DC Optimal Power Flow Research Articles

Determining Optimal Buses for Implementing Demand Response as an Effective Congestion Management Method

Demand response (DR) can be counted as an effective congestion management method in power systems. However, appointing the optimal buses for the demand response programs (DRPs) implementation is one of the main challenges for the power system operators. In this paper, a new procedure has been developed by which the optimal locations and times of DRPs implementation are determined. Optimal buses are identified based on the power transfer distribution factors (PTDFs), available transfer capability, and dynamic dc optimal power flow problem. Applying the developed method results in reducing lines' congestion, increasing customers, and independent system operator's benefits, improving load curve's characteristics, preventing line outages and black outs, and consequently increasing the network reliability. The proposed method has been applied on the IEEE 39-bus New England test system. Results indicate the effectiveness and practical benefits of the proposed method.

Optimizing Storage Siting, Sizing, and Technology Portfolios in Transmission-Constrained Networks

In this paper, we propose a DC optimal power flow (OPF) framework for storage portfolio optimization in transmission-constrained power networks. In particular, this model is designed to investigate two problems: 1) optimizing storage operation and allocation over a network given a fixed technology portfolio and 2) optimizing the storage portfolio (i.e., the size, technology, and network allocation of these resources). We demonstrate this framework using case studies based on the IEEE 14-bus test system with four different storage technologies. Our results show that although certain technologies are generally classified as being suitable for either power or energy services, many technologies can add value to the system by performing both fast-time scale regulation (power) and load-shifting (energy) services. These results suggest that limiting the type of service that a certain technology is compensated for may result in inefficiencies at the system level and under-valuation of storage.

Day-Ahead Corrective Adjustment of FACTS Reactance: A Linear Programming Approach

Reserve requirements serve as a proxy for N-1 reliability in the security-constrained unit commitment (SCUC) problem. However, there is no guarantee that the reserve is deliverable for all scenarios (post-contingency states). One cheap way to improve reserve deliverability is to harness the flexibility of the transmission network. Flexible AC transmission system (FACTS) devices are able to significantly improve the transfer capability. However, FACTS utilization is limited today due to the complexities these devices introduce to the DC optimal power flow problem (DCOPF). With a linear objective, the traditional DCOPF is a linear program (LP); when variable impedance based FACTS devices are taken into consideration, the problem becomes a nonlinear program (NLP). A reformulation of the NLP to a mixed integer linear program, for day-ahead corrective operation of FACTS devices, is presented in this paper. Engineering insight is then introduced to further reduce the complexity to an LP. Although optimality is not guaranteed, the simulation studies on the IEEE 118-bus system show that the method finds the globally optimal solution in 98.8% of the cases. Even when the method did not find the optimal solution, it was able to converge to a near-optimal solution, which substantially improved the reliability, very quickly.

A Fast LP Approach for Enhanced Utilization of Variable Impedance Based FACTS Devices

Transmission systems are under stress and need to be upgraded. Better utilization of the existing grid provides a fast and cheap alternative to building new transmission. One way to improve the utilization of the transmission network is power flow control via flexible ac transmission system (FACTS) devices. While FACTS devices are used today, the utilization of these devices is limited; traditional dispatch models (e.g., security constrained economic dispatch) assume a fixed, static transmission grid even though it is rather flexible. The primary barrier is the complexity that is added to the power flow problem. The mathematical representation of the DC optimal power flow, with the added modeling of FACTS devices, is a nonlinear program (NLP). This paper presents a method to convert this NLP into a mixed-integer linear program (MILP). The MILP is reformulated as a two-stage linear program, which enforces the same sign for the voltage angle differences for the lines equipped with FACTS. While this approximation does not guarantee optimality, more than 98% of the presented empirical results, based on the IEEE 118-bus and Polish systems, achieved global optimality. In the case of suboptimal solutions, the savings were still significant and the solution time was dramatically reduced.

AC Optimal Power Flow Calculation for Locational Marginal Pricing

This is the case of the ACOPF form, the blocking element of the Locational marginal price vector exhibit strong addiction on the power reference. In instruct to resolution this clash, a direct optimization outline is developed in this work this method is verified through an IEEE 30–bus scheme. Method: The power word simulator is used as a tool and in this an optimization technique is used to solve the both dc and AC optimal power flow. Findings: The marginal price details of each bus and linear programming solution is determined by comparing both AC and DC power flows. Applications: A power world simulator is used and for future scope a genetic algorithm, quadratic programming method can also be used.

