MILP formulation for generation and storage asset sizing and sitting for reliability constrained system planning

Opathella, C.; Elkasrawy, Ayman; Mohamed, Amr A.; Venkatesh, Bala

doi:10.1016/j.ijepes.2019.105529

Cited by 19 publications

(17 citation statements)

References 19 publications

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“…See References 15,20,110‐112*. On the other hand, Reference 113* uses a MILP formulation to perform dynamic anticipative investment optimization with a high level of technical details. The temporal facet is restricted to two typical days per year to limit computational costs.…”

Section: Survey Of Optimization Methods For Energy System Planningmentioning

confidence: 99%

Techno‐economic planning of local energy systems through optimization models: a survey of current methods

Cuisinier

Bourasseau

Ruby

et al. 2020

Intl J of Energy Research

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Summary Energy system planning is a difficult task, since it involves long‐term decision‐makings with multiple dimensions: technical, economic, social, ecological, and political. The rise of distributed and multi‐energy systems including new technologies has further increased this complexity. Techno‐economic studies based on optimization models have recently received much attention in the literature. They are essential to grasp energy systems complexity and provide decision support. This work targets methodological issues related to local systems while comparing them with methods used at larger scales. First, a new framework providing a comprehensive vision of added values and limits of optimization models is presented. Then, the main methodological trends as well as several undertaken research paths are identified based on the analysis of more than 60 research papers. The review results are summarized in a complete and concise table. Finally, future research topics are discussed including the operational facets of investment optimization models in case of high intermittent energy shares, flexibility issues and long‐term operational decisions. The results provide useful information to modellers or researchers that look for appropriate and state‐of‐the‐art optimization methods, or aim to deepen current research paths. Hence, they will facilitate the planning and development of energy systems for the future.

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Section: Survey Of Optimization Methods For Energy System Planningmentioning

confidence: 99%

Techno‐economic planning of local energy systems through optimization models: a survey of current methods

Cuisinier

Bourasseau

Ruby

et al. 2020

Intl J of Energy Research

View full text Add to dashboard Cite

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“…Moreover, the optimal value for initial energy stored in the BESS is set by the optimization program. Determining these values is critical to optimize the contribution of the BESS in the system [37]. The power and energy capacities of the BESS, and the initial energy stored are limited to be positive values.…”

Section: Energy Storagementioning

confidence: 99%

“…Formulations for the energy storage are shown in Equations (27)- (37) and are similar to Equations (8)- (18).…”

Section: Energy Storagementioning

confidence: 99%

Optimal Asset Planning for Prosumers Considering Energy Storage and Photovoltaic (PV) Units: A Stochastic Approach

et al. 2020

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In the distribution system, customers have increasingly use renewable energy sources and battery energy storage systems (BESS), transforming traditional loads into active prosumers. Therefore, methodologies are needed to provide prosumers with tools to optimize their investments and increase business opportunities. In this paper, a stochastic mixed integer linear programming (MILP) formulation is proposed to solve for optimal sizes of prosumer assets, considering the use of a BESS and photovoltaic (PV) units. The objective is to minimize the total cost of the system, which is defined as the combination of a solar PV system investment, BESS investment, maintenance costs of assets, and the cost of electricity supplied by the grid. The developed method defines the optimal size of PV units, the power/energy capacities of the BESS, and the optimal value for initial energy stored in the BESS. Both deterministic and stochastic approaches were explored. For each approach, the proposed model was tested for three cases, providing a varying combination of the use of grid power, PV units, and BESS. The optimal values from each case were compared, showing that there is potential to achieve more economic plans for prosumers when PV and BESS technologies are taken into account.

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“…Wu et al [129] considered investment planning for generators and pumped-hydro storage constrained by the low-carbon requirements of the system. Opathella et al [126] analysed the influence of generator contingencies in a long-term planning model. Tejada-Arango et al [12] proposed a change of approach for unit commitment used in planning models from energy-based to power-based.…”

Section: Coordinated Investments In Ess and Generatorsmentioning

confidence: 99%

“…Planning Solving Technique [20,22,23,30,43,46,[49][50][51]53,54,57,59,73,74,78,[88][89][90]105] [ 119,125,130,156] LP [1,16-18,20,25,32,33,35,44,47,50,52, 56-58,60,61,63,65,66,70-72,76,79-83, 86,92,94-96,100-102,104,106,107] [ 14,28,[109][110][111][112][113][114][115]117,121,122,126,127,131,[133][134][135][136][137]139,148,149,155,156,<...>…”

Section: Operationmentioning

confidence: 99%

Operating and Investment Models for Energy Storage Systems

2020

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In the context of climate changes and the rapid growth of energy consumption, intermittent renewable energy sources (RES) are being predominantly installed in power systems. It has been largely elucidated that challenges that RES present to the system can be mitigated with energy storage systems (ESS). However, besides providing flexibility to intermittent RES, ESS have other sources of revenue, such as price arbitrage in the markets, balancing services, and reducing the cost of electricity procurement to end consumers. In order to operate the ESS in the most profitable way, it is often necessary to make optimal siting and sizing decisions, and to determine optimal ways for the ESS to participate in a variety of energy and ancillary service markets. As a result, many publications on ESS models with various goals and operating environments are available. This paper aims at presenting the results of these papers in a structured way. A standard ESS model is first outlined, and that is followed by a literature review on operational and investment ESS models at the transmission and distribution levels. Both the price taking and price making models are elaborated on and presented in detail. Based on the examined body of work, the paper is concluded with recommendations for future research paths in the analysis of ESS.

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MILP formulation for generation and storage asset sizing and sitting for reliability constrained system planning

Cited by 19 publications

References 19 publications

Techno‐economic planning of local energy systems through optimization models: a survey of current methods

Techno‐economic planning of local energy systems through optimization models: a survey of current methods

Optimal Asset Planning for Prosumers Considering Energy Storage and Photovoltaic (PV) Units: A Stochastic Approach

Operating and Investment Models for Energy Storage Systems

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