Peak-valley Electricity Price 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.

Research on the charging strategy of battery swapping stations under the optimization of peak-valley electricity price of electrical technology

Research on the charging strategy of battery swapping stations under the optimization of peak-valley electricity price of electrical technology

Optimal Planning of Urban Building-Type Integrated Energy Systems Considering Indoor Somatosensory Comfort and PV Consumption

Building energy consumption is the main urban energy consumption component, which mainly serves people-centered work and living energy demands. Based on the physical requirements of humans in urban buildings and to determine the comfortable body temperature in each season, this paper establishes a sizing optimization model of building-type integrated energy systems (IES) for sustainable development, where the cooling and heating loads required to maintain indoor somatosensory body comfort temperature are calculated. Depending on the external energy price, internal power balance, and other constraints, the model develops an optimal sizing and capacity-planning method of energy conversion and storage unit in a building-type IES with PV generation. The operating principle is described as follows: the PV generation is fully consumed, a gas engine satisfies the electric and thermal base load requirements, and the power system and a heat pump supply the remaining loads. The gas price, peak-valley electricity price gap, and heat-to-power ratio of gas engines are considered important factors for the overall techno-economic analysis. The developed method is applied to optimize the economic performance of building-type IES and verified by practical examples. The results show that using the complementary characteristics of different energy conversion units is important to the overall IES cost. A 300 kW building photovoltaic system can reduce the gas engine capacity from 936.7 kW to 854.7 kW, and the annual cost can be approximately reduced from 7.82 million to 7.50 million RMB yuan.

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.

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.

An optimal coordinated planning strategy for distributed energy station based on characteristics of electric vehicle charging behavior under carbon trading mechanism

Under the dual-carbon goal, the number of electric vehicle (EV) has surged, and the uncertainty of the temporal and spatial characteristics of the load has become prominent, which brings the challenge for higher requirements to the equipment composition of distributed energy station (DES) and performance of station-network. This paper proposes a collaborative planning method for low-carbon DES with networks, which is focusing on the characteristics of EV charging behavior. First of all, based on the quantitative analysis of the temporal and spatial distribution of charging load of four typical types of EV, including private vehicle, public vehicle, taxi and bus, the Monte Carlo method is used to construct the charging load modeling of EV in the region area. In addition, the low-carbon DES is modeled equipped with photovoltaic (PV) and power to gas (P2G) devices, and the Prim algorithm is adopted to search for the optimal network layout of energy transmission pipelines in the region area. Under carbon trading mechanism, aiming at the lowest annualized total cost of the regional station-network, a station-network collaborative planning modeling strategy for the capacity allocation of low-carbon DES with networks is established. Finally, the case study for a project in Beijing China is implemented on MATLAB, to prove the effectiveness of the method proposed in the paper. The time-of-use electricity price scheme changes the temporal and spatial characteristics of EV load. For example, more than 2 MW the EV load can be brought into the valley price range, which reduces the carbon transaction cost and energy purchase cost of DES by 50 thousand yuan almost when peak-valley electricity price difference is close to 1.2 yuan. At the same time, the growth of EV charging load(the penetration rate of EV can reach up to 20%) in the planning area has not increased the investment and operation-maintenance costs of DES equipment.

Preliminary Study on Optimization of a Geothermal Heating System Coupled with Energy Storage for Office Building Heating in North China

Geothermal heating is considered to be one of the low-carbon-energy technologies for building heating. Aiming at the problem that the operating cost and investment cost of geothermal heating systems are still high, the conventional geothermal heating system coupled with energy storage for office building heating is studied in this paper. Four operational strategy models of the coupled system are established based on time-of-use electricity prices. A genetic algorithm is used to find the optimal value of each decision variable using minimization of levelized cost of heat (LCOH) as the objective function. The influences of electricity and equipment prices on the optimal values of the decision variables are discussed. Four operation strategies are investigated. If only operating cost is considered in the optimization, comparison shows that the best operation strategy is the one giving high priority to use the energy storage tank for heating during the peak electricity period. However, if the investment cost is further considered in the optimization, the best operation strategy is the one using the energy storage tank for heat load peak-regulating. In addition, based on the minimization of LCOH, an optimal energy storage ratio is found for each scenario, and suitable conditions of using energy storage tank are discussed. The geothermal heating system coupled with energy storage can have a good performance when the peak-valley electricity price difference is higher than CNY 0.566/kW·h (USD 0.0847/kW·h)+ or the energy storage tank price is lower than CNY 900/m3 (USD 134.64/m3). The results obtained from this study prove that the cost of geothermal heating systems can be effectively reduced by choosing an optimal operation strategy and using an energy storage device with an optimal energy storage ratio.