Flexible implementation of power system corrective topology control

This paper proposes a novel decision making framework for optimal transmission switching satisfying the AC feasibility, stability and circuit breaker (CB) reliability requirements needed for practical implementation. The proposed framework can be employed as a corrective tool in day to day operation planning scenarios in response to potential contingencies. The switching options are determined using an efficient heuristic algorithm based on DC optimal power flow, and are presented in a multi-branch tree structure. Then, the AC feasibility and stability checks are conducted and the CB condition monitoring data are employed to perform a CB reliability and line availability assessment. Ultimately, the operator will be offered multiple AC feasible and stable switching options with associated benefits. The operator can use this information, other operating conditions not explicitly considered in the optimization, and his/her own experience to implement the best and most reliable switching action(s). The effectiveness of the proposed approach is validated on the IEEE-118 bus test system.

Distributed Stochastic Market Clearing With High-Penetration Wind Power

Integrating renewable energy into the modern power grid requires risk-cognizant dispatch of resources to account for the stochastic availability of renewables. Toward this goal, day-ahead stochastic market clearing with high-penetration wind energy is pursued in this paper based on the DC optimal power flow (OPF). The objective is to minimize the social cost which consists of conventional generation costs, end-user disutility, as well as a risk measure of the system re-dispatching cost. Capitalizing on the conditional value-at-risk (CVaR), the novel model is able to mitigate the potentially high risk of the recourse actions to compensate wind forecast errors. The resulting convex optimization task is tackled via a distribution-free sample average based approximation to bypass the prohibitively complex high-dimensional integration. Furthermore, to cope with possibly large-scale dispatchable loads, a fast distributed solver is developed with guaranteed convergence using the alternating direction method of multipliers (ADMM). Numerical results tested on a modified benchmark system are reported to corroborate the merits of the novel framework and proposed approaches.

Forecasting of Utility Cost in a Deregulated Electricity Market by Using Locational Marginal Pricing

In the deregulated electricity market bidding contest is the major operation. Prices obtained from the result of bidding strategy is essential, since all market participants do not be familiar with the accurate assessment of future prices in their decision-making process. Locational Marginal Pricing obtains from the Optimal Power Flow problem gives the economic value of electrical energy at each location. Proposed method is based on lossless DC Optimal Power Flow. To solve this LMP problem optimization based Linear Programming (LP) approach has been implemented. In this paper LMP values with transmission, line outage and generator outage constraints are studied. DOI: http://dx.doi.org/10.11591/telkomnika.v14i1.7713

A Study on the Application of DC HTS cable systems to enhance power transfer limits of a grid-connected offshore wind farm

This paper introduces two on-going projects for DC high temperature superconducting (HTS) cable systems in South Korea. This study proposes the application of DC HTS cable systems to enhance power transfer limits of a grid-connected offshore wind farm. In order to develop the superconducting DC transmission system model based on HTS power cables, the maximum transfer limits from offshore wind farm are estimated and the system marginal price (SMP) calculated through a Two-Step Power Transfer (TSPT) model based on PV analysis and DC-optimal power flow. The proposed TSPT model will be applied to 2022 KEPCO systems with offshore wind farms.

Stochastic optimal power flow incorporating offshore wind farm and electric vehicles

Abstract In this paper, an optimal power flow model of a power system, which includes an offshore wind farm and plug-in electric vehicles (PEVs) connected to grid, is presented. The stochastic nature of wind power and the uncertainties in the EV owner’s behavior are suitably modelled by statistical models available in recent literatures. The offshore wind farms are assumed to be composed of doubly fed induction generators (DFIGs) having reactive power control capability and are connected to offshore grid by HVDC link. In order to obtain the optimal active power schedules of different energy sources, an optimization problem is solved by applying recently introduced Gbest guided artificial bee colony algorithm (GABC). The accuracy of proposed approach has been tested by implementing AC–DC optimal power flow on modified IEEE 5-bus, IEEE 9-bus, and IEEE 39-bus systems. The results obtained by GABC algorithm are compared with the results available in literatures. This paper also includes AC–DC optimal power flow model, implemented on modified IEEE-30 bus test system by including wind farm power and V2G source. It has been shown that the uncertainty associated with availability of power from wind farm and PEVs affects the overall cost of operation of system.

