs. The forecast dataset was updated every 3 h (eight times a day). Although the simulation results showed that the proposed method could reduce the supply‐demand imbalances, it was not clear whether the forecasted or actual values made contributions. Therefore, in this study, we propose and evaluate a real‐time scheduling and operation method using the forecasted and actual PV power outputs assuming that the forecasted dataset is updated only once a day. Numerical simulations of supply‐demand operations are conducted on the power system model of the Kanto area of Japan for one year. The results show that the previous study method has a slight advantage over proposed method in terms of curtailed PV energy and operational cost of thermal generators reduction, but the difference is very small, indicating that the contribution of the actual PV power outputs is greater than that of the forecasted PV power outputs.

A Novel Control Scheme Using UAPF in an Integrated PV Grid-Tied System

This article investigates the photovoltaic fed universal active power filter (PV-UAPF) system for enhancing power quality indices. A novel comb filter together with second-order generalized integrator (CFSOGI) based instantaneous power balance theory with power angle (IPBTPA) control scheme is implemented. Under distorted or adverse grid conditions, the CFSOGI effectively extracts the phase angle, frequency, and fundamental positive and negative sequence components (FPNSC) to overcome the limitations of adaptive notch filters. Here, a comb filter constitutes a cluster/group of zeros at multiple harmonic frequencies to achieve notch peaks thereby providing superior harmonic rejection ability. Whereas, IPBTPA generates the reference signals to operate the system at dual compensation strategy with or without solar PV. The power angle is used to extract the desired load voltages under grid voltage fluctuations thereby reducing the burden on the shunt converter. Moreover, the hysteresis controller generates the switching pulses based on the calculation of reference and load powers which improves the dynamic performance by maintaining system power balance and effective DC voltage regulation. Besides, reactive power compensation, suppression of harmonic currents and mitigation of grid voltage fluctuations is also carried out to strengthen the system further. The system is also tested in grid voltage interruption for islanding mode to realize a microgrid system. The overall system performance is also validated using simulation and in a real-time experimental set-up, and results are demonstrated under various conditions.

Optimal Configuration of Self-Consistent Microgrid System with Hydrogen Energy Storage for Highway Service Area

Targeting on the goal of carbon peaking and carbon neutralization, the transportation sector is facing the pressure of carbon reduction, emission reduction and energy transformation simultaneously. Building a green, flexible, self-consistent and sustainable road transportation energy integration system has become an inevitable trend for the future development in an area without power grid. This paper proposes a self-consistent micro grid system model for wind and solar power with hydrogen energy storage for a highway service area without power grid connection. On this basis, a micro grid optimal configuration model is proposed with the goal of minimizing the comprehensive cost of the micro grid in the service area, under the constraints of the battery, hydrogen energy storage system (ESS), and the power balance of the micro grid system. Particle Swarm Optimization (PSO) algorithm is employed to solve the problem for a case study to verify the effectiveness of the model and the method proposed. Experimental results show that the model proposed in this paper not only improves the renewable energy utilization rate of the system, but also improves the reliability of power supply, verifying the effectiveness of the micro grid configuration scheme for the highway service area containing hydrogen ESS.

OPERATION OF A HYBRID POWER PLANT POWERED BY RENEWABLE ENERGY SOURCES

The use of power plants powered by renewable energy sources for the power supply of real objects is of great interest among scientists around the world. The task of uninterrupted and reliable power supply to remote consumers is relevant. (Research purpose) The research purpose is studying the operation of hybrid energy complexes operating on several renewable energy sources in order to obtain an uninterrupted and reliable power source. (Materials and methods) A mathematical model of a hybrid energy complex consisting of a solar module, a wind module and an energy storage module was proposed. A mathematical model of the solar module was presented, taking into account the ambient temperature, the dustiness of solar panels, the throughput capacity of the surface above the solar cells; and a mathematical model of the wind module taking into account the efficiency of an electric synchronous generator and gearbox. The total power generated by the energy complex at any given time during the year was determined. The equation of the power balance of the power supply system was compiled. A mathematical model of the hydrogen system was shown. The amount of electricity needed to produce 1 kilogram of hydrogen has been calculated. The mass of hydrogen obtained by electrolysis was determined. The dependence of the mass of hydrogen in the storage system on time was determined. The electrical power that can be obtained from the heating element was calculated. Restrictions have been introduced regulating the mass of hydrogen stored in tanks. We have developed a scheme for the operation of a power plant with a hydrogen system. (Results and discussions) The article presents obtained by direct measurements the load schedule of the electrical receivers of the botanical garden’s own needs for the year by month. Equipment was selected to ensure the operation of the hybrid energy complex. We obtained, using data on renewable resources over the past 20 years, taking into account the outdoor temperature, the dependence of the amount of electricity generated per year by month. (Conclusions) The energy complex with an energy storage module consisting of an electrolyzer, a hydrogen storage device and a fuel cell is capable of providing reliable and uninterrupted power supply.

