Valley Electricity Research Articles

Muti‐units day‐ahead scheduling involving the pumped storages and considering deep‐load regulation

AbstractThis paper presents a day‐ahead scheduling for multi‐energy entities. The deep load regulation involving pumped storages, which refers to deep peak regulation, is adopted to address the impact of wind power and photovoltaic (PV) uncertainties, thereby improving the economic efficiencies of day‐ahead dispatching. And the impact of different peak valley electricity price differences on the peak shaving effectiveness of pumped storage energy was studied. Firstly, the multi‐scenario random programming method is applied to solve the prediction uncertainties of wind power and PV output in the day‐ahead. Subsequently, the multi‐scenario set of day‐ahead wind power and PV output and the load forecasting curve are considered. A pumped storage scheduling model is then established integrating the hydropower, thermal power and pumped storage. The optimal generation scheduling of pumped storage and thermal units is determined by minimizing load fluctuations and peak shaving costs. Finally, a local power grid in the Hunan province of China is selected for verification. It is shown that the proposed model can effectively accommodate the fluctuation of renewable energy output, reduce the peak regulating pressure of thermal units, and improve the operational economy of the power system.

A charge and discharge control strategy of gravity energy storage system for peak load Cutting

Gravity energy storage is a type of energy storage method that utilizes gravitational potential energy to store energy. In recent years, it has been widely concerned by scholars and enterprises at home and abroad for its unique advantages. From the perspective of long-term profit, the economic analysis of the gravity energy storage system is essential. In previous studies, only some specific economic models are available for describing the gravity energy storage system. This article proposes a revenue model for the gravity energy storage system first. Then, suggest a method for operating and scheduling a decentralized slope-based gravity energy storage system based on peak valley electricity prices. This method aligns with the current business model of using user-side energy storage to participate in power system auxiliary services. Last, verify the feasibility of the process through analysis. This study will make a beneficial attempt for the market promotion and application of gravity energy storage.

A control strategy for peak clipping and valley filling based on DC microgrid

Abstract In this paper, the peak clipping and valley filling control strategy for DC microgrid is proposed. The purpose of the proposed control strategy is to make the power system run more smoothly while reducing the cost of electricity. The working mode of the DC microgrid is determined by the peak-valley time of the electricity cost. By distinguishing different periods of time, the charging and discharging of the battery are controlled, and the difference between the peak and valley electricity prices is earned for the users. The maximum power was extracted from photovoltaic panels by P&O (Perturb and Observe) MPPT algorithm, and SPWM technology based on droop control strategy was adopted. The system is simulated in matlab/simulink environment, and the feasibility of the control strategy is verified.

Operation optimization of cogeneration microgrid based on deep reinforcement learning

Abstract The deep Q learning method is adopted to transform the microgrid model into the Markov decision model to realize the coordinated management and energy optimization of the microgrid. For the problem of the Markov decision model, we cleverly divide the working state of the gas turbine into different gears to meet its requirements. To reduce the fitting difficulty and improve the result accuracy and convergence stability, a linear penalty term was added to the reward function. Considering the operating and environmental costs, in addition to the purchase and sale price of a large power grid, peak and valley electricity price and operation constraints, we further reduce the peak and valley difference and reduce the operating cost. Finally, the output of the battery and the output of the distributed power supply are obtained through simulation verification. Through the peak-shifting and valley-filling function of the battery, it can effectively deal with the fluctuation of peak and valley electricity prices, reducing the peak and valley difference of electric heating load, and providing strong support for sustainable energy management.

The Effects of Different Durations of Night-Time Supplementary Lighting on the Growth, Yield, Quality and Economic Returns of Tomato.

