Showing papers on "Load shifting published in 2011"

Virtual power plant system and method incorporating renewal energy, storage and scalable value-based optimization

Abstract: Methods and systems provided for creating a scalable building block for a virtual power plant, where individual buildings can incorporate on-site renewable energy assets and energy storage and optimize the acquisition, storage and consumption of energy in accordance with a value hierarchy. Each building block can be aggregated into a virtual power plant, in which centralized control of load shifting in selected buildings, based on predictive factors or price signals, can provide bulk power for ancillary services or peak demand situations. Aggregation can occur at multiple levels, including developments consisting of both individual and common renewable energy and storage assets. The methods used to optimize the system can also be applied to “right size” the amount of renewable energy and storage capacity at each site to maximize return on the capital investment.

Centralized and decentralized control for demand response

Abstract: Demand response has been recognized as an essential element of the smart grid. Frequency response, regulation and contingency reserve functions performed traditionally by generators are now starting to involve demand side resources. Additional benefits from demand response include peak reduction and load shifting, which will defer new infrastructure investment and improve generator operation efficiency. Technical approaches designed to realize these functionalities can be categorized into centralized control and decentralized control, depending on where the response decision is made. This paper discusses these two control philosophies and compares their response performances in terms of delay time and predictability. A distribution system model with detailed household loads and controls is built to demonstrate the characteristics of the two approaches. The conclusion is that the promptness and reliability of decentralized control should be combined with the controllability and predictability of centralized control to achieve the best performance of the smart grid.

Building control and storage management with dynamic tariffs for shaping demand response

Abstract: The results from a proof-of-concept study combining modern building automation systems (BAS) with dynamic electricity tariffs are presented. The use of a building automation system that optimizes the electricity demand of a retail end-consumer while managing a local battery unit and respecting all comfort constraints, e.g., on room temperature, illuminance, and indoor air quality, is proposed. The optimization is done in a fully automated fashion, i.e. without any need of action from an external operator. The study focuses on the situation of end-consumers in the city of Zurich, Switzerland. Demand shifting as well as effects on the cost of electricity consumption for different retail consumer groups, i.e. households and offices using their typical usage profiles are assessed. In-house battery systems are introduced as additional means of electricity demand flexibility. Extensive simulations (500+ full-year simulations) are performed for different building types, battery types, and usage profiles. The overall load shifting effect on the aggregated load curve of the city of Zurich is evaluated.

Investigating the effects of dynamic demand side management within intelligent Smart Energy communities of future decentralized power system

Abstract: This paper firstly discusses the benefits of transforming conventional power system into decentralized systems which are composed of clusters of smart energy communities, supplied mainly by renewable energy sources. Application of Demand Side Management within such communities has been identified as a necessity to account for the required degree of active management in such dynamic systems. The intelligent Smart Energy Community project and its concepts have been discussed. An electricity demand model has been created and used to firstly determine the appropriate size of a community for implementation of an effective and non-disturbing load shifting demand side management. The model is then utilized to quantify the potential benefits of applying load shifting demand side management with a variable severity level.

Power consumption in refrigeration systems - Modeling for optimization

Abstract: Refrigeration systems consume a substantial amount of energy. Taking for instance supermarket refrigeration systems as an example they can account for up to 50–80% of the total energy consumption in the supermarket. Due to the thermal capacity made up by the refrigerated goods in the system there is a possibility for optimizing the power consumption by utilizing load shifting strategies. This paper describes the dynamics and the modeling of a vapor compression refrigeration system needed for sufficiently realistic estimation of the power consumption and its minimization. This leads to a non-convex function with possibly multiple extrema. Such a function can not directly be optimized by standard methods and a qualitative analysis of the system's constraints is presented. The description of power consumption contains nonlinear terms which are approximated by linear functions in the control variables and the error by doing so is investigated. Finally a minimization procedure for the presented problem is suggested.

Active load management in an intelligent building using model predictive control strategy

Abstract: This paper introduces PowerFlexHouse, a research facility for exploring the technical potential of active load management in a distributed power system (SYSLAB) with a high penetration of renewable energy and presents in detail on how to implement a thermal model predictive controller for load shifting in PowerFlexHouse heaters' power consumption scheme. With this demand side control study, it is expected that this method of demand response can dramatically raise energy efficiencies and improve grid reliability, when there is a high penetration of intermittent energy resources in the power system.

Impacts of demand side management on bulk system reliability evaluation considering load forecast uncertainty

Abstract: Electric power utilities are facing with increasing awareness of environment conditions and very expensive infrastructure investments due to the continually increasing demand for electricity. Demand side management can play a very important role in meeting the challenges faced by power utilities. This paper is mainly focused on the effects of one aspect of the various demand side management measures, which is load shifting, on reliability indices, reliability index probability distributions and peak load carrying capabilities for a bulk electric system. Load forecast uncertainty is an important consideration in an electric power system particularly when there is increased competition in the electric utility industry and more comprehensive risk evaluation is required. The interactive impacts of demand side management programs and the consideration of load forecast uncertainty on system reliability are also investigated.

