查看更多>>摘要：We consider a power system whose electric de-mand pertaining to freshwater production is high(high freshwa-ter electric demand),as in the Middle East,and investigate the tradeoff of storing freshwater in tanks versus storing electricity in batteries at the day-ahead operation stage.Both storing freshwater and storing electricity increase the actual electric de-mand at valley hours and decrease it at peak hours,which is generally beneficial in term of cost and reliability.But,to what extent?We analyze this question considering three power sys-tems with different generation-mix configurations,i.e.,a ther-mal-dominated mix,a renewable-dominated one,and a fully re-newable one.These generation-mix configurations are inspired by how power systems may evolve in different countries in the Middle East.Renewable production uncertainty is compactly modeled using chance constraints.We draw conclusions on how both storage facilities(freshwater and electricity)complement each other to render an optimal operation of the power system.
Carmen Bas DomenechAntonella Maria De CoratoPierluigi Mancarella
334-345页
查看更多>>摘要：Community batteries(CBs)are emerging to sup-port and even enable energy communities and generally help consumers,especially space-constrained ones,to access potential techno-economic benefits from storage and support local grid decarbonization.However,the economic viability of CB projects is often uncertain.In this regard,typical feasibility studies as-sess CB value for behind-the-meter(BTM)operation or whole-sale market participation,i.e.,front-of-meter(FOM).This work proposes a novel techno-economic operational framework that allows systematic assessment of the different options and intro-duces a two-meter architecture that co-optimizes both BTM and FOM benefits.A real CB project application in Australia is used to demonstrate the significant two-meter co-optimization opportunities that could enhance the business case of CB and energy communities by multi-service provision and value stack-ing.
查看更多>>摘要：The scale of distributed energy resources is increas-ing,but imperfect business models and value transmission mechanisms lead to low utilization ratio and poor responsive-ness.To address this issue,the concept of cleanness value of dis-tributed energy storage(DES)is proposed,and the spatiotempo-ral distribution mechanism is discussed from the perspectives of electrical energy and cleanness.Based on this,an evaluation sys-tem for the environmental benefits of DES is constructed to bal-ance the interests between the aggregator and the power system operator.Then,an optimal low-carbon dispatching for a virtual power plant(VPP)with aggregated DES is constructed,where-in energy value and cleanness value are both considered.To achieve the goal,a green attribute labeling method is used to es-tablish a correlation constraint between the nodal carbon poten-tial of the distribution network(DN)and DES behavior,but as a cost,it brings multiple nonlinear relationships.Subsequently,a solution method based on the convex envelope(CE)linear re-construction method is proposed for the multivariate nonlinear programming problem,thereby improving solution efficiency and feasibility.Finally,the simulation verification based on the IEEE 33-bus DN is conducted.The simulation results show that the multidimensional value recognition of DES motivates the willingness of resource users to respond.Meanwhile,resolving the impact of DES on the nodal carbon potential can effectively alleviate overcompensation of the cleanness value.
查看更多>>摘要：As renewable energy continues to be integrated in-to the grid,energy storage has become a vital technique sup-porting power system development.To effectively promote the efficiency and economics of energy storage,centralized shared energy storage(SES)station with multiple energy storage bat-teries 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 en-ergy power plants.We implement a multi-entity cooperative op-timization operation model based on Nash bargaining theory.This model is decomposed into two subproblems:the operation profit maximization problem with energy trading and the leas-ing payment bargaining problem.The distributed alternating di-rection multiplier method(ADMM)is employed to address the subproblems separately.Simulations reveal that the optimal op-eration with a dynamic partitioning strategy improves the track-ing 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.
查看更多>>摘要：Battery energy storage systems(BESSs)serve a crucial role in balancing energy fluctuations and reducing car-bon emissions in net-zero power systems.However,the efficien-cy 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 involve-ment 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 devia-tions by energy interaction with the goal of minimizing system costs while generating revenue for shared energy storage provid-ers(ESPs).Additionally,power line lease model supports peer-to-peer(P2P)power trading among prosumers through the pow-er lines laid by ESPs to connect each prosumer.This model al-lows ESP to earn profits from the use of power lines while bal-ancing power deviations and better consuming renewable ener-gy.Experimental results validate the effectiveness of the pro-posed scheme,ensuring stable power supply for net-zero power systems and providing benefits for both the ESP and prosumers.
Pavitra SharmaKrishna Kumar SainiHitesh Datt MathurPuneet Mishra...
