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This paper proposes a new hybrid particle swarm optimization with gravitational search algorithm to solve the economic/environment optimal power flow dispatching incorporating wind power generations into the isolated Adrar Algerian power system. Taking into account the intermittent of the wind speed, the maximum probable active wind power generation is estimated by computing the wind speed carried...
A pessimistic three-level equilibrium model for a market-based expansion of both transmission and generation is proposed. The lower (third) level models the market outcome; the intermediate (second) level models the equilibrium in generation capacity expansion by taking into account the outcomes of the market equilibrium at the third level. The upper (first) level models the expansion of the transmission...
The paper shows that the manifestation of Hamilton principle in electric power system is tending of its states to self-optimization. Characteristic feature of these states is minimum dissipation of electric energy during its transmission. The possibility and expedience of this principle usage for optimal control of normal modes of electric power system is shown.
Leveraging of flexibility in certain types of electric loads such as water heaters, washers, dryers, heating and air conditioning, and electric vehicles, offers an attractive and promising approach for large scale penetration of renewable generation and peak demand reduction. In price/market based approaches, consumers of flexible loads optimize their consumption schedules to meet their energy/power...
The paper analyzes the optimal response of an individual consumer, with a deferrable demand for electricity, to exogenous stochastic prices. The main goal of the paper is (i) to introduce a model where many realistic features are taken into account (such as the presence of bounds on power consumption, the possibility of curtailment, and time correlation in the price process) (ii) determine an explicit...
A dynamic decision model for microgrids optimal control having as objective function the minimization of the operating costs is proposed and mathematically formalized in this paper. The model is part of an overall decision support system that optimizes microgrids planning and management at different temporal scales, namely long term planning, day ahead and intra-day. Here, the model formalization...
In this research, we present a discrete version of cat swarm optimization that is used to build an optimization model based on support vector machines (SVM). This model is undertaken to select the best transformer tests that can be utilized to classify transformer health index into three categories; thus, improving the reliability of identifying the transformer condition within the power system. The...
This paper is motivated by the open questions concerning effective nonlinear state estimation (SE) approaches. The basic difficulty comes from the highly nonlinear functions relating measurements and voltages defined by the AC power flow models. Today's AC power flow SE approach is, therefore, a highly non-convex problem and, as such, it is prone to convergence problems and sub-optimal solutions....
The major concern of the power system utilities is to not only deliver high quality power supply to the end users but to do it with minimum possible fuel cost and emission levels. Combined Economic Emission Dispatch (CEED) is a way to compute the optimal generation of the power system by minimizing the fuel cost and emission levels simultaneously. The CEED is a multi objective problem and in general...
We present a novel selection algorithm for N-2 contingency analysis problem. The algorithm is based on the iterative bounding of line outage distribution factors and successive pruning of the set of contingency pair candidates. The selection procedure is non-heuristic, and is certified to identify all events that lead to thermal constraints violations in DC approximation. The complexity of the algorithm...
This paper is concerned with zonal pricing as an approach to congestion management. The main contributions of the paper are summarized as follows. Algebraic characterization of optimal zonal prices is presented, where physical tie-line limits are explicitly accounted for without introducing conservatism. In a case of affine bids, it is shown that the optimal zonal price in a zone can be represented...
The United States Marine Corps (USMC) utilizes Forward Operating Bases (FOBs) which employ multiple generation units, primarily powered by JP-8 (similar to diesel fuel). It is often true that logistical support to deliver fuel is both expensive and dangerous. On the other hand, the generation units deployed by USMC range from 2 KW to over 200 KW, with very different input-output characteristics. In...
The objective of the economic dispatch problem of electrical power generation is to schedule the committed generating unit's output so as to meet the required load demand while satisfying the system equality and inequality constraints. This paper solves the combined economic emission dispatch problem by using Min-Max and Max-Max price penalty factor approaches using Lagrange's method. The price penalty...
There have been numerous attempts to use graph-theoretic algorithms in power systems. But it has not been clear enough what the potentials and the limitations of these applications are. The goal of our work is to model differences between transportation and electrical networks and to provide a uniform way for transforming an electrical network into its transportation equivalent. The limitations of...
It is widely agreed that Demand Response (DR), in the form of load curtailments in power systems, not only improve the system reliability but also the market efficiency through the mitigation of spot price volatility. This panel paper introduces a novel agent-based market-clearing scheme for fairly distributing the benefits of such DRs on various categories of market participants (as agents). The...
This paper proposes an optimal power flow (OPF) algorithm based on quadratic modeling and incremental loading of the network. The proposed OPF algorithm is robust and highly efficient for large-scale power systems. Robustness is achieved by the design of the algorithm to operate on infeasible but optimal points and move towards the feasible and optimal operating point. Efficiency is achieved by (a)...
One of the important tasks of system operators in electricity network is Unit commitment. Considering development of electricity market restructuring in generation side, the Generating and Transition costs will be decreased in a high scale by right committing of this operation. This paper proposes to represent compromise improved TS and enhanced PSO in the sense of accuracy and speed of solution....
When ensuring electric power system to supply power safely and reliably, economic and social benefit are very good which hydropower station economic operation brought. But selecting the optimal combination model of unit is a high-dimension, discrete, non-convex and non-linear optimization problem, so it is very difficult to obtain optimal solution from theory. According to similarity between hydropower...
An adaptive particle swarm optimization(APSO) algorithm is presented to solve the problem that the standard particle swarm optimization(PSO) algorithm is easy to fall into a locally optimized point, where inertia weight is nonlinearly adjusted by using population diversity information. Velocity mutation factor and position interchange factor are both introduced. The APSO algorithm thus improves its...
Continuing trend towards deregulation and unbundling of transmission services has resulted in the need to measure the flow of power primarily for pricing and tariff purposes. Tracing methodology hence had been introduced to overcome problems related to the Marginal pricing of transmission costs. This study is twofold: the first revolves around the validation of the method and a 360° analysis of the...
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