Optimization analysis of energy storage application based on electricity price arbitrage and ancillary services

Energy storage is an effective way to facilitate renewable energy (RE) development. Its technical performance and economic performance are key factors for large scale applications. As battery energy storage system (BESS) is one commercially-developed energy storage technology at present, BESS is utilized to connect to RE generation. BESS couple with RE can balance the generation and load, and provide auxiliary services. Thus, the technical and economic performance of this coupling system was investigated. The coupling system generates extra revenue compared to RE-only through arbitrage considering peak-valley electricity price and ancillary services. In order to maximize the net revenues of BESS, a multi-objective three-level model for the optimal configuration of BESS was developed. The outer layer was a model for the optimal configuration of BESS, the middle layer was a multi-objective optimal model for BESS to participate in electricity price arbitrage and reserve ancillary services, and the inner layer was an optimal scheduling model that coordinated wind power, photovoltaic (PV) power and BESS. The multi-objective genetic algorithm (GA) based on the roulette method was employed to solve the optimal model. A case study was conducted, and the annual net revenues of BESS under different BESS capacities were evaluated. When the annual net revenues of BESS reach the maximum, the optimal BESS capacity is obtained. Sensitive analysis was also conducted considering different price difference, environment conditions of irradiance, wind speed. The effective trend and optimization values were calculated. The study presented a solution including methodology and values for how to determine the installation of energy storage to RE.

Thermodynamic analysis of a liquid air energy storage system with off-peak electric heat storage and reutilization

As a large-scale energy storage technology, liquid air energy storage (LAES) can effectively improve the stability and quality of power grid. However, the traditional LAES has low cycle efficiency, high initial investment and low economic benefits. In order to improve the system performance, a LAES system based on off-peak electric heat storage and high temperature preheating of turbine inlet air was proposed. The thermodynamic characteristics of the LAES system were analyzed, and the energy analysis, exergy analysis and economic evaluation were carried out. Combined with off-peak electric heat storage, the power generation during the peak time by the LAES system can be significantly increased, and the economy of the LAES system can be effectively improved with the peak-valley electricity price difference, especially in areas where the price difference is obvious. The results will be beneficial for the application and promotion of the LAES technology.

Techno-economic analysis of multi-generation liquid air energy storage system

• Economic model of the multi-generation LAES system was established. • Economic analysis of the multi-generation LAES system was carried out. • Internal rate of return of the multi-generation system in Beijing reached 35%. • Dynamic payback period is most susceptible to the influence of uncertain factors. Multi-generation liquid air energy storage (LAES) system solves the shortcoming that the compression heat cannot be fully utilized in the general LAES system, and greatly improves the round-trip efficiency. Which is expected to become one of the most promising emerging energy technologies and has important research value and exploration significance. In order to prove the feasibility that the multi-generation LAES technology using peak-valley price difference for profits, this paper established the economic calculation model by life cycle cost theory. Based on peak-valley electricity price, heating price and cooling price of four typical cities in China, the cost analysis, profit analysis, breakeven analysis, sensitivity analysis and subsidy analysis of the multi-generation LAES system are carried out. The results show that the energy storage system has good economic benefits only in Beijing under the single electricity supply mode, the rate of return on investment is 12.5%, the internal rate of return is 25%, the static payback period is 6.25 years, and the dynamic payback period is 8.08 years. Under the multi-generation mode, the multi-generation LAES system has good economic benefits both in Beijing and Suzhou. Among them, the rate of return on investment in Beijing is increased 28.16% contrasted with the single electricity supply mode, the internal rate of return is increased 40%, the static payback period is decreased 34.88%, the dynamic payback period is decreased 42.33%. This study indicated that the multi-generation LAES system has strong market adaptability and risk resistance ability.

