Economic Operation Strategy Research Articles

Operation Optimization of Regional Integrated Energy Systems with Hydrogen by Considering Demand Response and Green Certificate–Carbon Emission Trading Mechanisms

Amidst the growing imperative to address carbon emissions, aiming to improve energy utilization efficiency, optimize equipment operation flexibility, and further reduce costs and carbon emissions of regional integrated energy systems (RIESs), this paper proposes a low-carbon economic operation strategy for RIESs. Firstly, on the energy supply side, energy conversion devices are utilized to enhance multi-energy complementary capabilities. Then, an integrated demand response model is established on the demand side to smooth the load curve. Finally, consideration is given to the RIES’s participation in the green certificate–carbon trading market to reduce system carbon emissions. With the objective of minimizing the sum of system operating costs and green certificate–carbon trading costs, an integrated energy system optimization model that considers electricity, gas, heat, and cold coupling is established, and the CPLEX solver toolbox is used for model solving. The results show that the coordinated optimization of supply and demand sides of regional integrated energy systems while considering multi-energy coupling and complementarity effectively reduces carbon emissions while further enhancing the economic efficiency of system operations.

Low-carbon economic operation strategy for multi-agent integrated energy system considering uncertainty of renewable energy power generation

The uncertainty of renewable energy output threatens the operation safety of multi-agent integrated energy system (MAIES), which makes it difficult to balance the low-carbon economic operation demands of various stakeholders. However, the existing research solely focuses on the operational strategy of multi-agent game involving integrated energy suppliers and users in deterministic scenarios, overlooking the complementary supporting role and game interaction of shared energy storage and wind farm as independent entities of interest under the instability of renewable energy power generation. Hence, this paper first establishes the optimal operation models for integrated energy system operator (IESO), user aggregator (UA), shared energy storage operator (SESO), and wind farm operator (WFO) considering the stepped carbon trading. Second, in the face of the actual situation of uncertainty of photovoltaic and wind power output, fuzzy chance-constrained programming is adopted for processing. Then, a bi-layer game equilibrium model with IESO as a leader and UA, SESO, and WFO as followers is proposed, and the existence and uniqueness of Stackelberg equilibrium solution are proved. Finally, simulation calculation is carried out based on the YALMIP toolbox in the Matlab R2023a software, and the improved particle swarm optimization algorithm and CPLEX solver are used to solve the model. The results demonstrate that the participation of SESO and WFO as independent stakeholders in the game interaction can improve the economic and environmental benefits of MAIES. The iterative optimization of demand response subsidy prices can effectively motivate users to participate in demand response, improve the ability of MAIES to cope with the uncertain risks of renewable energy generation and load, and reduce the power grid dispatch pressure.

Thermoelectric optimization of integrated energy system considering wind-photovoltaic uncertainty, two-stage power-to-gas and ladder-type carbon trading

Integrated energy system (IES) coupled with renewable energy generation and power-to-gas (P2G) technology provides an effective solution to alleviate the current urgent carbon peak demand. Therefore, This paper develops a novel IES low-carbon economic operation strategy incorporating market mechanism. Firstly, a 24-h joint wind turbine and photovoltaic (WT-PV) output scenario generation method is proposed based on the time-varying Copula function. Secondly, the introduction of carbon capture technology (CCT), electrolyzer (EL), methane reactor (MR) and hydrogen fuel cell (HFC) refines the operation process of p2g into two stages. The combined heat and power (CHP) and HFC variable power operation strategy with adjustable thermoelectric ratio is proposed. Finally, the ladder-type carbon trading mechanism is used to guide IES to control carbon emission. The results of case study show that 1) The time-varying Copula function is effective in improving the scenario accuracy and fitting the data closely to reality 2) The introduction of hydrogen improves the energy utilization efficiency while promoting the consumption of WT-PV. 3) The variable power operation reduces the total cost and carbon emission by 2.4 % and 3.14 %, respectively, compared with the constant thermoelectric ratio. 4) The proposed IES operates reliably and economically under reasonable carbon trading parameters.