Multi-objective transmission expansion planning considering minimization of curtailed wind energy

Abstract This paper proposes a new multi-objective transmission expansion planning (TEP) in order to find optimum location of lines/transformers by considering intermittent nature of wind power and variable load structure. To reveal the benefit of wind power in the context of TEP, curtailed wind energy is considered as one of the objective functions besides the sum of the investment costs and penalty for energy not supplied (ENS). By this way, a trade-off between investment cost and curtailed wind energy is established using fuzzy satisfying approach while maintaining the adequacy of power system. The multi-objective nature of the proposed method is handled by using the Non-dominated Sorting Genetic Algorithm-II combined with the DC-optimal power flow which is performed several times to obtain curtailed wind energy and ENS. The nature of load and wind power is incorporated into the methodology by using agglomerative hierarchical clustering to reduce computational effort. The proposed methodology is illustrated on the different configurations of modified IEEE-RTS 24 bus test system. Numerical case studies indicate the effectiveness of the proposed method for reduction of total investment cost in TEP of power systems with wind power integration.

Interdiction Analysis of Electric Grids Combining Cascading Outage and Medium-Term Impacts

This paper presents an improved interdiction model to identify maximal electric grid attacks. The contribution of the model is that it incorporates both short-term (seconds to minutes) and medium-term (minutes to days) impacts of the possible attack. The medium-term impacts are examined by an interdicted dc optimal power flow model. The short-term impacts are addressed by a cascading outage analysis model that uses a set of sequentially applied checkers to perform the simulation of the cascading outage events and assess the short-term impacts of a blackout subsequent to specified terrorist attacks. An integer programming heuristic is applied that can utilize standard optimization software (e.g. CPLEX) to solve master problems generated by the heuristic. The proposed model has been verified using the IEEE 300-Bus Test System and IEEE RTS 96 Test System. Discussions of the results and future research plans are also presented in this paper.

Transmission management for congested power system: A review of concepts, technical challenges and development of a new methodology

Transmission networks have some constraints that should be addressed in order to ensure sufficient control to maintain the security level of a power system while maximising market efficiency. The most obvious drawback of transmission constraints is a congestion problem that becomes an obstacle to perfect competition among the market participants since it can influence spot market pricing. As the power flow violates transmission constraints, redispatching generating units is required and this will cause the price at every node to vary. This manuscript presents concepts, technical challenges and methodology for investigating an alternative solution to the redispatch mechanism and then formulates LMP scheme using an optimisation technique that may well control congestion as the main issue. The LMP scheme are varied and improved to take into account the energy price, congestion revenue, cost of losses, as well as the transmission usage tariff by utilising shift factor-based optimal power flow (SF-OPF), which is derived from the well-known DC optimal power flow (DC-OPF) model.

Closure to Discussion on “Distribution Locational Marginal Pricing for Optimal Electric Vehicle Charging Management”

AC optimal power flow (ACOPF) is typically used for operational dispatch decisions. However, DC optimal power flow (DCOPF) based on linearization of the ACOPF is widely used for locational marginal price (LMP) calculation in market operation and settlements due to its efficiency and reasonable accuracy. The DCOPF is considered to be sufficient in many cases. Especially for calculating LMPs of distribution systems, the DCOPF is a good option considering the large number of nodes in distribution systems. In industry, DCOPF has been employed by several software tools for chronological LMP simulation and forecasting.

Optimal spot pricing in electricity market with inelastic load using constrained bat algorithm

In restructured electricity markets, an effective transmission pricing is required to address transmission issues and to generate correct economic signals. These prices depend on generator bids, load levels and transmission network constraints. A congestion charge is incurred when the system is constrained due to physical limitations. Spot pricing or Locational Marginal Pricing (LMP) or Nodal pricing is a popular method in restructured power markets to address these issues. This paper presents a DC optimal power flow (DCOPF) based spot pricing approach in single auction model with fuel cost minimization as objective function. This is solved with a heuristic technique called Bat algorithm and the results are compared with Linear Programming (LP) and Genetic algorithm (GA) approaches in a constrained pool based restructured electricity market. The developed models have been tested on IEEE 14 bus system, New England 39 bus system and 75 bus Indian practical power system. Different cases such as without loss, concentrated loss and distributed loss are considered for this problem. Two types of generator bids i.e., fixed bids and linear bids are considered for generators. Load is assumed to be inelastic. Generator profit, ISO profit and Social surplus during congestion have been computed in all the cases. In most of the cases studied, Bat algorithm is proven to be better than LP and GA algorithms for fuel cost minimization and social welfare (Social surplus) improvement.

A linearized formulation of AC multi-year transmission expansion planning: A mixed-integer linear programming approach

This paper presents a method in expansion planning of transmission systems using the AC optimal power flow (AC-OPF). The AC-OPF provides a more accurate picture of power flow in the network compared to the DC optimal power flow (DC-OPF) that is usually considered in the literature for transmission expansion planning (TEP). While the AC-OPF-based TEP is a mixed-integer nonlinear programming problem, this paper transforms it into a mixed-integer linear programming environment. This transformation guarantees achievement of a global optimal solution by the existing algorithms and software. The proposed model has been successfully applied to a simple 3-bus power system, Garver's 6-bus test system, 24-bus IEEE reliability test system (RTS) as well as a realistic power system. Detailed case studies are presented and thoroughly analyzed. Simulations show the effectiveness of the proposed method on the TEP.