A Novel Stochastic Blockchain-Based Energy Management in Smart Cities Using V2S and V2G

This paper proposes a secure management framework for optimal scheduling and operation of energy systems in smart cities, which will bring balance in modern power systems. The expanded infiltration of energy systems along with stochastic performance and high data transfer rate can bring new challenges that may severely affect precise energy management. This research work investigates the optimal and secure operation of energy systems in the presence of smart transportation systems in a correlated energy system. To achieve the maximum efficiency from the transportation system, the ideas of vehicle-to-subway (V2S) and vehicle-to-grid (V2G) are utilized to develop a bilateral power flow strategy (charging/discharging or idle mode) to provide the chief charging requirements of energy systems. In this regard, the proposed model suggests a novel stochastic architecture based on unscented transformation (UT) to handle the operational uncertainties of the transportation systems when considering the correlated power generation of wind turbines (WTs). Moreover, blockchain technology is deployed to guarantee the security of data transfer within the smart city. Hence, there is a secure collaboration within all sub-systems in the smart cities, which has triggered the integrated management in this structure. The simulation results are discussed on a typical smart city test system to show the quality of the proposed model.

지정학의 신사고와 그레이트 게임

Traditional geopolitics is a geopolitics of concentration based on nation states and military power. The competition for space has been a struggle in behalf of possession for good territory. Sovereign states have been a physical and legal violence historically. Geopolitics is an academic discipline of super powers only that have a dominant position in a global world. This means balance of power system among nations and it causes the murder of a human life and destruction of a human dignity in a real world. Globalization does need transformation of a traditional geopolitics because of its multi-level orders. This paper pursues to change from military power centered geopolitics with hard resources to human centered it with soft resources composed of economy, culture, thought, information, and intelligence technology. The era of new thinking on geopolitics is coming beyond geopolitics by violence and war. From perspective of upon geopolitics of intervention-diffusion and the more, the better space to human life can be formed via peaceful methods and devices. In this respect, the possibility of human centered global geopolitics is searched through reinterpretation process of great games as an ideal type.

Strategic Participation of Active Citizen Energy Communities in Spot Electricity Markets Using Hybrid Forecast Methodologies

The increasing penetrations of distributed renewable generation lead to the need for Citizen Energy Communities. Citizen Energy Communities may be able to be active market players and solve local imbalances. The liberalization of the electricity sector brought wholesale and retail competition as a natural evolution of electricity markets. In retail competition, retailers and communities compete to sign bilateral contracts with consumers. In wholesale competition, producers, retailers and communities can submit bids to spot markets, where the prices are volatile or sign bilateral contracts, to hedge against spot price volatility. To participate in those markets, communities have to rely on risky consumption forecasts, hours ahead of real-time operation. So, as Balance Responsible Parties they may pay penalties for their real-time imbalances. This paper proposes and tests a new strategic bidding process in spot markets for communities of consumers. The strategic bidding process is composed of a forced forecast methodology for day-ahead and short-run trends for intraday forecasts of consumption. This paper also presents a case study where energy communities submit bids to spot markets to satisfy their members using the strategic bidding process. The results show that bidding at short-term markets leads to lower forecast errors than to long and medium-term markets. Better forecast accuracy leads to higher fulfillment of the community programmed dispatch, resulting in lower imbalances and control reserve needs for the power system balance. Furthermore, by being active market players, energy communities may save around 35% in their electrical energy costs when comparing with retail tariffs.