To achieve higher economic returns, we employ inexpensive valley electricity for night-time supplementary lighting (NSL) of tomato plants, investigating the effects of various durations of NSL on the growth, yield, and quality of tomato. Tomato plants were treated with supplementary light for a period of 0 h, 3 h, 4 h, and 5 h during the autumn-winter season. The findings revealed superior growth and yield of tomato plants exposed to 3 h, 4 h, and 5 h of NSL compared to their untreated counterparts. Notably, providing lighting for 3 h demonstrated greater yields per plant and per trough than 5 h exposure. To investigate if a reduced duration of NSL would display similar effects on the growth and yield of tomato plants, tomato plants received supplementary light for 0 h, 1 h, 2 h, and 3 h at night during the early spring season. Compared to the control group, the stem diameter, chlorophyll content, photosynthesis rate, and yield of tomatoes significantly increased upon supplementation with lighting. Furthermore, the input-output ratios of 1 h, 2 h, and 3 h NSL were calculated as 1:10.11, 1:4.38, and 1:3.92, respectively. Nonetheless, there was no detectable difference in yield between the 1 h, 2 h, and 3 h NSL groups. These findings imply that supplemental LED lighting at night affects tomato growth in the form of light signals. Night-time supplemental lighting duration of 1 h is beneficial to plant growth and yield, and its input-output ratio is the lowest, which is an appropriate NSL mode for tomato cultivation.

Clean energy pipeline energy storage system and its economy

The economic problem of a clean energy heating system under a peak and valley electricity pricing system is investigated, and a pipe network energy storage system is correspondingly proposed to solve this problem. The system makes use of large-capacity primary network pipe network water storage to store heat during the valley electricity hours when the electricity price is lower, and releases the stored heat to supply heat during the peak electricity hours when the electricity price is higher, with a view to reducing the operating time of the heating system during the peak electricity hours when the electricity price is higher. The principle of the system and the efficient regulation scheme are given, and a mathematical model of primary pipe network energy storage and release is established, and the reliability of the model is verified with a heating project in Qingdao as an example, and the results show that the maximum temperature deviation of the return temperature of the primary pipe network obtained by the calculation of the energy storage and release model is 0.23 °C, and the maximum temperature hysteresis error is in 15 %, which meets the requirements of engineering practice. Based on the energy storage model, the simulation of the actual heating economy of the project using the pipe network energy storage system was carried out, and the results showed that compared with the original scheme based on the maximum heat load adjustment of the proportion of heating units and boilers, the electricity consumption of the project using the pipe network heat storage scheme was increased by 18.8 % in the whole heating season, the total operating costs were reduced by 14.5 %, with an annual saving of 800,600 yuan in operating costs, and the payback period for the investment was relatively short, at 2.1 years, which is of good economy.

Self-operation and low-carbon scheduling optimization of solar thermal power plants with thermal storage systems

Photo thermal power generation, as a renewable energy technology, has broad development prospects. However, the operation and scheduling of photo thermal power plants rarely consider their internal structure and energy flow characteristics. Therefore, this study explains the structure of a solar thermal power plant with a thermal storage system and analyzes its main energy flow modes to establish a self-operation and low-carbon scheduling optimization model for the solar thermal power plant. The simulation results of the example showed that for the self-operating model oriented towards power generation planning and peak valley electricity prices, the existence of a thermal storage system could improve the power generation capacity and revenue of the photovoltaic power plant. For example, when the capacity of the thermal storage system was greater than 6 h, the penalty for insufficient power generation in the simulation result was 0 $, and the maximum increase in revenue reached 84.9% as the capacity of the thermal storage system increased. In addition, when the capacity of the thermal storage system increased from 0 to 8 h, the comprehensive operating cost decreased from 1635.2 k $ to 1224.6 k $, and the carbon emissions decreased from 26.4 × 103 ton to 22.1 × 103 ton. Compared with the existing literature, this study provides a more comprehensive and systematic solution through detailed energy flow analysis and optimization model. The research has practical and far-reaching significance for promoting the development of clean energy technology, improving the sustainable utilization of renewable energy, and optimizing the overall performance of the energy system.

Low-carbon optimal dispatch of campus integrated energy system considering flexible interactions between supply and demand

To solve the problem of coupled and coordinated dispatch of multi-energy between campus integrated energy system operator and users. A bi-level Stackelberg low-carbon economic dispatch model with horizontal and vertical integrated demand response and dynamic supply and demand multi-energy pricing (DSDMEP) is proposed. Firstly, the DSDMEP is established to effectively coordinate the interests of the upper CIESO and lower users. Secondly, the combined heat and power containing the power to gas and carbon capture system and the reward and penalty stepped carbon trading mechanism (SCTM) are introduced on the energy supply side to minimize carbon emissions. Then, the HVIDR is introduced to the users to increase the energy coupling and adjustable price characteristics of supply and demand. Finally, the results show that the proposed model compared to other scenarios has its carbon emissions reduced by 21.72%, the benefits of CIESO are increased by 27.86%, and the cost of the users is reduced by 6.9%. This paper also provides a multi-angle sensitivity analysis of the impact of different parameters of the SCTM on the operation of the campus integrated energy system (CIES), as well as a sensitivity analysis of the HVIDR and peak and valley electricity price difference.

