Planning Framework for BESSs in Microgrids (MGs) Using Linearized AC Power Flow Approach

Habibifar, Reza; Saber, Hossein; Gharigh, M.R. Karimi; Ehsan, Mehdi

doi:10.1109/sgc.2018.8777868

Cited by 9 publications

(6 citation statements)

References 15 publications

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“…The reason behind considering the DC power flow equations in the proposed planning model is related to its computational efficiency. It is worth mentioning that the computational burden of DC power flow is significantly less than AC and linearized AC power flow models [37,38]. Moreover, since the X/R ratio in the transmission level of power systems is very high, employing the DC power flow model can be an efficient approach in TEP studies [39].…”

Section: ∑ 𝑃mentioning

confidence: 99%

Developing a Robust Expansion Planning Approach for Transmission Networks and Privately-Owned Renewable Sources

et al. 2023

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Power system restructuring has changed transmission expansion planning (TEP) and caused many complications due to conflicting and contradictory objectives. The transmission capacity expansion would significantly affect the revenue of investor-owned renewable energy sources (RESs). Thus, the investment decisions on merchant RESs must be considered in the TEP studies conducted by the transmission system operator (TSO). In this regard, this paper aims to propose a multi-objective co-planning of investment in transmission networks and merchant RESs with three objective functions: minimizing the investment cost of newly deployed transmission lines, minimizing transmission congestion cost, and minimizing load curtailment in N-1 conditions. Moreover, the TSO guarantees a desirable rate of return for private investors to finance renewable energy projects. Further, a robust optimization (RO) technique is employed to cope with the uncertainties associated with demand and renewable energy production. Also, a posteriori multi-objective optimization algorithm, i.e., the non-dominated sorting genetic algorithm (NSGAII), is applied to solve the advanced optimization problem, followed by the fuzzy min-max method to acquire the final optimal solution. Finally, the IEEE RTS 24-bus test system is utilized to demonstrate the effectiveness and applicability of the suggested approach.

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Section: ∑ 𝑃mentioning

confidence: 99%

Developing a Robust Expansion Planning Approach for Transmission Networks and Privately-Owned Renewable Sources

et al. 2023

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“…Hence, considering all square planes for all sides available in the set Ψ M , a regular polygon is obtained, which is almost a circular plane. Therefore, constraint (19) in the linearized format is given by constraint (39) [9,98].…”

Section: Linear Approximation Model Of the Lower-level Problemmentioning

confidence: 99%

“…To extract a linear relationship using the Big M method, first, an auxiliary variable such as Γ is used, which is equal to the multiplication of binary and continuous variables, that is, Γ = z.χ. Then, two linear equations, (98) and (99), replace the mentioned nonlinear relationship. In the two linear and nonlinear relationships, if z = 1 (z = 0), then…”

Section: Single-level Formulation Of the Proposed Schemementioning

confidence: 99%

“…Hence, considering all square planes for all sides available in the set Ψ M , a regular polygon is obtained, which is almost a circular plane. Therefore, constraint () in the linearized format is given by constraint () [9, 98].

\begin{eqnarray} &&P_{b,k,l,\omega }^{eL}\cos \left( {m \times \Delta \varpi } \right) + Q_{b,k,l,\omega }^{eL}\sin \left( {m \times \Delta \varpi } \right)\nonumber\\ &&\qquad\le \bar{S}_{b,k}^{eL}:\underline {\varphi ^{\prime}} _{b,k,l,\omega }^{sl}\quad\forall b,k,l,\omega ,m\end{eqnarray}

…”

Section: Single‐level Formulationmentioning

confidence: 99%

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Resilience‐oriented expansion planning of multi‐carrier microgrid utilizing bi‐level technique

