This paper analyzes the impact of natural gas supply, increased penetration of renewable energy sources and shifting demand trends due to tight financial conditions on generating unit maintenance scheduling. The main ...
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ISBN:
(纸本)9781467356688
This paper analyzes the impact of natural gas supply, increased penetration of renewable energy sources and shifting demand trends due to tight financial conditions on generating unit maintenance scheduling. The main focus is on the increased importance of enhancing unit availability in periods of concurrent peak electricity and natural gas demand and limited RES contribution, through proper adjustment of power system maintenance rules. In power systems with peak demand in summer and high photovoltaic penetration, this translates into enforcing unit availability during winter. A detailed mixedinteger linear programming model for the yearly maintenance scheduling of a System Operator is developed with GAMS/CPLEX in order to evaluate modifications in maintenance rules. The same model is used to assess the consequences of a short-term natural gas shortage contingency scenario, given the maintenance decisions of the yearly scheduling process. The method is applied to the Greek power system.
The EU research project DISCUS defines a future proof end-to-end network architecture for next-generation communication networks. One central decision is at which and at how many Local Exchange (LE) locations the acti...
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ISBN:
(纸本)9781479956029
The EU research project DISCUS defines a future proof end-to-end network architecture for next-generation communication networks. One central decision is at which and at how many Local Exchange (LE) locations the active equipment has to be placed. The key drivers here are threefold: as hard constraint, technical requirements must be satisfied, while as softer constraints, reliability and cost-efficiency should be as high as possible. In this paper we present an optimization study on a set of parameters that influence the number of selected locations for active equipment. In particular we compute the number of active nodes that is actually necessary to connect all customers. Moreover, for this study we compute a realistic reference network that contains the Local Exchange (LE) locations of Italy provided by TELECOM ITALIA.
Even in a static setting, the economic load dispatch problem (ELDP) - namely the cost-optimal distribution of power among generating units to meet a specific demand subject to system constraints - turns out to be a ch...
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Even in a static setting, the economic load dispatch problem (ELDP) - namely the cost-optimal distribution of power among generating units to meet a specific demand subject to system constraints - turns out to be a challenge owing to the consideration of valve-point effects (VPE), which make the cost function nonsmooth and nonconvex. We present a new method, termed Adaptive Piecewise-Quadratic Under-Approximation (APQUA), for the global solution of the ELDP with VPE. Unlike the many existing methods for this problem, APQUA produces at each iteration an upper and a lower bound on the globally optimal cost, and the gap between the two bounds is guaranteed to converge to zero as the iteration number grows. Consequently, APQUA is guaranteed to compute the global optimum of the ELDP within any user-prescribed accuracy. Even though APQUA has to call an MIQP solver on increasingly large surrogate problems in order to achieve this unprecedented optimality guarantee, our experiments indicate that the total computation time remains reasonable even when the prescribed accuracy is very high.
A mixed-integer nonlinear programming model is proposed in this paper for reducing excessive standing phase angle difference (SPA) across open circuit breakers in transmission loop paralleling operation. The model ado...
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ISBN:
(纸本)9781479932559
A mixed-integer nonlinear programming model is proposed in this paper for reducing excessive standing phase angle difference (SPA) across open circuit breakers in transmission loop paralleling operation. The model adopts both the active power generation increment and the load switch as control variables and takes the relative importance of the loads to be restored into account, resulting in fewer rescheduled generators and less adjustment of active power generation. The condition for transmission loop paralleling operation can be reached from two ways of reducing generator adjustment time and optimally restoring load. The method can improve power restoration efficiency, speed up restoration progress, and hence reduce the loss of outage. Simulation results of New England 10-machine 39-bus test system demonstrate the effectiveness of the method.
This article presents an agent-based simulation-optimization modeling and algorithmic framework to determine the optimal vaccine center location and vaccine allocation strategies under budget constraints during an epi...
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This article presents an agent-based simulation-optimization modeling and algorithmic framework to determine the optimal vaccine center location and vaccine allocation strategies under budget constraints during an epidemic outbreak. Both simulation and optimization models incorporate population health dynamics, such as susceptible (S), vaccinated (V), infected (I) and recovered (R), while their integrated utilization focuses on the COVID-19 vaccine allocation challenges. We first formulate a dynamic location–allocation mixed-integer programming (MIP) model, which determines the optimal vaccination center locations and vaccines allocated to vaccination centers, pharmacies, and health centers in a multi-period setting in each region over a geographical location. We then extend the agent-based epidemiological simulation model of COVID-19 (Covasim) by adding new vaccination compartments representing people who take the first vaccine shot and the first two shots. The Covasim involves complex disease transmission contact networks, including households, schools, and workplaces, and demographics, such as age-based disease transmission parameters. We combine the extended Covasim with the vaccination center location-allocation MIP model into one single simulation-optimization framework, which works iteratively forward and backward in time to determine the optimal vaccine allocation under varying disease dynamics. The agent-based simulation captures the inherent uncertainty in disease progression and forecasts the refined number of susceptible individuals and infections for the current time period to be used as an input into the optimization. We calibrate, validate, and test our simulation-optimization vaccine allocation model using the COVID-19 data and vaccine distribution case study in New Jersey. The resulting insights support ongoing mass vaccination efforts to mitigate the impact of the pandemic on public health, while the simulation-optimization algorithmic framework co
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