Mechanism Design for Ancillary Service Market Considering Social Welfare and Fairness

Increasing penetration of distributed energy resources in the distribution network(DN)is threatening safe operation of the DN,which necessitates setup of the ancillary service market in the DN.In the ancillary service market,distribution system operator(DSO)is responsible for safety of the DN by procuring available capacities of aggregators.Unlike existing studies,this paper proposes a novel market mechanism composed of two parts:choice rule and payment rule.The proposed choice rule simultaneously considers social welfare and fairness,encouraging risk-averse aggregators to participate in the ancillary service market.It is then formulated as a linear programming problem,and a distributed solution using the multi-cut Benders decomposition is presented.Moreover,successful implementation of the choice rule depends on each aggregator’s truthful adoption of private parameters.Therefore,a payment rule is also designed,which is proved to possess two properties:incentive compatibility and individual rationality.Simulation results demonstrate effectiveness of the proposed choice rule on improving fairness and verify properties of the payment rule.

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.

Dispatch and bidding strategy of active distribution network in energy and ancillary services market

The active distribution network(ADN)is able to manage distributed generators(DGs),active loads and storage facilities actively.It is also capable of purchasing electricity from main grid and providing ancillary services through a flexible dispatching mode.A competitive market environment is beneficial for the exploration of ADN’s activeness in optimizing dispatch and bidding strategy.In a bilateral electricity market,the decision variables such as bid volume and price can influence the market clearing price(MCP).The MCP can also have impacts on the dispatch strategy of ADN at the same time.This paper proposes a bilevel coordinate dispatch model with fully consideration of the information interaction between main grid and ADN.Simulation results on a typical ADN validate the feasibility of the proposed method.A balanced proportion between energy market and ancillary services market can be achieved.

MILP Optimization Model for Assessing the Participation of Distributed Residential PV-battery Systems in Ancillary Services Market

A novel non-linear stochastic method based on a Mixed-Integer Linear Programming(MILP)optimization model is proposed to optimally manage a high number of photovoltaic(PV)-battery systems for the provision of up and down regulation in the ancillary services market.This method,considers both the technical constraints of the power system,and those of the equipment used by all the prosumers.This allows an aggregator of many residential prosumers endowed with photovoltaic(PV)-battery systems to evaluate the baseline of the aggregate by minimizing the costs related to the electrical energy absorbed from the grid and then to assess the up and down flexibility curves with relative offer prices.As confirmed by simulation results carried out considering different realistic case studies,the method can effectively be used by an aggregator to evaluate the economic impact of its participation in the ancillary services market,both for the aggregator and for its prosumers.

Economic potentials of energy storage technologies in electricity markets with renewables

The increasing penetration of renewables in power systems urgently entails the utilization of energy storage technologies.As the development of energy storage technologies depends highly on the profitability in electricity markets,to evaluate the economic potentials for various types of energy storage technologies under the compre-hensive market environment is of great significance.To this end,this study aims at conducting a quantitative analysis on the economic potentials for typical energy storage technologies by establishing a joint clearing model for electric energy and ancillary service(AS)markets considering the operating features of energy storage systems(ESSs).Furthermore,a test system is adopted for numerical analysis that accurately represents for the real-world operation characteristics of power systems in China,with which the market prices,and operation schedules and profitability of ESSs are comparatively studied.The proposed methodology and results could provide benefi-cial references for the modifications on electricity markets and the development of ESSs towards the increasing penetration of renewables in power systems.

Impacts of COVID-19 Pandemic on Italian Electricity Demand and Markets

In this paper,the short-,medium-,and long-term effects of the COVID-19 pandemic on the Italian power system,particularly electricity consumption behavior and electricity market prices,are investigated by defining various metrics.The investigation reveals that COVID-19 lockdown caused a drop in load consumption and,consequently,a decrement in day-ahead market prices and an increase in ancillary service prices.

Benefit Evaluation of the Deep Peak-regulation Market in the Northeast China Grid

In the Northeast China Grid(NCG),the percentage of wind power has reached nearly 20%of the total installed generation capacity,which causes increasing demands for deep peak-regulation capacity(DPC)during the operation of power systems.The shortage of DPC has become a significant problem in the NCG which may lead to wind curtailments and affect the security of power systems as well as the heating needs for inhabitants.In order to cope with this DPC shortage issue,the deep peak-regulation market(DPM)was established and has been running steadily in the past few years in NCG.This paper elaborates on the roles of the market players and the operational processes of the DPM,of which the advancements in terms of management mechanism are summarized.Moreover,benefits of the DPM for social harmony,environmental protection and economic efficiency are analyzed,for which relevant evaluation indices are proposed.A five-unit simulation system is constructed to illustrate the operation and benefits of the DPM.And focusing on comparisons with the previous Two Rules,the case study of Liaoning Power Grid verifies further that the DPM is feasible and able to bring more benefits to grids.

Generalized Energy Storage Allocation Strategies for Load Aggregator in Hierarchical Electricity Markets

The uncertainty of user-side resource response will affect the response quality and economic benefit of load aggregator(LA).Therefore,this paper regards the flexible user-side resources as a virtual energy storage(VES),and uses the traditional narrow sense energy storage(NSES)to alleviate the uncertainty of VES.In order to further enhance the competitive advantage of LA in electricity market transactions,the operation mechanism of LA in day-ahead and real-time market is analyzed,respectively.Besides,truncated normal distribution is used to simulate the response accuracy of VES,and the response model of NSES is constructed at the same time.Then,the hierarchical market access index(HMAI)is introduced to quantify the risk of LA being eliminated in the market competition.Finally,combined with the priority response strategy of VES and HMAI,the capacity allocation model of NSES is established.As the capacity model is nonlinear,Monte Carlo simulation and adaptive particle swarm optimization algorithm are used to solve it.In order to verify the effectiveness of the model,the data from PJM market in the United States is used for testing.Simulation results show that the model established can provide the effective NSES capacity allocation strategy for LA to compensate the uncertainty of VES response,and the economic benefit of LA can be increased by 52.2%at its maximum.Through the reasonable NSES capacity allocation,LA is encouraged to improve its own resource level,thus forming a virtuous circle of market competition.

The operating schedule for battery energy storage companies in electricity market

This paper presents a series of operating schedules for Battery Energy Storage Companies(BESC)to provide peak shaving and spinning reserve services in the electricity markets under increasing wind penetration.As individual market participants,BESC can bid in ancillary services markets in an Independent System Operator(ISO)and contribute towards frequency and voltage support in the grid.Recent development in batteries technologies and availability of the day-ahead spot market prices would make BESC economically feasible.Profit maximization of BESC is achieved by determining the optimum capacity of Energy Storage Systems(ESS)required for meeting spinning reserve requirements as well as peak shaving.Historic spot market prices and frequency deviations from Australia Energy Market Operator(AEMO)are used for numerical simulations and the economic benefits of BESC is considered reflecting various aspects in Australia’s National Electricity Markets(NEM).