Low‐carbon economic optimal operation strategy of rural multi‐microgrids based on asymmetric Nash bargaining

AbstractThe multi‐microgrids operation can greatly improve the proportion of renewable energy integration and power reliability of rural microgrids through energy trading between adjacent microgrids. Therefore, this paper proposes an optimization method for the low‐carbon economic operation of rural microgrids which contain wind power, photovoltaic, biogas, and other common rural renewable energy sources. Using the asymmetric Nash bargaining model which can form the non‐linear energy mapping function to quantify the bargaining power of each microgrid to establish the multi‐microgrids energy trading model, and the non‐convex trading optimization problem is equivalently transformed into two convex optimization subproblems, subproblem 1 is microgrids alliance costs containing the emission costs, and subproblem 2 is cooperative benefits distribution. Then, the accelerated Alternating Direction Method of Multipliers (ADMM) method is used to solve subproblem 1 and subproblem 2, respectively, and the privacy of transaction information is also protected. The results show that: compared with the single‐microgrid operation, the combined operation of rural multi‐microgrids with biogas can greatly improve the renewable energy consumption rate, reduce carbon emission, and improve the profit income of the alliance and each microgrid. Meanwhile, the accelerated ADMM algorithm used can greatly improve the solution speed.

Integration of sewage source heat pump and micro-cogeneration system based on domestic hot water demand characteristics: A feasibility study and economic analysis

The reduction of carbon emissions from building space heating and cooling technology has become a crucial approach in achieving global carbon neutrality. Among these technologies, heat pumps and cogeneration systems are effective methods for carbon reduction in buildings. However, in numerous studies of coupled system operation, few scholars have considered the energy use of domestic hot water. This research investigates the operational feasibility of a sewage source heat pump coupled with a micro-cogeneration system, using a large-scale hotel building as the basis for the study. An economic operation strategy, based on the load characteristics of domestic hot water, is proposed and validated through simulation using TRNSYS software. The results showed that the proposed system can reduce peak power usage by 37 % annually, leading to lower operating costs. The calculations indicate that the proposed system can decrease the annual operating cost by 402,300 CNY compared to a single sewage source heat pump system. The payback period for the proposed system is estimated to be 6 years at the current time-of-use electricity price. Under various energy policy conditions, 71 % of the proposed system’s payback period is less than 20 years. Moreover, the emissions of SO2, NOx, and CO2 are reduced by 73.5 %, 73 %, and 64.8 % respectively. The system offers substantial economic and environmental benefits, and this study can serve as a reference for energy supply systems in cold regions.

The low-carbon economic operation strategy of virtual power plant under different electricity-gas-heat-carbon multi-market synergy scenarios

Studying the grid integration of renewable energy power generation is crucial for achieving the goal of carbon neutrality since it may have a significant influence on the secure and reliable functioning of the power system. In order to solve the problem of deviation impact caused by renewable energy fluctuations and the optimal scheduling of VPP (Virtual Power Plant), the study divides the internal aggregation unit of the virtual power plant into two parts to model. One part is the source equipment, including wind power generation equipment, gas turbine, gas boiler and waste heat boiler. And the other part is the generalized Energy storage, including electric vehicles, air conditioners and alternative response loads. Ultimately, a generalized energy storage-based virtual power plant operation optimization model is developed under multi-market coordination of electricity-gas-heat-carbon. According to the study’s findings, adding more power-to-gas technology boosts revenue in the carbon trading market by 25.24 percent. The energy market’s revenue is equal to that in the absence of a carbon trading market, and the income of the natural gas market increases by $ 32.96. The income of the carbon trading market is $ 181.51, and the final operating cost is reduced by $ 180.80, a drop of 7.81%. To sum up, the suggested approach may more effectively achieve the best distribution of different energy sources, increase the dependability of VPP operation, and make it more low-carbon.

Economic Operation Strategy of an EV Parking Lot with Vehicle-to-Grid and Renewable Energy Integration

The economic operation of an electric vehicle (EV) parking lot under different cases are explored in the paper. The parking lot is equipped with EV charging stations with a vehicle-to-grid (V2G) function, renewable energy sources (RESs), and energy storage system (ESS). An optimisation problem is formulated to maximise the profit of the parking lot from EV charging and feed-in energy to the grid under various charging modes while considering the uncertain factors, ESS degradation, and diverse EV parking conditions. The electricity market price, solar radiation and wind speed are considered as uncertain factors, and the scenred toolbox of MATLAB is used to generate scenarios. Based on the parking time of different EVs, the model classifies the EVs entering the charging station and dynamically determines the charging price according to their charging demand through a linear price-demand relationship. The efficacy of the proposed model is verified by the comparison with two other models under three different cases. It is shown that the proposed model gains the most profit based on the proposed V2G services and dynamic charging price.