Electricity storage systems

Purpose. Analysis of the state of energy storage systems in the world, determination of prospects for their development and comparison of electricity storage methods. Research methodology. Theoretical justification and comparison of electricity storage systems taking into account the real indicators of the energy system of Ukraine as of the end of 2021. The results. Show that there is a need for a theoretical and practical approach to the implementation of storage capacities in order to maintain the balance of the electric power system. As a result of the review of the most common electricity storage devices, their features as a whole were highlighted. All of them have both advantages and disadvantages. However, in a comprehensive approach to their promotion, it is possible to obtain the greatest expected result. The most promising, from the point of view of the chain: environmental friendliness - cost - relevance - necessity, is – hydrogen. Scientific novelty. Is that the possibility of combined use of various types of battery systems with different characteristics is being considered. Practical value. The possibility of introducing battery capacities at the industrial level for more effective decentralization of the state's energy sector. Today, without the necessary infrastructure, re-equipment of existing energy-receiving and distribution stations, large-scale investments, hydrogen cannot become effective, as much as it is capable, because energy must move from the wire to the gas, and then back to the wire. That is, there is a certain vector of energy that is constantly in a "transitional" position. That is why the energy efficiency at each of the levels of converting hydrogen into electricity drops. Efficiency, under normal, normal conditions of "yesterday's" day in this case will be about 80%. To transport hydrogen, it is necessary to compress and cool it. This process takes up to 10-15% of energy. For further transformation into electrical energy, thermal energy is consumed, and as a result, electricity can be obtained with an efficiency of ~65-70%.

Dynamic Economic Environmental Dispatch of Power System Using An Improved Whale Algorithm

With the global energy crisis and environmental problems becoming increasingly serious, the construction of a new power system containing multiple renewable energy sources for power generation has become a current research direction. In this study, a dynamic economic environmental dispatch model for power systems containing wind and thermal power generation is proposed to promote renewable energy consumption while ensuring system power balance. Firstly, a comprehensive objective function that integrates system operating costs and pollutant emission targets is established, and system active balance constraints and unit output constraints are considered. Secondly, an improved whale optimization algorithm is proposed to deal with the solution problem of the dynamic economic environmental dispatch model by introducing circle chaos mapping, dynamic sine cosine factor, and polynomial variation strategy. Finally, the optimization capability of the proposed model is verified by running a unit test system. The proposed model promotes the consumption and utilization of wind and photovoltaic resources and positively impacts achieving carbon peaking and carbon neutrality.

Modeling of I‐V characteristics for crystalline silicon photovoltaic modules based on a simplified equivalent circuit and a temperature correction

AbstractElectric power generated by photovoltaic (PV) systems is generally unstable because of uncertain meteorological conditions. Stably maintaining the supply‐demand balance of power systems requires an accurate prediction of the performance of PV systems. Especially for predicting the performance of the PV systems containing modules with different electrical characteristics or installed in different angles, it is necessary to calculate the generated power of the system by combining the current‐voltage (I‐V) characteristics of each module in series and parallel. Therefore, an accurate method is required for estimating the I‐V characteristics in various meteorological conditions. In this paper, a simple modeling method of the I‐V characteristics for crystalline silicon PV modules is proposed. The I‐V characteristics can be simulated in a good accuracy for practical use based on a simplified equivalent circuit of PV modules and a temperature correction of the short‐circuit current, open‐circuit voltage, and the current and voltage at maximum power point. The validity of the proposed method is examined by comparing simulated and measured I‐V characteristics of a PV module. Furthermore, to demonstrate the effectiveness of the proposed modelling method, it was applied to simulating the power generation of a PV system containing modules installed in different angles.

A review of research considering polymorphic load response characteristics in power system

As more and more loads start to join the electricity market and the role of loads in power system balancing and regulation becomes more and more important, the study of the response characteristics of polymorphic loads becomes more and more important. This paper firstly reviews the aggregation methods for loads, introduces its parameter aggregation model using temperature-controlled loads as an example, and introduces the use of machine learning methods to first cluster and then aggregate. It then reviews methods for the study of load response characteristics, with an increasing number of neural networks and hybrid neural networks being introduced into the field. Finally, a review of load uncertainty is presented, introducing sources of load uncertainty and methods for coping with load uncertainty.