TY - CHAP
T1 - The microgrid investment and planning in rural locations
T2 - Microgrids for Rural Areas: Research and case studies
Y1 - 2020/07//
SP - 33
EP - 54
A1 - Miguel Heleno
A1 - Carmen Bas Domenech
A1 - Gonçalo Cardoso
A1 - Salman Mashayekh
AB - This chapter presents different methods and tools for microgrid optimal investment and planning problem, focusing on specific methodological aspects addressing the challenges of rural microgrids design. In particular, three aspects of rural microgrids planning are analyzed: (1) the multi-energy nature of rural microgrids, where electricity coexists with other energy vectors (such as heat distribution); (2) the occupation of large portions of the rural territory, which requires planning methods to consider the microgrid internal network constraints; (3) the remote (and sometimes off-the-grid) locations of rural microgrids, which require security criteria and multi-objective approaches to be considered in planning problem. These three methodological aspects are discussed using the example of a real microgrid in Alaska.
JF - Microgrids for Rural Areas: Research and case studies
PB - The Institution of Engineering and Technology
CY - London
ER -
TY - CONF
T1 - A Multi- Period Investment Model for Behind-the-Meter PV and Storage
T2 - 2020 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)
Y1 - 2020/02//
A1 - Julia Lindberg
A1 - Miguel Heleno
A1 - Gonçalo Cardoso
A1 - Alan Valenzuela
AB - Behind -the-meter photovoltaic (PV) systems, especially when combined with storage units, are becoming an attractive solution for individual prosumers to decrease electricity costs and reduce the dependence from the utility grid. The technology costs of PV and batteries are expected to continue to decrease during the next decade, while utility energy costs and feed-in remuneration will face regulatory changes. In these scenarios of intense variations of technology and operation costs, multi-period investment approaches become relevant, by allowing for an optimal schedule of the investments throughout the years. In this paper, we propose a multi-period optimal investment model for behind-the-meter PV and storage considering multi-year variations of technology and energy costs.
JF - 2020 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)
PB - IEEE
CY - Washington, DC, USA
ER -
TY - JOUR
T1 - A Mixed Integer Linear Programming Approach for Optimal DER Portfolio, Sizing, and Placement in Multi-Energy Microgrids
JF - Applied Energy
Y1 - 2017/02//
SP - 154
EP - 168
A1 - Salman Mashayekh
A1 - Michael Stadler
A1 - Gonçalo Cardoso
A1 - Miguel Heleno
KW - electrical network
KW - heating and cooling network
KW - mixed-21 integer linear program
KW - Multi-energy microgrid design
KW - power flow
AB - Optimal microgrid design is a challenging problem, especially for multi-energy microgrids with electricity, heating, and cooling loads as well as sources, and multiple energy carriers. To address this problem, this paper presents an optimization model formulated as a mixed-integer linear program, which determines the optimal technology portfolio, the optimal technology placement, and the associated optimal dispatch, in a microgrid with multiple energy types. The developed model uses a multi-node modeling approach (as opposed to an aggregate single-node approach) that includes electrical power flow and heat flow equations, and hence, offers the ability to perform optimal siting considering physical and operational constraints of electrical and heating/cooling networks. The new model is founded on the existing optimization model DER-CAM, a state-of-the-art decision support tool for microgrid planning and design. The results of a case study that compares single-node vs. multi-node optimal design for an example microgrid show the importance of multi-node modeling. It has been shown that single-node approaches are not only incapable of optimal DER placement, but may also result in sub-optimal DER portfolio, as well as underestimation of investment costs.
PB - To be published in Applied Energy
VL - 187
U2 - LBNL-1006559
ER -
TY - JOUR
T1 - Modelling of Non-linear CHP Efficiency Curves in Distributed Energy Systems
JF - Applied Energy
Y1 - 2015/06//
SP - 334
EP - 347
A1 - Christian Milan
A1 - Michael Stadler
A1 - Gonçalo Cardoso
A1 - Salman Mashayekh
KW - combined heat and power (chp)
KW - Distributed energy resources
KW - Linearization
KW - Microgrid modeling
KW - Non-linear optimization
KW - Renewable energy supply system
AB - Distributed energy resources gain an increased importance in commercial and industrial building design. Combined heat and power (CHP) units are considered as one of the key technologies for cost and emission reduction in buildings. In order to make optimal decisions on investment and operation for these technologies, detailed system models are needed. These models are often formulated as linear programming problems to keep computational costs and complexity in a reasonable range. However, CHP systems involve variations of the efficiency for large nameplate capacity ranges and in case of part load operation, which can be even of non-linear nature. Since considering these characteristics would turn the models into non-linear problems, in most cases only constant efficiencies are assumed. This paper proposes possible solutions to address this issue. For a mixed integer linear programming problem two approaches are formulated using binary and Special-Ordered-Set (SOS) variables. Both suggestions have been implemented into the optimization model DER-CAM to simulate investment decisions of CHP micro-turbines and CHP fuel cells with variable efficiencies. The approaches have further been applied successfully in a case study with four different commercial buildings. Comparison of the results between the standard version and the new approaches indicate that total annual system costs remain almost unchanged. System performance is subject to change and storage technologies become more important. Part load operation has mainly been found important for fuel cell units. The micro-turbine is found almost exclusively in full load, thus rendering the application of the new approaches for this technology unnecessary for the considered unit sizes and building types. The approach using binary variables was the most promising method to model variable efficiencies in terms of computational costs and results. It should especially be considered for specific fuel cell technologies. Further investigation on the impacts of this approach on the prediction of fuel cell and micro-turbine performance is suggested.
