3,199 research outputs found
Quasi-dynamic Load and Battery Sizing and Scheduling for Stand-Alone Solar System Using Mixed-integer Linear Programming
Considering the intermittency of renewable energy systems, a sizing and
scheduling model is proposed for a finite number of static electric loads. The
model objective is to maximize solar energy utilization with and without
storage. For the application of optimal load size selection, the energy
production of a solar photovoltaic is assumed to be consumed by a finite number
of discrete loads in an off-grid system using mixed-integer linear programming.
Additional constraints are battery charge and discharge limitations and minimum
uptime and downtime for each unit. For a certain solar power profile the model
outputs optimal unit size as well as the optimal scheduling for both units and
battery charge and discharge (if applicable). The impact of different solar
power profiles and minimum up and down time constraints on the optimal unit and
battery sizes are studied. The battery size required to achieve full solar
energy utilization decreases with the number of units and with increased
flexibility of the units (shorter on and off-time). A novel formulation is
introduced to model quasi-dynamic units that gradually start and stop and the
quasi-dynamic units increase solar energy utilization. The model can also be
applied to search for the optimal number of units for a given cost function.Comment: 6 pages, 3 figures, accepted at The IEEE Conference on Control
Applications (CCA
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Corrective receding horizon EV charge scheduling using short-term solar forecasting
Forecast errors can cause sub-optimal solutions in resource planning optimization, yet they are usually modeled simplistically by statistical models, causing unrealistic impacts on the optimal solutions. In this paper, realistic forecast errors are prescribed, and a corrective approach is proposed to mitigate the negative effects of day-ahead persistence forecast error by short-term forecasts from a state-of-the-art sky imager system. These forecasts preserve the spatiotemporal dependence structure of forecast errors avoiding statistical approximations. The performance of the proposed algorithm is tested on a receding horizon quadratic program developed for valley filling the midday net load depression through electric vehicle charging. Throughout one month of simulations the ability to flatten net load is assessed under practical forecast accuracy levels achievable from persistence, sky imager and perfect forecasts. Compared to using day-ahead persistence solar forecasts, the proposed corrective approach using sky imager forecasts delivers a 25% reduction in the standard deviation of the daily net load. It is demonstrated that correcting day-ahead forecasts in real time with more accurate short-term forecasts benefits the valley filling solution
Modeling and Real-Time Scheduling of DC Platform Supply Vessel for Fuel Efficient Operation
DC marine architecture integrated with variable speed diesel generators (DGs)
has garnered the attention of the researchers primarily because of its ability
to deliver fuel efficient operation. This paper aims in modeling and to
autonomously perform real-time load scheduling of dc platform supply vessel
(PSV) with an objective to minimize specific fuel oil consumption (SFOC) for
better fuel efficiency. Focus has been on the modeling of various components
and control routines, which are envisaged to be an integral part of dc PSVs.
Integration with photovoltaic-based energy storage system (ESS) has been
considered as an option to cater for the short time load transients. In this
context, this paper proposes a real-time transient simulation scheme, which
comprises of optimized generation scheduling of generators and ESS using dc
optimal power flow algorithm. This framework considers real dynamics of dc PSV
during various marine operations with possible contingency scenarios, such as
outage of generation systems, abrupt load changes, and unavailability of ESS.
The proposed modeling and control routines with real-time transient simulation
scheme have been validated utilizing the real-time marine simulation platform.
The results indicate that the coordinated treatment of renewable based ESS with
DGs operating with optimized speed yields better fuel savings. This has been
observed in improved SFOC operating trajectory for critical marine missions.
Furthermore, SFOC minimization at multiple suboptimal points with its treatment
in the real-time marine system is also highlighted
Reliability of Dynamic Load Scheduling with Solar Forecast Scenarios
This paper presents and evaluates the performance of an optimal scheduling
algorithm that selects the on/off combinations and timing of a finite set of
dynamic electric loads on the basis of short term predictions of the power
delivery from a photovoltaic source. In the algorithm for optimal scheduling,
each load is modeled with a dynamic power profile that may be different for on
and off switching. Optimal scheduling is achieved by the evaluation of a
user-specified criterion function with possible power constraints. The
scheduling algorithm exploits the use of a moving finite time horizon and the
resulting finite number of scheduling combinations to achieve real-time
computation of the optimal timing and switching of loads. The moving time
horizon in the proposed optimal scheduling algorithm provides an opportunity to
use short term (time moving) predictions of solar power based on advection of
clouds detected in sky images. Advection, persistence, and perfect forecast
scenarios are used as input to the load scheduling algorithm to elucidate the
effect of forecast errors on mis-scheduling. The advection forecast creates
less events where the load demand is greater than the available solar energy,
as compared to persistence. Increasing the decision horizon leads to increasing
error and decreased efficiency of the system, measured as the amount of power
consumed by the aggregate loads normalized by total solar power. For a
standalone system with a real forecast, energy reserves are necessary to
provide the excess energy required by mis-scheduled loads. A method for battery
sizing is proposed for future work.Comment: 6 pager, 4 figures, Syscon 201
Optimal Home Energy Management System for Committed Power Exchange Considering Renewable Generations
This thesis addresses the complexity of SH operation and local renewable resources optimum sizing. The effect of different criteria and components of SH on the size of renewable resources and cost of electricity is investigated. Operation of SH with the optimum size of renewable resources is evaluated to study SH annual cost. The effectiveness of SH with committed exchange power functionality is studied for minimizing cost while responding to DR programs
Demand and Storage Management in a Prosumer Nanogrid Based on Energy Forecasting
Energy efficiency and consumers' role in the energy system are among the strategic research topics in power systems these days. Smart grids (SG) and, specifically, microgrids, are key tools for these purposes. This paper presents a three-stage strategy for energy management in a prosumer nanogrid. Firstly, energy monitoring is performed and time-space compression is applied as a tool for forecasting energy resources and power quality (PQ) indices; secondly, demand is managed, taking advantage of smart appliances (SA) to reduce the electricity bill; finally, energy storage systems (ESS) are also managed to better match the forecasted generation of each prosumer. Results show how these strategies can be coordinated to contribute to energy management in the prosumer nanogrid. A simulation test is included, which proves how effectively the prosumers' power converters track the power setpoints obtained from the proposed strategy.Spanish Agencia Estatal de Investigacion ; Fondo Europeo de Desarrollo Regional
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