Dehshiri Badi,

Amir,

Shariatmadar

2023

IET Renewable Power Gen

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This paper presents the generation and transmission expansion planning (GTEP) in electricity and gas networks by considering their resilience against floods and earthquakes. These networks supply electricity, heat, and gas consumption energies as a multi‐carrier microgrid. The scheme is expressed in the form of bi‐level optimization, the upper level of which is the minimization of generation and transmission planning cost (total investment cost and expected operating cost) in the mentioned networks constrained to the investment budget and the planning model of the mentioned elements. Lower‐level formulation minimizes the total expected annual operating cost of these networks and the expected outage cost of electricity, heat, and gas consumers in the event of floods and earthquakes. This formulation is bound by the power flow equations of electricity and gas networks, the operation and resilience constraints of the networks, and the limitation on generation capability. In this problem, the expected energy not‐supplied and the outage cost during natural disasters are considered resilience indicators. Next, a single‐level model for the proposed design is extracted from the Karush–Kuhn–Tucker (KKT) method. The basic requirement of this method is the convexity of the lower‐level constraints. For this purpose, first, a linear approximation model is obtained for the lower‐level constraints of the problem. Furthermore, stochastic optimization is adopted to model the uncertainty of load, renewable power, and network equipment availability during floods and earthquakes. Finally, the extracted numerical results confirm the capability of the proposed scheme in improving the operation and resilience of the mentioned networks using optimal generation and transmission planning.

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“…e intense increase in fossil fuel prices and environmental concerns of greenhouse gases (GHG) has made policy-makers and power system planners find alternatives for conventional thermal and gas power plants [1,2]. In recent decades, exploiting renewable energy sources (RESs) in the generation sector of power systems has been increasing rapidly [3,4].…”

Section: Aimmentioning

confidence: 99%

Bidding Strategy of a Wind-Thermal GENCO considering Piecewise Linear AC Power Flow and Correlated Uncertainties

Daealhaq

Hassan

Ghanimi

et al. 2022

International Transactions on Electrical Energy Systems

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In deregulated electricity markets, generation companies (GENCO) try to maximize their economic benefits considering the electricity demand, transmission network condition, and other participants’ behaviors. The increasing penetration of renewable sources such as wind power generation with intermittent nature poses several challenges to the participation of GENCOs in the electricity market. Thus, this paper presents a stochastic bilevel optimization model to determine the coordinated bidding strategy of a wind-thermal GENCO with the aim of maximizing its profit in the day-ahead and real-time balancing market. Herein, the model aims to maximize the profit of GENCO in the day-ahead and the balancing market in the upper-level problem while minimizing the operation cost of the system in the lower-level problem. The uncertainties of wind power generation and electricity demand are modeled by defining a set of scenarios considering their mutual correlation using the copula technique. Additionally, incorporating AC power flow constraints in the proposed optimization model offers a better solution to the coordinated bidding strategy of the wind-thermal GENCO. Further, the nonlinear AC power flow equations are linearized using the piecewise approximation technique to reduce the computational complexity and enhance the accuracy of the optimal solution. In the end, the developed algorithm is implemented on the IEEE 24-bus RTS, and the simulation results are provided to validate the efficiency and applicability of the proposed coordinated bidding strategy model. The results advocate that the participation of the thermal unit along with the wind farm might mitigate the risk of uncertainties, but it causes an intense increase in the locational marginal price of the system. Importantly, the simulation results indicate the computational efficiency of the model by developing an exact AC power flow model without compromising the results. Notably, it has been found that the profit of the wind-thermal GENCO would be increased by 35.2% employing the copula technique to model the mutual correlation of uncertain parameters.

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Planning Framework for BESSs in Microgrids (MGs) Using Linearized AC Power Flow Approach

Cited by 9 publications

References 15 publications

Developing a Robust Expansion Planning Approach for Transmission Networks and Privately-Owned Renewable Sources

Developing a Robust Expansion Planning Approach for Transmission Networks and Privately-Owned Renewable Sources

Resilience‐oriented expansion planning of multi‐carrier microgrid utilizing bi‐level technique

Bidding Strategy of a Wind-Thermal GENCO considering Piecewise Linear AC Power Flow and Correlated Uncertainties

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