Research on the Optimized Operation of Hybrid Wind and Battery Energy Storage System Based on Peak-Valley Electricity Price

The combined operation of hybrid wind power and a battery energy storage system can be used to convert cheap valley energy to expensive peak energy, thus improving the economic benefits of wind farms. Considering the peak–valley electricity price, an optimization model of the economic benefits of a combined wind–storage system was developed. A charging/discharging strategy of the battery storage system was proposed to maximize the economic benefits of the combined wind–storage system based on the forecast wind power. The maximal economic benefits were obtained based on scenario analysis, taking into account the wind-power forecast error, and costs associated with the loss of battery life, battery operation, and maintenance. Case simulation results highlight the effectiveness of the proposed model. The results show that the hybrid wind–storage system is not only able to convert cheap electricity in the valley period into expensive electricity in the peak period, thus resulting in higher economic benefits, but can also balance the deviation between actual output and plans for the wind power generator to decrease the loss penalty. The analyzed examples show that, following an increase in the deviation of the forecast wind power, the profit of the combined wind–storage system can increase by up to 45% using the charging/discharging strategy, compared with a wind farm that does not utilize energy storage. In addition, the profit of the combined wind–storage system can increase by up to 16% compared with separate systems, following an increase in the deviation penalty deviation coefficient.

Energy performance evaluation of centralised ice-storage district cooling system

Centralised district cooling system equipped with ice storage has substantial advantages in comprehensive energy utilization and cost effectiveness. It facilitates cutting peak and filling valley of power load and helps saving energy costs by using the peak-valley electricity price. Despite such advantages, energy performance of ice-storage district cooling systems is still a controversial topic, especially there is a lack of effective evaluation methods and relevant evaluation standards in China. Therefore, this paper establishes a thorough index system to evaluate energy performance of ice-storage district cooling system. The index system covers all aspects of ice-storage district cooling systems, including the gradual evaluation of each process from equipment, via subsystem to whole system. Afterwards, the index system is used to analyse a real case, focusing on the eight most important energy performance indexes. The results show that the index system can adapt well to the evaluation requirements, help to find energy performance problems and facilitate to improve energy efficiency. In view of existing insufficiency, further efforts are needed to make in formulating reasonable benchmarks of such energy performance indexes.

Thermal demand response model considering user's satisfaction with heat consumption under electrothermal coupling

.In recent years, the development of new energy has become a bottleneck. As a high-quality demand side response resource that can be flexibly dispatched, thermal load can be used to promote the consumption and utilization of new energy. Based on the theory of peak valley electricity price and power demand response mechanism, this paper designs a demand response model of thermal price type, which uses time-sharing heat price to guide users to use heat orderly on the heating side. The simulation results show that the reasonable setting of heat price and satisfaction constraints of different heating modes can effectively change the heating mode of the user side and alleviate the contradiction between the supply and demand of thermal power, reduce the heating cost and realize the economic operation of the system.

Design Scheme of Block Smart Energy Internet System

Traditional energy consumption is continuously decreasing, and new energy demand industries are continuously increasing. Full consumption of clean and renewable energy and efficient utilization of comprehensive energy will become the development trend of energy industry. The smart energy Internet based on the physical structure of the energy Internet is sweeping the world. Using smart and green to fundamentally change the existing energy structure and to adjust the structure dominated by fossil energy to a new energy structure dominated by renewable energy is of far-reaching significance to China’s energy transformation and upgrading in the future. This paper aims at the design idea of smart energy Internet rack for the newly-built ChengBi campus in Baise University, combines peak-valley electricity price and photovoltaic hydrogen production technology to stabilize the fluctuation of renewable energy output, and realizes the safe and stable operation of a comprehensive energy system of distributed photovoltaic power stations. A campus smart energy Internet system is formed by “wind power + photovoltaic + energy storage + charging pile + photovoltaic hydrogen production”.

Optimal configuration of grid-side battery energy storage system under power marketization

From the view of power marketization, a bi-level optimal locating and sizing model for a grid-side battery energy storage system (BESS) with coordinated planning and operation is proposed in this paper. Taking the conventional unit side, wind farm side, BESS side, and grid side as independent stakeholder operators (ISOs), the benefits of BESS are divided into direct and indirect parts. The direct revenue for BESS is the arbitrage of the peak-valley electricity price and auxiliary service compensation. The indirect revenue refers to the benefits that BESS provides to other ISOs, including wind curtailed energy savings, a reduction in the operating cost of units, and a decrease in network loss. To maximize the comprehensive benefits of BESS, the outer layer is a multi-objective optimal model for BESS locating and sizing based on a cost-benefit analysis. The inner layer is an optimal scheduling model that coordinates wind power, units, and BESS. Thus, a multi-objective bi-level model for the optimal configuration of BESS is established. In addition, by considering the impact of a charge/discharge strategy on the life cycle of BESS, the interaction between BESS planning and operation is introduced into the model based on the equivalent life loss. The multi-objective particle swarm optimization (PSO) based on the information entropy method and the second-order cone relaxation method is employed to solve the optimal model. Results based on an improved IEEE 39-node system verify the feasibility and effectiveness of the proposed model.