Economic operation strategy of integrated hydrogen energy system considering the uncertainty of PV power output

To address the negative influence caused by power randomness of distributed PV output on energy system’s economic operation, in this work, an economic operation strategy considering the uncertainty features of PV output has been designed and applied on an integrated hydrogen energy system. First, the thermal system operation model and the thermoelectric output control model are precisely built for the integrated hydrogen energy system and the hydrogen-based fuel cell, respectively. Then, referring to the PV output prediction data, the uncertainty of light intensity variation is analyzed to correct the PV output prediction curve. Finally, a cost–benefit model for the optimal economic operation of the integrated hydrogen energy system including PV, hydrogen fuel cell and cogeneration unit is designed with an objective function of achieving an optimal economic operation of the multi-energy coupling devices. The simulation tests validate that considering the influence of PV output uncertainty on hydrogen fuel cell output can make the system operation more reasonable, which ensures the economic and reliable operation of hydrogen energy systems.

Distributed economic operation strategy of charging stations based on consistency algorithm

Considering that the centralized optimization control strategy is difficult to adapt to the access of large-scale electric vehicles, a distributed collaborative control strategy based on consensus algorithm is proposed in this paper to control the operation of multiple charging stations. In order to reduce the computational cost, a charging station aggregation model is established to reduce the optimization variables of large-scale electric vehicle access. According to the dispatching instructions issued by the distribution network, this method takes the economic operation of charging stations as the goal, satisfies the global and local constraints, and realizes the power allocation among charging stations. The case analysis proves the accuracy, effectiveness and robustness of the method, and the adaptability to large-scale electric vehicle access.

Analysis of Optimal Operation of Charging Stations Based on Dynamic Target Tracking of Electric Vehicles

In view of the large impact of traditional charging stations on the power grid and the investment in the construction of charging stations for electric vehicle infrastructure services, this paper considers the configuration of optical storage equipment in charging stations from a practical point of view and proposes an economic operation strategy for charging stations to meet the economically optimal requirements of different scenarios. First, we analyze the behavioral characteristics of multiple types of electric vehicles, consider the influence of charging queues, and establish a daily load model of charging stations by taking into account the daily monitoring load and nighttime lighting load of charging stations. Then, considering the electric vehicle (EV) charging demand, photovoltaic (PV) output and energy storage charging and discharging power, the daily economic optimal operation problem based on the dynamic target tracking of charging stations is established; the objective is to maximize the daily operating revenue of charging stations under the condition of satisfying the EV charging demand and PV consumption. Secondly, the objective function is linearized, and the economic operation model is transformed into a mixed integer linear programming model for solving, and the simulation is verified under different scenarios. The results show that the economic optimal operation strategy can adapt to the economic operation requirements of charging stations in different scenarios and maximize the charging station revenue.

Integrated Optimal Planning of Distribution Network With Geographical-Zone-Restricted Renewable Energy Sources

Recently, a lot of renewable energy sources have been integrated into the distribution network. In consideration of economy and construction feasibility, some renewable energy sources are required to be installed in specific areas. In this paper, a bi-layer distribution network planning optimization model that considers the geographical restrictions of the installation locations of the substation, pumped storage plant, photovoltaic (PV) and wind power, as well as the impact of operation on planning, is proposed. In the planning optimization layer, the optimal distribution network topology with minimal total cost is obtained. The locations of the renewable energy sources and the substation are determined by the particle swarm optimization (PSO), and then all the components are interconnected using the dynamic minimum spanning tree (DMST) method. In the operation optimization layer, the economic operation strategy of the hybrid energy system with uncertainty is obtained by the scenario-based stochastic optimal power flow (OPF). The forecast error of the uncertain variable is represented by the probability distribution function, and the roulette wheel mechanism (RWM) is used to generate the stochastic scenarios. A modified 103-bus system is used to test the effectiveness of the proposed method, and the simulation results show that the proposed method can effectively reduce the total cost of the distribution network.

