Decomposition and Equilibrium Achieving Distribution Locational Marginal Prices Using Trust-Region Method

Hanif, Sarmad; Zhang, Kai; Hackl, Christoph M.; Barati, Masoud; Gooi, Hoay Beng; Hamacher, Thomas

doi:10.1109/tsg.2018.2822766

Cited by 51 publications

(24 citation statements)

References 25 publications

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“…The reference properties for the linear approximate model eq. (5) are then obtained by solving the reference power flow problem of the electric grid, e.g., through a fixed-point solution methodology, and a global approximation for the sensitivity matrices can be obtained as a function of the reference properties as in [3]. The detailed formulation is omitted here for the sake of brevity.…”

Section: A Thermal Grid Modelmentioning

confidence: 99%

Distribution Locational Marginal Pricing for Combined Thermal and Electric Grid Operation

Troitzsch¹,

Grussmann²,

Zhang³

et al. 2020

Preprint

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Distribution locational marginal prices (DLMPs) have been formulated for electric distribution grids to economically dispatch distributed energy resources (DERs) while addressing operational constraints of the electric grid. This paper proposes to extend this methodology to thermal grids, i.e, district heating or cooling systems, and specifically the combined operation of thermal and electric grids. To this end, thermal and electric grid models are formulated in a linear approximate model fashion. Then, the derivation and decomposition of DLMPs is formulated based on the combined optimal operation problem, assuming a linear state space model form for flexible loads (FLs). The ability of the DLMPs to reflect operational constraints in the thermal grid is demonstrated for a test case with 22 FLs.

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Section: A Thermal Grid Modelmentioning

confidence: 99%

Distribution Locational Marginal Pricing for Combined Thermal and Electric Grid Operation

Troitzsch¹,

Grussmann²,

Zhang³

et al. 2020

Preprint

Self Cite

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“…The megavolt ampere (MVA) limit constraint of each line j in phase / is given by the quadratic constraint in (9). The three-phase real and reactive power imbalance is restricted to a small percentage ðD/ p ; D/ q Þ at the substation level and imposed by (10), (11) between any two phases. Additional substation, DG, and load constraints, including integer constraints from utility-scale ES units [30,31], if any, can also be accommodated as summarized in (12).…”

Section: Dso First-stage Optimization Problemmentioning

confidence: 99%

“…As a consequence of this transformation, new market pricing mechanisms that can facilitate the efficient and reliable operation of the grid are being investigated. In this line of research, pricing based on distribution locational marginal price (DLMP) has been widely studied and proposed [2][3][4][5][6][7][8][9][10]. However, it has been shown in several studies that adopting such market-based mechanisms in a distribution system with a high deployment of price-responsive DERs can adversely affect the distribution system operation by causing congestions [2,11].…”

Section: Introductionmentioning

confidence: 99%

“…Contrary to the transmission system, distribution systems are highly unbalanced and have higher losses and voltage drops due to higher r=x (resistance/reactance) ratio which, in addition to real power, requires power flow models that account for voltage magnitudes and reactive power flows and their associated losses. A few studies have incorporated power flow constraints to obtain losses, voltage violations, and line congestion prices using DLMP decomposition [7,8,10]. In these studies, the appearance of voltage violation and congestion components in a nodal DLMP signals the occurrence of an operational issue, partly caused by the marginal contribution of the nodal demand.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

HEMS-enabled transactive flexibility in real-time operation of three-phase unbalanced distribution systems

Faqiry

Wang

2019

J. Mod. Power Syst. Clean Energy

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This paper proposes a coordinated two-stage real-time market mechanism in an unbalanced distribution system which can utilize flexibility service from home energy management system (HEMS) to alleviate line congestion, voltage violation, and substation-level power imbalance. At the grid level, the distribution system operator (DSO) computes the distribution locational marginal prices (DLMP) and its energy, loss, congestion, and voltage violation components through comprehensive sensitivity analyses. By using the DLMP components in a firststage optimization problem, the DSO generates two price signals and sends them to HEMS to seek flexibility service. In response to the request of DSO, each home-level HEMS computes a flexibility range by incorporating the prices of DSO in its own optimization problem. Due to future uncertainties, the HEMS optimization problem is modeled as an adaptive dynamic programming (ADP) to minimize the total expected cost and discomfort of the household over a forward-looking horizon. The flexibility range of each HEMS is then used by the DSO in a second-stage optimization problem to determine new optimal dispatch points which ensure the efficient, reliable, and congestionfree operation of the distribution system. Lastly, the second-stage dispatch points are used by each HEMS to constrain its maximum consumption level in a final ADP to assign consumption level of major appliances such as energy storage, heating, ventilation and airconditioning , and water heater. The proposed method is validated on an IEEE 69-bus system with a large number of regular and HEMS-equipped homes in each phase.

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“…With the increasing integration of distributed energy resources (DERs) such as flexible loads (FLs) and distributed generators (DGs) into the electric distribution grid, the concept of distribution locational marginal prices (DLMPs) was developed to economically dispatch DERs, while keeping within the operational constraints of the electric grid. If not operated appropriately, DERs may lead to increased losses and congestion in the distribution grid, whereas DLMPs have been demonstrated to efficiently aid with loss reduction [1] and congestion management [2], [3].…”

Section: Introductionmentioning

confidence: 99%

Distribution Locational Marginal Pricing for Combined Thermal and Electric Grid Operation

Troitzsch¹,

Grussmann²,

Zhang³

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

Decomposition and Equilibrium Achieving Distribution Locational Marginal Prices Using Trust-Region Method

Cited by 51 publications

References 25 publications

Distribution Locational Marginal Pricing for Combined Thermal and Electric Grid Operation

Distribution Locational Marginal Pricing for Combined Thermal and Electric Grid Operation

HEMS-enabled transactive flexibility in real-time operation of three-phase unbalanced distribution systems

Distribution Locational Marginal Pricing for Combined Thermal and Electric Grid Operation

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