Demand side management full season optimal operation potential analysis for coupled hybrid photovoltaic/thermal, heat pump, and thermal energy storage systems

In view of the excessive energy consumption caused by building demand-side matching, it is very important to combine energy storage systems and renewable energy to improve equipment energy efficiency and building energy efficiency, and correctly match demand-side management (DSM). This paper combines the energy coupling system with demand-side management to get the best balance of energy production and power grid load pressure. A photovoltaic/thermal coupling system that can be combined with heat pumps and energy storage in a single building is proposed, and a dynamic simulation model is developed to describe its operating performance. The simulation results show that the coupling system has a good energy-saving effect in the heating and cooling seasons. The energy-saving potential of the applied management strategy is 41.77 %, and the energy-saving rate is increased by 9.56 %. The cost and energy usage in different configurations are analyzed to evaluate the feasibility of combining the coupled system with demand-side management applications. It is found that the energy consumption of the coupled system is low, and the economy of its configuration selection is related to the peak and valley electricity prices, and the corresponding optimal configuration reduces the economic consumption by 58.89 % per year, which is 27.18 % less than that when the management strategy is not implemented. In addition, due to the utilization of hybrid PV/thermal energy and the smoothing effect of the temperature after heat energy storage, the payback period of the coupled system is as low as 6.23 years without relying on specific tariff factors.

Strategic investment in electric vehicle charging service: Fast charging or battery swapping

With the increasing adoption of electric vehicles (EVs), there is a growing need for public charging infrastructure. As a result, significant investments have been made in charging services, particularly, fast-charging (FC) and battery-swapping (BS) services. This paper examines the impact of technical and operational factors, as well as market conditions, on the pricing and profitability of each service to explore whether and how EV charging service providers should invest in these emerging charging services. The analysis with benchmark to private-use slow-charging (SC) services reveals that if the valley electricity price is high and the potential market size is small, lowering service costs does not make BS services a viable option. When the valley electricity price is low, reducing battery loss will not give FC services an advantage. However, in such scenarios, BS services can gain an edge by decreasing service costs. Interestingly, even if both SC and BS services are negatively affected by higher valley electricity prices, the impact on the profitability of BS services is more severe. Our results provide implications for the development of public EV charging service infrastructure. We recommend that implementing energy storage solutions can help alleviate the negative consequences of escalating valley electricity prices and wider peak–valley electricity price differences on BS services and FC services, respectively.

Optimizing Energy Usage and Smoothing Load Profile via a Home Energy Management Strategy with Vehicle-to-Home and Energy Storage System

This study investigates an energy utilization optimization strategy in a smart home for charging electric vehicles (EVs) with/without a vehicle-to-home (V2H) and/or household energy storage system (HESS) to improve household energy utilization, smooth the load profile, and reduce electricity bills. The proposed strategy detects EV arrival and departure time, establishes the priority order between EV and HESS during charge and discharge, and ensures that the EV battery state of energy at the departure time is sufficient for its travel distance. It also ensures that the EV and HESS are charged when electricity prices are low and discharged in peak hours to reduce net electricity expenditure. The proposed strategy operates in different modes to control the energy amount flowing from the grid to EV and/or HESS and the energy amount drawn from the HESS and/or EV to feed the demand to maintain the load curve level within the average limits of the daily load curve. Four different scenarios are presented to investigate the role of HESS and EV technology in reducing electricity bills and smoothing the load curve in the smart house. The results demonstrate that the proposed strategy effectively reduces electricity costs by 12%, 15%, 14%, and 17% in scenarios A, B, C, and D, respectively, and smooths the load profile. Transferring valley electricity by V2H can reduce the electricity costs better than HESS, whereas HESS is better than EV at flattening the load curve. Transferring valley electricity through both V2H and HESS gives better results in reducing electricity costs and smoothing the load curve than transferring valley electricity by HESS or V2H alone.