Research on Low-Carbon Economic Operation Strategy of Renewable Energy-Pumped Storage Combined System

Aiming at the problem of insufficient peak shaving capacity of the power system after large-scale renewable energy such as wind power and photovoltaics is connected to the grid, a new energy-pumped storage combined system low-carbon economic operation strategy is proposed. First, the energy storage characteristics of pumped storage are studied; wind power and photovoltaic output are shifted in time and space; and a new energy-pumped storage combined system model with photovoltaics, wind power, and pumped storage as the main body is established. Second, the carbon trading mechanism was introduced, and the reward and punishment ladder carbon trading cost model was established. Then, via the new energy-pumped storage combined system, the upper optimization target with the smallest investment cost and the lower optimization target with the largest system benefit are established, and a two-layer optimization model solution method based on linearly decreasing inertia weight particle swarm optimization and sequential quadratic programming algorithm is proposed. Finally, via the operating data of a pumped storage power station on an island in northern China, the new energy-pumped storage combined system low-carbon economic operation strategy was simulated and verified. The simulation results show that the low-carbon economic operation strategy of the new energy-pumped storage combined system proposed in this paper can effectively suppress load fluctuations, reduce the impact of wind and wind anti-peak regulation characteristics on the power grid, increase the utilization rate of renewable energy, and improve system economy.

Modeling and Economic Operation of Energy Hub Considering Energy Market Price and Demand

This paper discusses the economic operation strategy of the energy hub, which is being established in South Korea. The energy hub has five energy conversion devices: a turbo expander generator, a normal fuel cell, a fuel cell with a hydrogen outlet, a small-scale combined heat and power device, and a photovoltaic device. We are developing the most economically beneficial operation strategy for the operators who own the hub, without making any systematic improvements to the energy market. First, sixteen conversion efficiency matrices can be achieved by turning each device (except the PV) on or off. Next, even the same energy must be divided into different energy flows according to price. The energy flow is controlled to obtain the maximum profit, considering the internal load of the energy hub and the price fluctuations of the energy market. Using our operating strategy, the return on investment period is approximately 9.9 years, which is three years shorter than that without the operating strategy.

Security-Constrained Unit Commitment for Hybrid VSC-MTDC/AC Power Systems With High Penetration of Wind Generation

This paper presents the solution to the security-constrained unit commitment (SCUC) problem for hybrid voltage source converter (VSC) based multi-terminal DC/AC (VSC-MTDC/AC) power systems with high penetration of wind generation. The formulated SCUC model presents a detailed representation of the VSCs with two different VSC control strategies considered, constant DC voltage control (master-slave control) and DC voltage droop control. In addition, Grid Code for wind farm connection is considered. Benders decomposition is used to solve the formulated SCUC problem by decomposing it into a master problem for solving unit commitment (UC) and hourly transmission security check subproblems. The final SCUC solution provides an economic and secure operation and control strategy for the meshed MTDC/AC system. Numerical tests illustrated the efficiency of the proposed SCUC model.

Economic Operation Strategy ofElectric-Gas-Heat-Hydrogen Integrated Energy System Considering Carbon Cost

Economic Operation Strategy ofElectric-Gas-Heat-Hydrogen Integrated Energy System Considering Carbon Cost

Optimized Economic Operation Strategy for Distributed Energy Storage With Multi-Profit Mode

Distributed energy storage (DES) on the user side has two commercial modes including peak load shaving and demand management as main profit modes to gain profits, and the capital recovery generally takes 8–9 years. In order to further improve the return rate on the investment of distributed energy storage, this paper proposes an optimized economic operation strategy of distributed energy storage with multi-profit mode operation. Considering three profit modes of distributed energy storage including demand management, peak-valley spread arbitrage and participating in demand response, a multi-profit model of distributed energy storage is established, and the proposed optimal operation strategy formulates three stages of the energy storage operation, namely month-ahead, day-ahead, and in-day. In the month-ahead optimization stage, the demand charge threshold of the next month is optimized to minimize the electricity cost. In the day-ahead optimization stage, under the constraint of demand charge threshold and with the goal of maximizing returns, the distributed energy storage is controlled to participate in peak-valley spread arbitrage and demand response, and the optimized output curve for the next day is calculated. In the in-day optimization stage, based on the optimized output curve, taking real-time demand response into account, the real-time charge-discharge power of energy storage is adjusted dynamically with the goal of minimizing income loss, thus to realize adaptive adjustment of distributed energy storage and eliminate the risk of income loss. Simulation results of distributed energy storage for typical industrial large users show that the proposed strategy can effectively improve the economic benefits of energy storage.