Reduction of PTDF matrix and its application in DC optimal power flow

SUMMARY The paper presents an approach where traditional Power Transfer Distribution Factors (PTDF) matrix is reduced in size so that it reflects sensitivities of branch flows to changes in nodal power injections at generator buses only. The advantage of the reduced PTDF matrix is in both reductions of decision variables in the optimization procedure and number of columns in branch flow constraints matrix. Furthermore, the number of rows is also reduced on the basis of a simple check, which effectively detects non-binding branch flow limits allowing corresponding rows of the matrix to be omitted. The reduced PTDF matrix was successfully applied in solving two direct current optimal power flow problems: cost minimization and total transfer capacity calculation. Copyright © 2014 John Wiley & Sons, Ltd.

Design of Pareto optimal [formula omitted] cap-and-trade policies for deregulated electricity networks

Among the CO2 emission reduction programs, cap-and-trade (C&T) is one of the most used policies. Economic studies have shown that C&T policies for electricity networks, while reducing emissions, will likely increase price and decrease consumption of electricity. This paper presents a two layer mathematical–statistical model to develop Pareto optimal designs for CO2 cap-and-trade policies. The bottom layer finds, for a given C&T policy, equilibrium bidding strategies of the competing generators while maximizing social welfare via a DC optimal power flow (DC-OPF) model. We refer to this layer as policy evaluation. The top layer (called policy optimization) involves design of Pareto optimal C&T policies over a planning horizon. The performance measures that are considered for the purpose of design are social welfare and the corresponding system marginal price (MP), CO2 emissions, and electricity consumption level.

The Impact of Active Power Losses on the Wind Energy Exploitation of the North Sea

Transmission active power losses can influence the distribution of power flows in the transmission grid which consequently alter the generation dispatch and scheduling through the power system. This can especially affect the exploitation of large scale renewable energy sources (RES) since they are normally installed far away from load centres. RES technologies are expected to cover a large portion of the future energy mix in the continental European power system and grid bottlenecks are a critical factor for successful integration of RES technologies in Europe. In this respect, transmission losses can significantly affect the potential grid bottlenecks and the exploitation of the expected energy produced by RES.In this paper a comparison analysis is carried out on approaches to include active power losses in a DC optimal power flow. The initial idea is to apply a method to the existing flow-based market model Power System Simulation Tool (PSST), a tool for studying the effect of high penetration of wind power and consequent grid expansion in the European power system. Implementation of losses in large scale power systems significantly increases the computational burden. A solution to reduce computational time is to calculate reasonably good approximations of the active power losses. This paper proposes an approach to include transmission active power losses that can be implemented in large scale power system in reasonable computational time.

Reliability assessment of incentive- and priced-based demand response programs in restructured power systems

Fostering demand response (DR) through incentive-based and priced-based programs has always great impact on improvement of efficiency and reliability of the power systems. The use of DR lowers undesirable effects of failures that usually impose financial costs and inconveniences to the customers. Hence, quantifying the impact of demand response programs (DRPs) on reliability improvement of the restructured power systems is an important challenge for the independent system operators and the regional transmission organizations.In this paper, the DR model which treats consistently the main characteristics of the demand curve is developed for modeling. In proposed model, some penalties for customers in case of no responding to load reduction and incentives for customers who respond to reducing their loads are considered.In order to make analytical evaluation of the reliability, a mixed integer DC optimal power flow is proposed by which load curtailments and generation re-dispatches for each contingency state are determined. Both transmission and generation failures are considered in contingency enumeration. The proposed technique is modeled in the GAMS software and solved using CPLEX as a powerful mixed integer linear programming (MILP) solver. Both supply-side reliability for generation companies and demand-side reliability for customers are calculated using this technique.In order to simulate customers’ behavior to different DRPs in a real power network, the proposed DR model is used and evaluated over Iranian power network. In order to investigate the reliability effects of DRPs based on proposed reliability method, DRPs based on the DR model are implemented over the IEEE RTS 24-bus test system, and reliability indices for generation companies, transmission network and customers are calculated. Using proposed performance index, the priority of the DRPs are determined from view point of customers, generation companies, transmission network and the whole system in IEEE RTS.