A multi-service approach for planning the optimal mix of energy storage technologies in a fully-renewable power supply

被引:67
作者
Haas, J. [1 ,3 ]
Cebulla, F. [2 ]
Nowak, W. [1 ]
Rahmann, C. [3 ]
Palma-Behnke, R. [3 ]
机构
[1] Univ Stuttgart, Dept Stochast Simulat & Safety Res Hydrosyst IWS, Stuttgart, Germany
[2] Univ Stuttgart, Dept Syst Anal & Technol Assessment, DLR, Inst Engn Thermodynam, Stuttgart, Germany
[3] Univ Chile, Dept Elect Engn, Energy Ctr, Santiago, Chile
关键词
Generation expansion planning; Flexibility; Integration of renewable technologies; Low-carbon systems; Electrical energy storage; Paris Agreement; SYSTEM; GENERATION; DEMAND; WIND; REQUIREMENTS; DESALINATION; ELECTRICITY; TRANSITION; CHILE; NEED;
D O I
10.1016/j.enconman.2018.09.087
中图分类号
O414.1 [热力学];
学科分类号
摘要
Energy storage systems (ESS) are a structural solution for the integration of renewable energy systems. To plan the optimal combination of ESS, storage expansion planning approaches are commonly used. They tend to focus on balancing the energy fluctuations from renewable technologies but are usually blind to the need for specific additional services required for dealing with forecast errors. Hence, they underestimate the real operating costs of the future power system and lead to suboptimal investment recommendations. In response, we propose a multi-service storage expansion approach. A linear programming optimization is developed, LEELO, to find the optimal investments in a 100% renewable system (based on solar photovoltaic and wind power) deciding on renewable generators and storage systems. In our formulation, we explicitly model the provisioning of power reserves and energy autonomy as additional services. A case study applies our model to Chile considering four regions and the (existing) hydro-power park, for a complete year with an hourly resolution. We systematically assess how our novel multi-service planning differs from conventional energy-based planning in terms of total costs, operation, and investment decisions (with a focus on ESS). Considering power reserves and energy autonomy reveals on average 20% higher costs that otherwise would not be captured in the expansion planning process. Regarding operation, ESS show only slight differences in the two planning models. All ESS participate in the provision of energy. As might be expected, batteries are the main provider of (short-term) power reserves, assisted by pumped-hydro, whereas hydrogen storage is responsible for providing (long-term) energy autonomy. However, the storage investment decisions differ significantly between both models. In our multi-service model, the attained power capacities and energy capacities are up to 1.6 and 3.2 times larger, respectively than in conventional planning. The resulting storage mix changes even more strongly: a general shift towards hydrogen systems is observed. Mainly batteries are substituted, while pumped hydro capacities stay relatively constant. The trend of the above results is consistent for various scenarios of wind and photovoltaic generation and for sensitivities of service parameters. Our findings underline the importance of modeling multi-services in the planning of renewable-based power systems.
引用
收藏
页码:355 / 368
页数:14
相关论文
共 54 条
[1]   Novel Methodology for Selecting Representative Operating Points for the TNEP [J].
Alvarez, Ricardo ;
Moser, Albert ;
Andrea Rahmann, Claudia .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2017, 32 (03) :2234-2242
[2]   Joint Distribution Network and Renewable Energy Expansion Planning Considering Demand Response and Energy Storage-Part I: Stochastic Programming Model [J].
Asensio, Miguel ;
Meneses de Quevedo, Pilar ;
Munoz-Delgado, Gregorio ;
Contreras, Javier .
IEEE TRANSACTIONS ON SMART GRID, 2018, 9 (02) :655-666
[3]   Hydrogen storage: Recent improvements and industrial perspectives [J].
Barthelemy, H. ;
Weber, M. ;
Barbier, F. .
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2017, 42 (11) :7254-7262
[4]   Considerations on the need for electricity storage requirements: Power versus energy [J].
Belderbos, Andreas ;
Virag, Ana ;
D'haeseleer, William ;
Delarue, Erik .
ENERGY CONVERSION AND MANAGEMENT, 2017, 143 :137-149
[5]  
Bogdanov D, 2016, 2016 INT EN SUST C, P1, DOI [10.1109/IESC.2016.7569508, DOI 10.1109/IESC.2016.7569508]
[6]   Assessment of Mid-Term Growth Assumptions and Learning Rates for Comparative Studies of CSP and Hybrid PV-Battery Power Plants [J].
Breyer, Christian ;
Afanasyeva, Svetlana ;
Brakemeier, Dietmar ;
Engelhard, Manfred ;
Giuliano, Stefano ;
Puppe, Michael ;
Schenk, Heiko ;
Hirsch, Tobias ;
Moser, Massimo .
INTERNATIONAL CONFERENCE ON CONCENTRATING SOLAR POWER AND CHEMICAL ENERGY SYSTEMS (SOLARPACES 2016), 2017, 1850
[7]   A review on compressed air energy storage: Basic principles, past milestones and recent developments [J].
Budt, Marcus ;
Wolf, Daniel ;
Span, Roland ;
Yan, Jinyue .
APPLIED ENERGY, 2016, 170 :250-268
[8]   Large-scale integration of renewable energies and impact on storage demand in a European renewable power system of 2050-Sensitivity study [J].
Bussar, Christian ;
Stoecker, Philipp ;
Cai, Zhuang ;
Moraes, Luiz, Jr. ;
Magnor, Dirk ;
Wiernes, Pablo ;
van Bracht, Niklas ;
Moser, Albert ;
Sauer, Dirk Uwe .
JOURNAL OF ENERGY STORAGE, 2016, 6 :1-10
[9]   Electrical energy storage in highly renewable European energy systems: Capacity requirements, spatial distribution, and storage dispatch [J].
Cebulla, F. ;
Naegler, T. ;
Pohl, M. .
JOURNAL OF ENERGY STORAGE, 2017, 14 :211-223
[10]   Merit order or unit-commitment: How does thermal power plant modeling affect storage demand in energy system models? [J].
Cebulla, F. ;
Fichter, T. .
RENEWABLE ENERGY, 2017, 105 :117-132