A multi-objective operation strategy optimization for ice storage systems based on decentralized control structure

Improving the operational efficiency of chillers and science-based planning the cooling load distribution between the chillers and ice tank are core issues to achieve low-cost and energy-saving operations of ice storage air-conditioning systems. In view of the problems existing in centralized control architecture applied in heating, ventilation, and air conditioning, a distributed multi-objective particle swarm optimization improved by differential evolution algorithm based on a decentralized control structure was proposed. The energy consumption, operating cost, and energy loss were taken as the objectives to solve the chiller’s hourly partial load ratio and the cooling ratio of ice tank. A large-scale shopping mall in Xi’an was used as a case study. The results show that the proposed algorithm was efficient and provided significantly higher energy-savings than the traditional control strategy and particle swarm optimization algorithm, which has the advantages of good convergence, high stability, strong robustness, and high accuracy. Practical application: The end equipment of the electromechanical system is the basic component through the building operation. Based on this characteristic, taken electromechanical equipment as the computing unit, this paper proposes a distributed multi-objective optimization control strategy. In order to fully explore the economic and energy-saving effect of ice storage system, the optimization algorithm solves the chillers operation status and the load distribution. The improved optimization algorithm ensures the diversity of particles, gains fast optimization speed and higher accuracy, and also provides a better economic and energy-saving operation strategy for ice storage air-conditioning projects.

A Grid-Connected Microgrid Optimal Allocation Method Considering Self-Balancing Rate

Microgrid optimal allocation is the primary problem that needs to be solved in the stage of microgrid planning and design. Whether the optimal allocation scheme is reasonable or not will directly determine the safe operation and economic benefits of microgrid. Unreasonable allocation scheme will lead to higher power supply costs and poor performance, and can not even reflect the inherent superiority of microgrid. In this paper, based on some indicators such as the self-balancing rate, the power fluctuation rate of the tie line, and the proportion of spontaneous self-use, the effect of the different operation strategies of the wind/light/storage grid-type microgrid is analyzed firstly. Then, an optimal allocation method for grid-connected microgrid is proposed. Furthermore, based on the economic scheduling operation strategy, considering the initial investment cost, replacement cost, operation maintenance cost, residual value and purchase electricity cost, the optimal allocation scheme with different self-balancing rate is compared.

Research of Economic Operation and Control Strategy for PV-Storage-Charging Integrated Power Station

This paper proposes an economic operation mode and control strategy for an PV-storage-charging integrated power station. By optimizing the capacity configuration and analyzing the mechanism relationship of its various operating modes, this paper establishes the system model including PV system power, energy storage SOC and charging spot power, and gives its economic operation constraints. Based on statistical analysis of historical data, the strategy optimizes the operation mode dynamically to control the grid power flow and balance the system power supply and load. Simulation results verify the economic and stable operation of this strategy.

Transmission Grid Expansion Planning of a High Proportion Renewable Energy Power System Based on Flexibility and Economy

The large-scale grid connection of renewable energy causes great uncertainty in power system planning and operation. The power system flexibility index can quantify the system’s ability to adjust to uncertain events such as renewable energy, load fluctuations, and faults. Compared with traditional planning methods, the flexibility planning method can accurately evaluate the impact of various uncertain events on the system during the planning process, thus effectively ensuring the safe and economic operation of renewable energy systems. First, from the perspective of power transmission and safe operation, the flexibility index of the transmission line is defined. On this basis, considering the system’s economic operation strategy, aiming at the optimization of flexibility, investment cost, operation cost, and renewable energy consumption, a multi-objective transmission grid planning model based on flexibility and economy is proposed. The NSGAII optimization algorithm is used to solve the model. Finally, the simulation is performed in the modified Garver-6 and IEEE RTS-24 node systems to analyze the effectiveness of the proposed model. The results show that the planning model can meet the needs of flexibility and economy, improve the transmission capacity of power grids, reduce the probability of renewable energy abandonment or exceeding power flow, as well as enhance the flexibility, economy, and reliability of power systems.