381-392页
查看更多>>摘要：The concept of utilizing microgrids(MGs)to con-vert buildings into prosumers is gaining massive popularity be-cause of its economic and environmental benefits.These pro-sumer buildings consist of renewable energy sources and usual-ly install battery energy storage systems(BESSs)to deal with the uncertain nature of renewable energy sources.However,be-cause of the high capital investment of BESS and the limitation of available energy,there is a need for an effective energy man-agement strategy for prosumer buildings that maximizes the profit of building owner and increases the operating life span of BESS.In this regard,this paper proposes an improved energy management strategy(IEMS)for the prosumer building to min-imize the operating cost of MG and degradation factor of BESS.Moreover,to estimate the practical operating life span of BESS,this paper utilizes a non-linear battery degradation mod-el.In addition,a flexible load shifting(FLS)scheme is also de-veloped and integrated into the proposed strategy to further im-prove its performance.The proposed strategy is tested for the real-time annual data of a grid-tied solar photovoltaic(PV)and BESS-powered AC-DC hybrid MG installed at a commercial building.Moreover,the scenario reduction technique is used to handle the uncertainty associated with generation and load de-mand.To validate the performance of the proposed strategy,the results of IEMS are compared with the well-established en-ergy management strategies.The simulation results verify that the proposed strategy substantially increases the profit of the building owner and operating life span of BESS.Moreover,FLS enhances the performance of IEMS by further improving the financial profit of MG owner and the life span of BESS,thus making the operation of prosumer building more economi-cal and efficient.
查看更多>>摘要：Base station(BS)backup batteries(BSBBs),with their dispatchable capacity,are potential demand-side resources for future power systems.To enhance the power supply reliabili-ty and post-contingency frequency security of power systems,we propose a two-stage stochastic unit commitment(UC)model incorporating operational reserve and post-contingency frequen-cy support provisions from massive BSBBs in cellular networks,in which the minimum backup energy demand is considered to ensure BS power supply reliability.The energy,operational re-serve,and frequency support ancillary services are co-opti-mized to handle the power balance and post-contingency fre-quency security in both forecasted and stochastic variable re-newable energy(VRE)scenarios.Furthermore,we propose a dedicated and scalable distributed optimization framework to enable autonomous optimizations for both dispatching center(DC)and BSBBs.The BS model parameters are stored and pro-cessed locally,while only the values of BS decision variables are required to upload to DC under the proposed distributed opti-mization framework,which safeguards BS privacy effectively.Case studies on a modified IEEE 14-bus system demonstrate the effectiveness of the proposed method in promoting VRE ac-commodation,ensuring post-contingency frequency security,en-hancing operational economics,and fully utilizing BSBBs'ener-gy and power capacity.Besides,the proposed distributed optimi-zation framework has been validated to converge to a feasible solution with near-optimal performance within limited itera-tions.Additionally,numerical results on the Guangdong 500 kV provincial power system in China verify the scalability and practicality of the proposed distributed optimization framework.
查看更多>>摘要：Accurate prediction of the state-of-charge(SOC)of battery energy storage system(BESS)is critical for its safety and lifespan in electric vehicles.To overcome the imbalance of existing methods between multi-scale feature fusion and global feature extraction,this paper introduces a novel multi-scale fu-sion(MSF)model based on gated recurrent unit(GRU),which is specifically designed for complex multi-step SOC prediction in practical BESSs.Pearson correlation analysis is first em-ployed to identify SOC-related parameters.These parameters are then input into a multi-layer GRU for point-wise feature ex-traction.Concurrently,the parameters undergo patching before entering a dual-stage multi-layer GRU,thus enabling the model to capture nuanced information across varying time intervals.Ultimately,by means of adaptive weight fusion and a fully con-nected network,multi-step SOC predictions are rendered.Fol-lowing extensive validation over multiple days,it is illustrated that the proposed model achieves an absolute error of less than 1.5％in real-time SOC prediction.
查看更多>>摘要：The offering strategy of energy storage in energy and frequency response(FR)markets needs to account for country-specific market regulations around FR products as well as FR utilization factors,which are highly uncertain.To this end,a novel optimal offering model is proposed for stand-alone price-taking storage participants,which accounts for recent FR market design developments in the UK,namely the trade of FR products in time blocks,and the mutual exclusivity among the multiple FR products.The model consists of a day-ahead stage,devising optimal offers under uncertainty,and a real-time stage,representing the storage operation after uncertainty is materialized.Furthermore,a concrete methodological frame-work is developed for comparing different approaches around the anticipation of uncertain FR utilization factors(determinis-tic one based on expected values,deterministic one based on worst-case values,stochastic one,and robust one),by providing four alternative formulations for the real-time stage of the pro-posed offering model,and carrying out an out-of-sample valida-tion of the four model instances.Finally,case studies employing real data from UK energy and FR markets compare these four instances against achieved profits,FR delivery violations,and computational scalability.
NETL
NSTL
万方数据