VL - 148
U2 - LBNL-6979E
ER -
TY - JOUR
T1 - Modeling of Thermal Storage Systems in MILP Distributed Energy Resource Models
JF - Applied Energy
Y1 - 2015/01//
SP - 782
EP - 792
A1 - David Steen
A1 - Michael Stadler
A1 - Gonçalo Cardoso
A1 - Markus Groissböck
A1 - Nicholas DeForest
A1 - Chris Marnay
KW - distributed energy resources (der)
KW - Energy optimization
KW - Investment planning
KW - Renewables
KW - Thermal energy storage
AB - Thermal energy storage (TES) and distributed generation technologies, such as combined heat and power (CHP) or photovoltaics (PV), can be used to reduce energy costs and decrease CO2 emissions from buildings by shifting energy consumption to times with less emissions and/or lower energy prices. To determine the feasibility of investing in TES in combination with other distributed energy resources (DER), mixed integer linear programming (MILP) can be used. Such a MILP model is the well-established Distributed Energy Resources Customer Adoption Model (DER-CAM); however, it currently uses only a simplified TES model to guarantee linearity and short run-times. Loss calculations are based only on the energy contained in the storage. This paper presents a new DER-CAM TES model that allows improved tracking of losses based on ambient and storage temperatures, and compares results with the previous version. A multi-layer TES model is introduced that retains linearity and avoids creating an endogenous optimization problem. The improved model increases the accuracy of the estimated storage losses and enables use of heat pumps for low temperature storage charging. Results indicate that the previous model overestimates the attractiveness of TES investments for cases without possibility to invest in heat pumps and underestimates it for some locations when heat pumps are allowed. Despite a variation in optimal technology selection between the two models, the objective function value stays quite stable, illustrating the complexity of optimal DER sizing problems in buildings and microgrids.
PB - Elsevier
VL - 137
UR - http://www.sciencedirect.com/science/article/pii/S0306261914007181
U2 - LBNL-6757E
ER -
TY - JOUR
T1 - Microgrid Reliability Modeling and Battery Scheduling Using Stochastic Linear Programming
JF - Journal of Electric Power Systems Research
Y1 - 2013/06//
SP - 61
EP - 69
A1 - Gonçalo Cardoso
A1 - Michael Stadler
A1 - Afzal S. Siddiqui
A1 - Chris Marnay
A1 - Nicholas DeForest
A1 - Ana Barbosa-Póvoa
A1 - Paulo Ferrão
AB - This paper describes the introduction of stochastic linear programming into Operations DER-CAM, a tool used to obtain optimal operating schedules for a given microgrid under local economic and environmental conditions. This application follows previous work on optimal scheduling of a lithium-iron-phosphate battery given the output uncertainty of a 1 MW molten carbonate fuel cell. Both are in the Santa Rita Jail microgrid, located in Dublin, California. This fuel cell has proven unreliable, partially justifying the consideration of storage options. Several stochastic DER-CAM runs are executed to compare different scenarios to values obtained by a deterministic approach. Results indicate that using a stochastic approach provides a conservative yet more lucrative battery schedule. Lower expected energy bills result, given fuel cell outages, in potential savings exceeding 6%.
VL - 103
U2 - LBNL-6309E
ER -
TY - Generic
T1 - Microgrid Modeling Using the Stochasting Distributed Energy Resources Customer Adoption Model (DER-CAM)
Y1 - 2012/10//
A1 - Michael Stadler
A1 - Gonçalo Cardoso
A1 - Mohammad Bozchalui
A1 - Ratnesh Sharma
A1 - Chris Marnay
A1 - Afzal S. Siddiqui
A1 - Markus Groissböck
U2 - LBNL-5937E
ER -
TY - CONF
T1 - Modeling Electric Vehicle Benefits Connected to Smart Grids
T2 - 7th IEEE Vehicle Power and Propulsion Conference
Y1 - 2011/09//
A1 - Michael Stadler
A1 - Chris Marnay
A1 - Ratnesh Sharma
A1 - Gonçalo Mendes
A1 - Maximillian Kloess
A1 - Gonçalo Cardoso
A1 - Olivier Mégel
A1 - Afzal S. Siddiqui
AB - Connecting electric storage technologies to smartgrids will have substantial implications in building energy systems. Local storage will enable demand response. Mobile storage devices in electric vehicles (EVs) are in direct competition with conventional stationary sources at the building. EVs will change the financial as well as environmental attractiveness of on-site generation (e.g. PV, or fuel cells). In order to examine the impact of EVs on building energy costs and CO2 emissions in 2020, a distributed-energy-resources adoption problem is formulated as a mixed-integer linear program with minimization of annual building energy costs or CO2 emissions. The mixed-integer linear program is applied to a set of 139 different commercial buildings in California and example results as well as the aggregated economic and environmental benefits are reported. The research shows that considering second life of EV batteries might be very beneficial for commercial buildings.
JF - 7th IEEE Vehicle Power and Propulsion Conference
PB - LBNL
CY - Chicago, IL
U2 - LBNL-4929E
ER -