Field energy performance of cold storage in East China: A case study

The energy consumption cold storage is rapidly increasing due to fast development of cold chain. However, the energy consumption composition, energy efficiency, and cooling load composition of cold storage are not clear, which become a barrier for increasing energy efficiency in cold storage. In the previous research, an accurate and convenient field cooling capacity test method is lacking. In this study, an extended compressor energy conservation –compressor volumetric efficiency method was proposed to calculate the cooling capacity of each cold room in centralized cold storage. A cold storage system in Jiangsu Province was selected for field testing. The operational characteristics and composition of electricity consumption were investigated firstly. The field test results show that the refrigeration system accounts for 80% of the total energy consumption of cold storage. Statistical analysis revealed that the valley electricity price interval and compressors accounted for 64.0% and 67.3% of the total energy consumption of the refrigeration system, in time and space, respectively. Furthermore, during the transition season (4/1–5/31), with a cold storage temperature of −18 ℃, the average daily energy efficiency ratio of the refrigeration system in the cold storage is 1.33 kWh·kWh−1. An analysis of the composition of the refrigeration load was also conducted, and the results indicated that for the overall cooling load of the cold storage, the envelope cooling load, door leakage & personnel operating cooling load, income cargo cooling load, and electrical equipment cooling load accounted for 26%, 27%, 32%, and 15%, respectively.

Design and analysis of a novel liquefied air energy storage system coupled with coal-fired power unit

With its large scale and high flexibility, liquefied air energy storage is very suitable for integrated operation with existing power generation systems to improve the regulation ability of the grid. A novel liquified air energy storage system coupled with coal-fired power unit for heat exchange through the water/steam and the compression/expansion air is proposed. The thermodynamic model of a novel liquified air energy storage system is established with a 307 MW coal-fired power unit as the coupling object. And the parameters design and performance analysis of the coupling system are carried out. The results show that the efficiency of the system can reach 51.64 %. At this time, the corresponding energy storage/release pressure is 18/7.2 MPa. The highest return on investment of the system can reach 19.59 %, and the shortest dynamic payback period can reach 4.73 years. The sensitivity analysis shows that decreasing the heat transfer end difference of the regenerator and increasing the adiabatic efficiency of the compressor are conducive to reducing the exergosy destruction of equipment and improving the efficiency of the system. It is beneficial to improve the economic performance of the system to increase the difference between peak and valley electricity prices and the amount of peak regulation subsidy.

Role of different energy storage methods in decarbonizing urban distributed energy systems: A case study of thermal and electricity storage

Aiming at identifying the difference between heat and electricity storage in distributed energy systems, this paper tries to explore the potential of cost reduction by using time-of-use electricity prices and a variety of energy storage methods. The current situation is defined as basic situation which is purchasing electricity for all loads in real-time (Scenario 1). For the Scenario 2, battery energy storage to utilize valley electricity is considered (Scenario 2). Besides, considering that the price of the battery is relatively high, heat and cold pumps are also included as well as thermal storage to provide dispatchable heat and cold (Scenario 3). Lastly, as a representation of renewable heat, the solar collector was used to collect solar heat for supplying heat and cold (via absorption refrigeration) to the building (Scenario 4). Using levelized cost of electricity (LCOE) and payback time of scenarios as the main indicators, the influence rules of key parameters is analyzed and the capacity is optimized, aiming to explore the sensitive reaction of scenarios to components and compare the performance of different scenarios on typical days in four seasons. Based on the results, the utilization of valley electricity and storage methods in different scenarios can reduce the LCOE of commercial buildings. When the lifetime is considered as 10 years, Scenarios 2, 3, and 4 can reduce the LCOE from 0.9795 CNY/kWh (Scenario 1) to 0.9183, 0.6791 and 0.7748 CNY/kWh, respectively. Scenario 2 is sensitive to the lifetime of the battery. Scenario 4 has great potential for a long lifetime such as 20 years and it is also sensitive to the price of components.

