Decoupled Economic Dispatch Using the Participation Factors Load Flow

Guoyu,; Galiana,; Low,

doi:10.1109/mper.1985.5526638

Cited by 4 publications

(6 citation statements)

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“…This is called as single slack bus model. In the economic dispatch, the difference between generation and demand refers to system power imbalance and the distributed slack bus concept is adopted with participation factors [44,45,48,50] In this way, the imbalance power distributed among the conventional generators based on specified participation factor. In the uncertain operating conditions, the treatment of slack bus behavior is crucial.…”

Section: B Operational Subproblem: Participation Factor Power Flow (P...mentioning

confidence: 99%

“…Traditional economic dispatch problem [44,47,49,51,52] finds the real power generation for each plant providing the minimum generation cost that satisfies the power balance equation for the network. Lagrange multiplier method is typically used to solve such problem and the equal incremental cost is denoted as λ which is also the lagrange multiplier of the Lagrange function is given in (2) [53][54].…”

Section: B Operational Subproblem: Participation Factor Power Flow (P...mentioning

confidence: 99%

“…Several studies in the literature have combined the participation factors with power flow studies to find an economical dispatch of generators. The pioneer work is presented in [44], in which the treatment of slack bus is introduced under decoupled economic dispatch using participation factor power flow. In [45], the generator contributions are derived by reformulating the power flow problem in terms of distributed slack bus concept.…”

Section: Introductionmentioning

confidence: 99%

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Stochastic AC Transmission Expansion Planning: A Chance Constrained Distributed Slack Bus Approach With Wind Uncertainty

Mir

Karatepe

2022

IEEE Access

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Integrating more renewable energy sources into the grid leads to a more vulnerable power system and presents challenges for power system planners. This paper proposes a probabilistic overload constraint based AC transmission expansion planning model. In terms of economic dispatch, generation adequacy and network constraints are assessed using a probabilistic participation factor power flow. Generation participation factors, which are handled in the AC power flow equations, are used to manage mismatch power that comes from uncertainties as well as transmission loss of the system in a distributed slack bus concept. Combinations of load, wind and N-1 contingency uncertainties are evaluated with Monte Carlo Simulation and the loading limits for the existing and candidate lines and violations on bus voltages are enforced as probabilistic constraints using chance constraint programming. The investment decisions taken under various operating conditions are re-evaluated under a new set of wind power uncertainty that differs from those utilized in the optimization process, and the resulting TEP decisions are analyzed from a risk perspective. The proposed method allows for the uncertain operating conditions to be easily and accurately adapted to the ACTEP optimization. The optimization results show that the participation factor power flow is a promising tool for evaluating probabilistic operating conditions, which can be used to explore the possibility of violations under different uncertainty conditions. INDEX TERMSChance constrained programming, distributed slack bus, participation factor, transmission expansion planning, wind power. NOMENCLATURE 𝑖, 𝑘 Bus no 𝑐 Contingency 𝛽 Not overload probability 𝑁 Total number of buses Ω Total set of candidate lines Ω 𝐶 Total set of contingency 𝑃 𝐺𝑖 Real power output of a generator at bus i 𝑃 𝐷𝑖 Load at bus i 𝑃 𝐼𝑀𝐵 Imbalance power 𝐶 𝑖 Quadratic cost function of generator at bus i 𝐶 𝑖 (𝑃 𝐺𝑖 ) Total generation cost 𝑎 𝑖 , 𝑏 𝑖 , 𝑐 𝑖 Cost coefficients of generator at bus i 𝑃 𝐺𝑖_𝑠𝑐ℎ Scheduled real power output of a generator at bus i 𝑃 𝐺𝑖_𝑢𝑝𝑑 Updated real power output of a generator at bus i 𝑃𝑓 𝑖 Participation factor of generator at bus i 𝑃 𝑖 Injected active power at bus i 𝑄 𝑖 Injected reactive power at bus i 𝑃 𝑠𝑝,𝑖 Specified (known) active power at bus i 𝑄 𝑠𝑝,𝑖 Specified (known) reactive power at bus i ∆𝑃 Mismatch active power vector ∆𝑄 Mismatch reactive power vector 𝑉 𝑖 Voltage magnitude at bus i 𝜃 𝑖 Voltage angle at bus i 𝑉 𝑖 𝑐 Voltage magnitude at bus i at contingency operating condition c 𝜃 𝑖 𝑐 Voltage angle at bus i at contingency operating condition c 𝑔 𝑖𝑘 Conductance of line i-k 𝑏 𝑖𝑘 Susceptance of line i-k 𝑏 𝑖𝑘 𝑠ℎ

