Evaluation index system of shared energy storage market towards renewable energy accommodation scenario:A China’s Qinghai province context

With the ever-increased installed capacity of renewable energy generation units in a power system,the so-called shared energy storage(SES),a novel business model under the umbrella of the shared economy principle,has the potential to play an essential role in the accommodation of renewable energy generation.However,unified evaluation standards and methods,which can help decision-makers analyze the performance of the SES market,are still not available.In this paper,an evaluation index system of the SES market is designed based on the trading rules of China’s Qinghai province and the structure-conduct-performance(SCP)analytical model.Moreover,the definition and characteristics of the indices,which can show the performance of the SES market from different perspectives,are given.Furthermore,the ideal cases are presented as the evaluation benchmark based on the development expectation of the SES market,and the analytic hierarchy process(AHP)and the technique for order preference by similarity to an ideal solution(TOPSIS)are applied to evaluate the SES market comprehensively.Finally,a case study based on actual data of the SES trading pilot project in Qinghai shows that the evaluation index system can reflect the operation status,existing problems and influencing factors of the SES market.

Optimal Operation with Dynamic Partitioning Strategy for Centralized Shared Energy Storage Station with Integration of Large-scale Renewable Energy

As renewable energy continues to be integrated into the grid,energy storage has become a vital technique supporting power system development.To effectively promote the efficiency and economics of energy storage,centralized shared energy storage(SES)station with multiple energy storage batteries is developed to enable energy trading among a group of entities.In this paper,we propose the optimal operation with dynamic partitioning strategy for the centralized SES station,considering the day-ahead demands of large-scale renewable energy power plants.We implement a multi-entity cooperative optimization operation model based on Nash bargaining theory.This model is decomposed into two subproblems:the operation profit maximization problem with energy trading and the leasing payment bargaining problem.The distributed alternating direction multiplier method(ADMM)is employed to address the subproblems separately.Simulations reveal that the optimal operation with a dynamic partitioning strategy improves the tracking of planned output of renewable energy entities,enhances the actual utilization rate of energy storage,and increases the profits of each participating entity.The results confirm the practicality and effectiveness of the strategy.

Real-Time Energy Management for Net-Zero Power Systems Based on Shared Energy Storage

Battery energy storage systems(BESSs)serve a crucial role in balancing energy fluctuations and reducing carbon emissions in net-zero power systems.However,the efficiency and cost performance have remained significant challenges,which hinders the widespread adoption and development of BESSs.To address these challenges,this paper proposes a real-time energy management scheme that considers the involvement of prosumers to support net-zero power systems.The scheme is based on two shared energy storage models,referred to as energy storage sale model and power line lease model.The energy storage sale model balances real-time power deviations by energy interaction with the goal of minimizing system costs while generating revenue for shared energy storage providers(ESPs).Additionally,power line lease model supports peer-to-peer(P2P)power trading among prosumers through the power lines laid by ESPs to connect each prosumer.This model allows ESP to earn profits from the use of power lines while balancing power deviations and better consuming renewable energy.Experimental results validate the effectiveness of the proposed scheme,ensuring stable power supply for net-zero power systems and providing benefits for both the ESP and prosumers.

Multi-Time-Scale Resource Allocation Based on Long-Term Contracts and Real-Time Rental Business Models for Shared Energy Storage Systems

The push for renewable energy emphasizes the need for energy storage systems(ESSs)to mitigate the unpre-dictability and variability of these sources,yet challenges such as high investment costs,sporadic utilization,and demand mismatch hinder their broader adoption.In response,shared energy storage systems(SESSs)offer a more cohesive and efficient use of ESS,providing more accessible and cost-effective energy storage solutions to overcome these obstacles.To enhance the profitability of SESSs,this paper designs a multi-time-scale resource allocation strategy based on long-term contracts and real-time rental business models.We initially construct a life cycle cost model for SESS and introduce a method to estimate the degradation costs of multiple battery groups by cycling numbers and depth of discharge within the SESS.Subsequently,we design various long-term contracts from both capacity and energy perspectives,establishing associated models and real-time rental models.Lastly,multi-time-scale resource allocation based on the decomposition of user demand is proposed.Numerical analysis validates that the business model based on long-term contracts excels over models operating solely in the real-time market in economic viability and user satisfaction,effectively reducing battery degradation,and leveraging the aggregation effect for SESS can generate an additional increase of 10.7%in net revenue.

Optimal Operation of Micro-energy Grids Considering Shared Energy Storage Systems and Balanced Profit Allocations

Following the unprecedented generation of renewable energy,Energy Storage Systems(ESSs)have become essential for facilitating renewable consumption and maintaining reliability in energy networks.However,providing an individual ESS to a single customer is still a luxury.Thus,this paper aims to investigate whether the Shared-ESS can assist energy savings for multiple users through Peer-to-Peer(P2P)trading.Moreover,with the increasing number of market participants in the integrated energy system(IES),a benefit allocation scheme is necessary,ensuring reasonable benefits for every user in the network.Using the multiplayer cooperative game model,the nucleolus and the Shapley value methods are adopted to evaluate the benefit allocation between multiple users.Numerical analyses based on multiple micro-energy grids are performed,so as to assess the performance of the Shared-ESS and the proposed benefit allocation scheme.The results show that the micro-energy grid cluster can save as much as 38.15%of the total energy cost with Shared-ESS being equipped.The following conclusions can be drawn:the Shared-ESS can significantly reduce the operating costs of the micro-energy grid operator,promote the consumption of renewable energy,and play the role of peak-shaving and valley-filling during different energy usage periods.In addition,it is reflected that the multiplayer cooperative game model is effective in revealing the interaction between the micro-energy grids,which makes the distribution results more reasonable.

A Novel Stackelberg-Game-Based Energy Storage Sharing Scheme Under Demand Charge

Demand response(DR)using shared energy storage systems(ESSs)is an appealing method to save electricity bills for users under demand charge and time-of-use(TOU)price.A novel Stackelberg-game-based ESS sharing scheme is proposed and analyzed in this study.In this scheme,the interactions between selfish users and an operator are characterized as a Stackelberg game.Operator holds a large-scale ESS that is shared among users in the form of energy transactions.It sells energy to users and sets the selling price first.It maximizes its profit through optimal pricing and ESS dispatching.Users purchase some energy from operator for the reduction of their demand charges after operator's selling price is announced.This game-theoretic ESS sharing scheme is characterized and analyzed by formulating and solving a bi-level optimization model.The upper-level optimization maximizes operator's profit and the lower-level optimization minimizes users'costs.The bi-level model is transformed and linearized into a mixed-integer linear programming(MILP)model using the mathematical programming with equilibrium constraints(MPEC)method and model linearizing techniques.Case studies with actual data are carried out to explore the economic performances of the proposed ESS sharing scheme.