Thermoeconomic analysis and multiple parameter optimization of a combined heat and power plant based on molten salt heat storage

The global energy supply is transitioning to sustainable, low-carbon energy. Power-to-heat technology with molten salt thermal energy storage (TES) is a potential way to accommodate renewable power, and the stored heat can be converted to heat and electricity for residential heating and power supply with a combined heat and power plant (CHP). In this study, a CHP-TES system with valley electricity as the input energy source is proposed. Thermodynamic models are developed, and an economic evaluation index is established by considering electricity price, heat price, TES scale, and CHP layout. Then, multiparameter optimization of the proposed CHP-TES system is conducted with the genetic algorithm, and the energy-exergy-economic feasibilities of the system are evaluated. The CHP-TES system can operate under CHP and condensing modes in heating and non-heating periods, and its output power can be regulated during peak and valley load time, respectively. The exergy efficiency of the CHP-TES system is 45.07% and 36.67% in condensing modes with the peak and valley output power, respectively. The exergy efficiency of the CHP-TES system is 46.16% and 42.96% in CHP modes with the peak and valley output power, respectively. The exergy is mainly destructed in the electric heater, which accounts for over 65% of the total exergy loss in all operation modes. The equipment investment of the TES, steam generator, and CHP systems account for 87.59%, 3.53%, and 8.88% of the total, respectively. The electric heater takes the largest portion of the total equipment investment, which accounts for 37.99%. When the peak-valley electricity price changes from 0.121 $ kWh−1 to 0.259 $ kWh−1, the net present value increases from $592 million to $5.79 billion.

A method for sizing air source heat pump and electric boiler considering the peak and valley electricity prices

In a combined air source heat pump and electric boiler heating system, the capacity an oversized heat pump increases investment costs but decreases operation costs, and vice versa. Most current equipment selection methods are complex and ignore the impact of the peak valley price policy on system costs. This often leads to the selection of oversized equipment for the actual project, resulting in an increase in the total cost of the system. Therefore, we propose a new calculation method. The optimal number of non-guaranteed days for the air source heat pump (OGD) was used as the reference value for the calculation. A new optimization module was developed, and a system simulation model was built using Trnsys. The variation patterns of the OGD for 12 groups of buildings in Changchun, China, were analyzed. Finally, OGD recommendations were provided for 35 important cities in China. The results showed that OGD was not affected by changes in the building type or equipment installation costs. The average error of the annual cost calculation for different building types was 0.074%, and the maximum error was 1.7% when the equipment investment cost was changed. In addition, the OGD value was affected by a combination of outdoor temperature and local electricity prices. This value gradually decreased as the climate warmed. For regions with unfavorable price policies, such as Kashgar, China, the recommended local OGD value increased by 75.8%. The proposed method can be used as a methodological complement to the calculations of such systems during the design phase.

Multi-objective optimization of battery capacity of grid-connected PV-BESS system in hybrid building energy sharing community considering time-of-use tariff

The use of renewable energy and storage systems in energy sharing communities relieves the strain on the grid and reduces the cost of electricity, making the design of community energy management strategies particularly important. In this paper, a shared energy storage operation strategy considering the time-of-use tariff is proposed for the grid-connected PV-BESS system of hybrid building community including factories, offices and dormitories. Aiming at maximizing the photovoltaic self-consumption ratio, minimizing the payback period and power transportation loss, the system is optimized by non-dominated sequencing genetic algorithm II to obtain the optimal battery capacity of each building under the designed strategy. The results show that when the total battery capacity of the community is determined, the photovoltaic power generation of each building and the building load are the main factors that affect the allocation of battery capacity, and the proportion of battery allocation in each building changes little when the values of other influencing parameters are changed. The photovoltaic array area of the building, the difference between peak and valley electricity price and the power input and output limits of the grid are the main factors affecting the optimal battery capacity and system performance. When the photovoltaic array area increases from 65% to 80%, the difference between peak and valley price increases from 0.52RMB/kWh to 0.82RMB/kWh, and the grid power output limit increases from 7500 kW to 9000 kW, the total optimal battery capacity is increased by 9.8%, 20%, 2.2%, the corresponding payback period is increased by 4%, 3.1%, 2%, the photovoltaic self-consumption ratio is increased by 3.3%, 1.9%, 0.2%, and the electricity transportation loss is increased by 6%, 21%, 2.4%, respectively. On the contrary, when the grid power input limit increases from 5500 kW to 7000 kW, the optimal total battery capacity, the corresponding payback period, photovoltaic self-consumption ratio, and power transport loss are reduced by 2.8%, 2.5%, 0.3% and 3.3%, respectively. This study provides theoretical guidance for community battery capacity optimization and energy scheduling design under the peak-valley policy of power grid.