Research on energy supply of intelligent energy system with energy storage

The coordinated intelligent energy supply should consider the characteristics of the energy supply equipment, load characteristics and user needs. As a special energy supply equipment, water energy storage system has two-way controllability, which can store and release energy. Using its energy supply characteristics, combined with the system characteristics such as peak valley electricity price difference, it is helpful to achieve peak load reduction, balance load and save energy supply cost of the system. In this paper, an enterprise park is taken as an example to study the energy supply of intelligent energy system with water energy storage. An energy supply strategy is proposed. An energy supply model is established. At last, the simulation verifies the advantages of intelligent energy system with water energy storage.

Multi-Objective Optimal Dispatching of Microgrid With Large-Scale Electric Vehicles

Dispatching the output of distributed power sources is the main task in the microgrid operation phase. This task is more concerned with the optimal dispatch of large electric vehicles connected to the grid-connected microgrid today.Full consider the influence of storage battery and peak-valley electricity price, its objective is to minimize the operating cost of microgrid and the cost of environmental protection, and establishing economic dispatching model of microgrid. To solve this constrained optimization problem, an annealing mutation particle swarm optimization algorithm is proposed. Through simulation and comparison, the dispatching cost results of microgrid are obtained under two dispatching modes of electric vehicle disorder and order. It is concluded that the orderly charging and discharging mode guided by electricity prices can effectively reduce the operating cost and environmental protection cost of microgrid. Improving the economy and reliability of microgrid operation.

Optimal Charging/discharging Strategy of Electric Vehicles in Residential Area Considering User Comprehensive Satisfaction

At present, the research on charging/discharging of electric vehicles (EVs) lacks consideration of the user experience, particularly with the aspects of user's convenience and profitability. Therefore, this paper analyses the travelling characteristics and travelling demand of EV users in a residential area and establishes the user comprehensive satisfaction model considering travel convenience and charging/discharging economy. Based on this model, a genetic algorithm is used to optimize the charging/discharging strategy of EVs with the aim of maximizing user comprehensive satisfaction, the validity of the proposed optimization model is verified by results of example. The model is also used to study the impact of large-scale EVs charging/discharging optimization strategy on grid load fluctuation. Based on the load data of a residential area, the simulation is carried out, and the influence of different peak-valley prices on EVs charging/discharging strategy is analysed. Our case analysis shows that the load peak-valley difference is reduced. With the increase of peak-valley electricity price, more users discharge during the peak hours and charge during the peak-off hours, the load peak-valley difference and the load fluctuation decrease accordingly.

Algorithm Comparison on Optimal Daily Operation Model of Multiple Pump Units with Adjustable-Blade for Single Pumping Station

The mathematical model of optimal daily operation for multiple pump units with adjustable-blade in single pumping station was solved by means of decomposition-dynamic programming aggregation method and experimental optimization method while the peak-valley electricity price was taken into consideration. After taking No.4 Huaian Pumping Station as a study case, a series of optimal operation schemes under different average daily heads and water pumping loads were obtained. Based on the analysis of optimization benefits, the applicability comparison of two optimal algorithms have been carried out, by which the application scope of each algorithm was proposed.

Research on Peak Load Shifting for Mixing Procedure in the Tyre Industry

Since the establishment of peak-valley electricity price system, many enterprises in China have devoted to research on peak load shifting strategies. This paper firstly analyzes the feasibility of applying peak load shifting for mixing procedure in two aspects: rubber compound standard and electric power consumption, then establishes the shifting model, makes depth description to the planning and scheduling algorithm that implements the model, then verify the model with real data and finally reach the expected goal. At last, the paper introduces MESNAC planning and scheduling solutions which have integrated the shifting model.