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Spinning reserve (SR) allocation problem is of vital importance in maintaining power systems security and reliability. Considering forecast uncertainties, unit commitment problem and contingencies on the failure of transmission lines, a general probabilistic model for expected total cost is established and its corresponding solution for optimal SR allocation strategy is proposed. The objective function...
This paper investigates the scheduling horizon of power system containing wind and concentrating solar power (CSP) plants with thermal energy storage (TES). CSP plant with TES can be used to reduce the uncertainty of renewable generation and provide services to power system. However, forecast error of wind/solar is strongly related to the forecast horizon. When CSP plant with TES is incorporated into...
This paper proposes a novel two-stage stochastic optimization model that incorporates effect of dynamic line rating (DLR) on transmission network operation with increased penetration of wind generation, explicitly considering uncertainty in both wind generation and line rating. The stochastic model co-optimizes energy and reserve holding levels for the forecasted/expected condition (that with zero...
High penetrations of distributed renewables can dramatically increase uncertainty in the transmission system, making small-signal stability verification far more challenging. In this paper, we examine the impact of generating 30% of the power in the IEEE 118 bus test network with 118 distributed renewable sources, and show the inadequacy of sampling approaches to stability analysis. We show that multipoint...
This paper presents a new dynamic and stochastic decision supporting model for distributed generation investment planning (DGIP). The model is formulated as a mixed integer linear programming (MILP) optimization problem that simultaneously minimizes emission, operation and maintenance, as well as reliability costs. One of the salient features of the model is that it is based on a two-period planning...
This paper proposes a Stochastic Mixed-Integer Linear Programming (SMILP) formulation for Short-Term Hydrothermal Generation Scheduling (STHTGS) under uncertainty. STHTGS seeks to minimize present and future operation costs by deciding the commitments of thermal generators and the allocation of hydro resources during the planning horizon. The stochastic STHTGS is decomposed using the Progressive Hedging...
With higher shares of fluctuating electricity generation from renewables, new operational planning methods to handle uncertainty from forecast errors and short-term fluctuations are required. In this paper, we formulate a probabilistic AC optimal power flow where the uncertainties are accounted for using chance constraints on line currents and voltage magnitudes. The chance constraints ensure that...
Wind generation is traditionally treated as a non-dispatchable resource and is fully absorbed unless there are security issues. To tackle the operational reliability issues caused by the volatile and non-dispatchable wind generation, many dispatch frameworks have been proposed, including robust unit commitment (RUC) considering wind variation. One of the drawbacks that commonly exist in those dispatch...
This paper solves an optimal power flow problem to minimize the emission due to carbon oxides, nitrogen oxides and sulfur oxides with cost as a constraint for a wind-thermal power system. Wind energy can reach significant penetration in modern power system and the wind power will introduce additional uncertainties. Market price is mainly influenced by the generating fuel cost, as the wind power being...
Climate change can easily affect renewable energy power output, and the uncertainty of renewable generation may cause serious influence on the power grid. This paper proposes a novel optimal generation dispatch algorithm to compensate for the fluctuations in power outputs of renewable energy resources. The proposed method helps reduce bus voltage variation and improves the ability of the power system...
This paper describes a framework of incorporating smart sampling techniques in a probabilistic look-ahead contingency analysis application. The predictive probabilistic contingency analysis helps describe the impact of uncertainties caused by variable generation and load on potential violations of transmission limits. The objectives of smart sampling techniques are to represent structure and statistical...
This paper is concerned with computer control systems. In particular, we consider stability of quasi-periodic linear impulsive systems which can be used to model sampled-data systems and networked control systems. In this paper, we introduce a class of sets complex zonotopes and use them to verify global exponential stability by deriving a sufficient condition for their contraction. Their advantage...
Recently we developed supervisor localization, a top-down approach to distributed control of discrete-event systems. Its essence is the allocation of monolithic (global) control action among the local control strategies of individual agents. In this paper, we extend supervisor localization by considering partial observation; namely not all events are observable. Specifically, we employ the recently...
Aimed at the characteristics of nonlinear, strong coupling, multi-variable and natural unstable for inverted pendulum, based on information fusion technology, the state feedback gain matrix with quadratic optimal performance index is adopted as fusion function to reduce dimension of the outputs vector for double inverted pendulum, and decrease the difficulty of controller design. On this basis, a...
This paper introduces event-based control as a means to improve the behaviour of feedback loops with switching controllers. It investigates hybrid event-based control systems where the event-based part of the controller affects a continuous control loop. Its task is to adjust the operating point of this control loop to changing operation modes of the overall system. The paper introduces a control...
The uptake of high penetrations of renewable energy in microgrids is curtailed by concerns that their intermittency may cause the system to become unstable. The classic approach of small-signal stability analysis may lead to overly optimistic conclusions, because it implicitly assumes that the intermittency is small-signal in nature. Instead, LMI techniques from robust controls can be used to provide...
Levels of electricity access in sub-Saharan Africa are low with large populations living far from existing electricity infrastructure. This has led to interest in decentralized electrification solutions like microgrids, which can reach remote communities more quickly. To address a lack of capital to deploy these projects, governments have sought private investment in the sector. Studies have found...
The increase in renewable energy generators introduced into the electricity grid is putting pressure on its stability and management as predictions of renewable energy sources cannot be accurate or fully controlled. This, with the additional pressure of fluctuations in demand, presents a problem more complex than the current methods of controlling electricity distribution were designed for. A global...
This paper solves an optimization problem to minimize the emission due to carbon oxides, nitrogen oxides and sulfur oxides with cost as a constraint for a wind-solar-thermal power system. Wind and solar energy can reach significant penetration in modern power system and they will introduce additional uncertainties. Market price is mainly influenced by the generating fuel cost, as the wind and solar...
Supervisor localization procedure can be used to construct the local controllers relevant to each component agent in a discrete-event system. This procedure is based on state reduction of monolithic supervisor with respect to each set of controllable events corresponding to each component agent. In this paper, observation and coobservation properties which preserve through supervisor reduction and...
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