The investigation on a hot dry rock compressed air energy storage system

For the strict site requirement and the consumption of fossil fuel in compressed air energy storage system, the large-scale application of compressed air energy storage is limited. In this paper, a hot dry rock compressed air energy storage system is proposed, and the cracks of hot dry rock are used as the storage place of compressed air. Meanwhile, the thermodynamic model and wellbore model are constructed to evaluate the performance of proposed system. In the range of mass flow rate and recharge pressure of present work, the numerical results illustrate that the production temperature increases with the augment of the mass flow rate, but the increase of the recharge pressure has no obvious effect on the production temperature. Besides, the consumption of valley electricity increases with the augment of mass flow rate and the reduction of the recharge pressure. In addition, the round trip efficiency of the system fluctuates between 48.59%∼54.88%, which is much better than that of the traditional compressed air energy storage system (42%).

Optimal Allocation Method for Energy Storage Capacity Considering Dynamic Time-of-Use Electricity Prices and On-Site Consumption of New Energy

Configuring energy storage devices can effectively improve the on-site consumption rate of new energy such as wind power and photovoltaic, and alleviate the planning and construction pressure of external power grids on grid-connected operation of new energy. Therefore, a dual layer optimization configuration method for energy storage capacity with source load collaborative participation is proposed. The external model introduces a demand-side response strategy, determines the peak, flat, and valley periods of the time-of-use electricity price-based on the distribution characteristics of load and new energy output, and further aims to maximize the revenue of the wind and solar storage system. With the peak, flat, and valley electricity price as the decision variable, an outer optimization model is established. Based on the optimized electricity price, the user’s electricity consumption in each period is adjusted, and the results are transmitted to the inner optimization model. The internal model takes the configuration power and energy storage capacity in the wind and solar storage system as decision variables, establishes a multi-objective function that comprehensively considers the on-site consumption rate of new energy and the cost of energy storage configuration, and feeds back the optimization results of the inner layer to the outer layer optimization model. Use ISSA-MOPSO algorithm to solve the optimized configuration model. Finally, the rationality of the proposed model and algorithm in terms of on-site consumption rate and economy of new energy is verified through numerical examples.

Finned coil-type energy storage unit using composite inorganic hydrated salt for efficient air source heat pumps

The imbalance between the variable power load during day and night and the energy supply of office building heating can supplement a staggering electricity economy. In this study, a novel composite inorganic hydrated salt phase change material (PCM) was fabricated with a melting temperature of 50.3 °C using CH3COONa·3H2O (the primary material), KNO3 (the eutectic material), Na2HPO4·12H2O (the nucleating agent), and carboxymethyl cellulose (CMC, the thickener) in a mass ratio of 89 %:8 %:1.5 %:1.5 %. Moreover, we developed a modular finned coil-type energy storage unit (ESU) with a PCM charging capacity of 1200 kg and a theoretical heat storage capacity of 315 MJ. Subsequently, we created an ESU test system for an air source heat pump (ASHP) operated at the valley electricity period from 23:00 to 7:00. The heat storage, heat release, and defrosting functions were tested, and the operational cost of heating for the office building was evaluated. The results reveal that the composite PCM exhibited stable thermal properties, but more accurate working medium flow matching is required to improve the heat transfer tail phenomenon. Furthermore, the ASHP-ESU reduces the defrosting time by 63 % and improves the efficiency by 6–9 % compared to conventional ASHP. The operating costs are the lowest at 4.66 CNY/month/m2 with valley electricity operation compared with the other three heating modes. Therefore, the ASHP-ESU system for office building heating in off-peak operation is an economical and sustainable approach for the power system.