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Section: B Operational Subproblem: Participation Factor Power Flow (P...mentioning

confidence: 99%

Section: B Operational Subproblem: Participation Factor Power Flow (P...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Stochastic AC Transmission Expansion Planning: A Chance Constrained Distributed Slack Bus Approach With Wind Uncertainty

Mir

Karatepe

2022

IEEE Access

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“…This approach better mimics the operation of power systems provided that participation factors of generators are accurately determined. These participation factors can be appointed based on machine inertia [5], governor droop characteristics [6], [7], frequency control [8], and economic dispatch [9]- [11]. Another major aspect of post-contingency analysis is the determination of reactive power dispatch and voltage magnitudes [12].…”

Section: Introductionmentioning

confidence: 99%

Enhanced Modeling of Contingency Response in Security-constrained Optimal Power Flow

Altun¹,

Madani²,

Atamtürk³

et al. 2021

Preprint

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This paper provides an enhanced modeling of the contingency response that collectively reflects high-fidelity physical and operational characteristics of power grids. Integrating active and reactive power contingency responses into the securityconstrained optimal power flow (SCOPF) problem is challenging, due to the nonsmoothness and nonconvexity of feasible sets in consequence of piece-wise curves representing generator characteristics. We introduce a continuously-differentiable model using functions that closely resemble PV/PQ switching and the generator contingency response. These models enforce physical and operational limits by optimally allocating active power imbalances among available generators and deciding the bus type to switch from the PV type to the PQ type. The efficacy of this method is numerically validated on the IEEE 30-bus, 300bus, and 118-bus systems with 12, 10, and 100 contingencies, respectively.

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“…To be able to model the power system more realistically especially after a generation contingency, the governor power flow option is integrated into VCMARGIN. The governor power flow formulation uses a distributed slack scheme as described in [15,16]. It takes into account all the active power available by using the participation factors of the generators to account for the system losses, p. The new unknown variable, p, is added to the state vector, i.e., x = /QT,VT, plT, and the power flow Jacobian, I, in Eq.…”

Section: I "mentioning

confidence: 99%

Voltage Collapse Operating Margin Analysis Using Sensitivity Techniques

Rajagopalan¹,

Hao²,

Shirmohammadi³

et al.

Proceedings. Joint International Power Conference Athens Power Tech,

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In this paper, we describe the basic formulation, voltage collapse and plan operations under such implementation and application of a computer model, conditions, PG&E has developed a computer called VCMARGIN, for determining the s teady-state model called VCMARGIN (Voltage Collapse Operating operating margin of a potver system based on voltage Margin Calculation Program). stability considerations. The determination of the operating margin is based on the evaluation of the The steady-state voltage stability margin at an operating proximity of the current operating point of a power point of a power system is determined by measuring its system to the voltage collapse point. This proximity is distance from the critical point (nose point) on the calculated by tracing the path of the current operating voltage vs. activelreactive power (V-P/Q) curve. The point a s one or more system parameters vary.critical point is traditionally estimated by running Parameters under consideration include bus and area standard power flow programs repeatedly at various loads, line impedances and real/reactive generations. load levels. As the loading in the system increases, the VCMARGIN uses a continuation technique for power power flow Jacobian becomes numerically illflow, optimal power flow and governor power flow to conditioned and the solution diverges. As a result, the perform the determination of the operating margin very exact knowledge of the critical point through efficiently. VCMARGIN is extensively used by IJG&E's conventional power flow analysis is not always possible. operations planners for developing short-term operating plans for secure an mal use of PG&E's generation The rising interest in voltage collapse has focused and transmission attention on the behavior of power systems at critical load levels. Several authors on this subject have tried to Keywords: Steady-State Voltage Stability Analysis, explain the problem in terms of the singularity Voltage Collapse, Continuation Methods. phenomenon of the power flow Jacobian, multiple load flow solutions and the static bifurcation theory [2]-[10].

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Decoupled Economic Dispatch Using the Participation Factors Load Flow

Cited by 4 publications

References 0 publications

Stochastic AC Transmission Expansion Planning: A Chance Constrained Distributed Slack Bus Approach With Wind Uncertainty

Stochastic AC Transmission Expansion Planning: A Chance Constrained Distributed Slack Bus Approach With Wind Uncertainty

Enhanced Modeling of Contingency Response in Security-constrained Optimal Power Flow

Voltage Collapse Operating Margin Analysis Using Sensitivity Techniques

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