On the Trade-Off Between Environmental and Economic Objectives in Community Energy Storage Operational Optimization

The need to limit climate change has led to policies that aim for the reduction of greenhouse gas emissions. Often, a trade-off exists between reducing emissions and associated costs. In this article, a multi-objective optimization framework is proposed to determine this trade-off when operating a Community Energy Storage (CES) system in a neighbourhood with high shares of photovoltaic (PV) electricity generation capacity. The Pareto frontier of costs and emissions objectives is established when the CES system would operate on the day-ahead spot market. The emission profile is constructed based on the marginal emissions. Results show that costs and emissions can simultaneously be decreased for a range of solutions compared to reference scenarios with no battery or a battery only focused on increasing self-consumption, for very attractive CO2 abatement costs and without hampering self-consumption of PV-generated electricity. Results are robust for battery degradation, whereas battery efficiency is found to be an important determining factor for simultaneously decreasing costs and emissions. The operational schedules are tested against violating transformer, line and voltage limits through a load flow analysis. The proposed framework can be extended to employ a wide range of objectives and/or location-specific circumstances.

[1]  Tarek AlSkaif,et al.  A framework for the provision of flexibility services at the transmission and distribution levels through aggregator companies , 2019, Sustainable Energy, Grids and Networks.

[2]  João P. S. Catalão,et al.  Combining the Flexibility From Shared Energy Storage Systems and DLC-Based Demand Response of HVAC Units for Distribution System Operation Enhancement , 2019, IEEE Transactions on Sustainable Energy.

[3]  Peerapat Vithayasrichareon,et al.  Impact of Electric Vehicles and Solar PV on Future Generation Portfolio Investment , 2015, IEEE Transactions on Sustainable Energy.

[4]  S. Sivasubramani,et al.  Multi-objective dynamic economic and emission dispatch with demand side management , 2018 .

[5]  Adam Hawkes,et al.  The future cost of electrical energy storage based on experience rates , 2017, Nature Energy.

[6]  Badrul Chowdhury,et al.  Optimal Sizing and Operation of Battery Energy Storage Systems Connected to Wind Farms Participating in Electricity Markets , 2019, IEEE Transactions on Sustainable Energy.

[7]  Bryan Palmintier,et al.  Impact of operational flexibility on electricity generation planning with renewable and carbon targets , 2016, 2016 IEEE Power and Energy Society General Meeting (PESGM).

[8]  R. K. Ursem Multi-objective Optimization using Evolutionary Algorithms , 2009 .

[9]  C. Y. Chung,et al.  Reliability/Cost Evaluation With PEV and Wind Generation System , 2014, IEEE Transactions on Sustainable Energy.

[10]  E. W. C. Wilkins,et al.  Cumulative damage in fatigue , 1956 .

[11]  T. Schmidt,et al.  The economic viability of battery storage for residential solar photovoltaic systems – A review and a simulation model , 2014 .

[12]  Marko Milovanovic Smart grid: rendement voor iedereen , 2013 .

[13]  Robert Harmsen,et al.  How much CO2 emissions do we reduce by saving electricity? A focus on methods , 2013 .

[14]  Dirk Uwe Sauer,et al.  Modeling mechanical degradation in lithium ion batteries during cycling: Solid electrolyte interphase fracture , 2015 .

[15]  Manel Guerrero Zapata,et al.  Reputation-based joint scheduling of households appliances and storage in a microgrid with a shared battery , 2017 .

[16]  G. Kerber Aufnahmefähigkeit von Niederspannungsverteilnetzen für die Einspeisung aus Photovoltaikkleinanlagen , 2011 .

[17]  Lars Ole Valøen,et al.  Life Cycle Assessment of a Lithium‐Ion Battery Vehicle Pack , 2014 .

[18]  Pierluigi Siano,et al.  Stochastic optimal scheduling of distributed energy resources with renewables considering economic and environmental aspects , 2018 .

[19]  A. Jossen,et al.  Economics of Residential Photovoltaic Battery Systems in Germany: The Case of Tesla’s Powerwall , 2016 .

[20]  Martin Kumar Patel,et al.  An interdisciplinary review of energy storage for communities: Challenges and perspectives , 2017 .

[21]  G.B.M.A. Litjens,et al.  Economic benefits of combining self-consumption enhancement with frequency restoration reserves provision by photovoltaic-battery systems , 2018, Applied Energy.

[22]  Ioannis Lampropoulos,et al.  On the Use of Average versus Marginal Emission Factors , 2019, SMARTGREENS.

[23]  Alejandro Pena-Bello,et al.  Additional Emissions and Cost from Storing Electricity in Stationary Battery Systems. , 2019, Environmental science & technology.

[24]  Stuart A. Norman,et al.  Optimum community energy storage system for demand load shifting , 2016 .

[25]  Tarek AlSkaif,et al.  Benchmark analysis of day-ahead solar power forecasting techniques using weather predictions , 2019, 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC).

[26]  John N. Hooker,et al.  Optimization and , 2000 .

[27]  Daniel Schwabeneder,et al.  Portfolio optimization of energy communities to meet reductions in costs and emissions , 2019, Energy.

[28]  Andreas Jossen,et al.  Ageing of lithium-ion battery modules with dissipative balancing compared with single-cell ageing , 2016 .

[29]  W. V. Sark,et al.  Techno-economic analysis of household and community energy storage for residential prosumers with smart appliances , 2018 .

[30]  M. Nasir,et al.  Solar PV-Based Scalable DC Microgrid for Rural Electrification in Developing Regions , 2018, IEEE Transactions on Sustainable Energy.

[31]  Remus Teodorescu,et al.  Accelerated lifetime testing methodology for lifetime estimation of Lithium-ion batteries used in augmented wind power plants , 2013, 2013 IEEE Energy Conversion Congress and Exposition.

[32]  Wouter L. Schram,et al.  Photovoltaic systems coupled with batteries that are optimally sized for household self-consumption: Assessment of peak shaving potential , 2018, Applied Energy.

[33]  D. Sauer,et al.  Calendar and cycle life study of Li(NiMnCo)O2-based 18650 lithium-ion batteries , 2014 .

[34]  M. Verbrugge,et al.  Degradation of lithium ion batteries employing graphite negatives and nickel-cobalt-manganese oxide + spinel manganese oxide positives: Part 1, aging mechanisms and life estimation , 2014 .

[35]  Michael Stadler,et al.  Value streams in microgrids: A literature review , 2016 .

[36]  P.P.J. van den Bosch,et al.  Hierarchical predictive control scheme for distributed energy storage integrated with residential demand and photovoltaic generation , 2015 .

[37]  T. J. Walker,et al.  Demonstration of Community Energy Storage fleet for load leveling, reactive power compensation, and reliability improvement , 2012, 2012 IEEE Power and Energy Society General Meeting.

[38]  M. Webber,et al.  The impacts of storing solar energy in the home to reduce reliance on the utility , 2017, Nature Energy.