A generalized load management gateway coupling smart buildings to the grid

Abstract: Buildings are currently largely passive participants in the electric grid. As functional and residential buildings are responsible for a sizeable share of energy consumption in the industrialized world, use in demand side management schemes is a promising area in a future smart power grid. As each individual building, especially in the residential sector, offers only limited load shifting potential and associated financial gain, acceptance of demand response programs that require manual user interaction is unlikely. Instead, schemes based on automatic control are a viable alternative. This paper proposes a building agent, which acts as load management gateway, autonomously managing a building as a single unit, utilizing load models on one hand and a generic communication scheme that avoids close coupling of building and grid on the other hand. The agent manipulates the consumption profile of the building in a way, which matches the demands of the smart grid and offers the resulting load shifting potential to the grid.

Load-shifting opportunities for a typical South African cement plant

Abstract: Investigations into demand side reductions have been encouraged by the utility in sectors with high electricity consumption, such as the cement industry. It is responsible for 5% of the electrical consumption for the mining and industrial division of the country. It has also been estimated that by 2020 this sector will be ranked fifth for energy savings potential. This paper investigates the potential of a load-shifting scheme to reduce evening peak loads and save electrical costs on a raw mill at a South African cement plant. A simulation was performed, which showed that six hours of load-shifting could be achieved, without adversely affecting production. This was corroborated by a pilot study where the load was successfully shifted for six hours over a week-long period. The specific raw mill would achieve a reduction in yearly electrical costs of 2% when employing this load-shifting strategy. The results however showed that cost-saving opportunities are highly dependent on the reliability of the mills and on the change in production demand. Therefore, load-shifting schemes have to be highly adaptable on a daily basis to shift load when possible.

The effect of peak load shift to off-peak periods on pumping systems

Abstract: Demand Side Management (DSM) initially focussed on reducing the Eskom evening peak. However, over the last few years the electricity demand profile, although reduced during Eskom peak periods, broadened. Eskom also has a problem with base load supply between the morning and evening peaks during the day. Load shifting is therefore still necessary, but Eskom now requires the load to be shifted to night time periods when electricity demand is lower. In this paper the effects of shifting peak load to the off-peak periods is discussed. Simulations on different pumping layouts show that the success of load shifting projects can, inter alia, be attributed to sufficient water storage capacity. This paper shows that load shift on pumping systems are still possible within the new constraints.

Modeling of demand side shifting potentials for smart power grids

Abstract: Outlining the potential of demand response or load shifting techniques is vital for the smart power grid. While different approaches exist on how to model the demand response ability of different consuming nodes or whole subsystems of the power grid, the existing approaches tend to show the maximum amount of shiftable energy at any given point of time without taking into account the correlation between the temporal duration of shifted energy and its amount. A different approach that tries to solve this question is presented. The outlined solution includes the possibility to include the estimation on possible rebound effects that could happen by introducing demand response techniques.

The potential for compensating wind fluctuations with residential load shifting of electric vehicles

Abstract: Intermittent renewable energy sources introduced in large-scale deployments challenge the stability of the power grid. In this paper, we estimate the potential of residential demand control for compensating wind fluctuations, additionally, the control when charging electric vehicles at home. In our approach, household devices and electric vehicles generate a flexible load that can be applied to smooth fluctuating wind power. From this, we examine the future potential for creating residential load-controlled capacities with different electric vehicle penetrations and charging levels. We also show that communities with more than 20% of households owning electric vehicles have the flexibility to smooth wind farm fluctuations.

Optimization of the compressed air-usage in South African mines

Abstract: The critical electricity supply in South Africa has necessitated the implementation of demand-side management (DSM) projects. Load shifting and energy efficiency projects were introduced on mining sectors to reduce the electricity usage during day peak time. As the compressed air networks is using a large amount of mines' electricity, we investigate in this paper the possibility of improving and optimizing the compressed air usage at two different mines to reduce the electricity consumption on the compressed air system.

Investigating the ability of various buildings in handling load shiftings

Abstract: In modern constructions of residential buildings, several energy saving technologies exist Therefore, when such buildings are renovated, various investments can be considered The contribution of this article is a method for evaluating the ability of several renovating configurations to keep the inhabitants in a comfortable situation during load shifting periods This question is of importance in the relationship, and then in the price setting, between the users (inhabitants) and the energy provider who uses these load shifting periods to optimize his production on a regional or national scale

Estimations of cost and CO 2 emissions for smart grids using a linear programing approach

Abstract: A smart grid is an electricity network that uses digital technology to monitor and manage the transport of electricity from all generation sources to meet the varying electricity demands of end users. In this paper, the smart grid is defined as the electric power system consistent with the BASE or BLUE scenarios in the Energy Technology Perspectives 2010 with the large scale renewable integration and the capability of demand response. Quantitative estimations of the cost and the CO 2 emissions are made using a linear programing approach for the BASE and BLUE smart grids in the US. Among the BASE smart grids, a smart grid where a high penetration of renewables is considered is more expensive than the BASE scenario. The increased cost was due to expensive renewables. Another smart grid where both high renewables and load shifting, were applied demonstrated the least CO 2 emissions. The trend in increasing CO 2 emissions continues 2050. Among the BLUE smart grids, both cost and CO 2 emissions were decreased when load shifting was applied. Temporal change of CO 2 emissions clearly shows a decreasing trend. Then, the capacity of the electric storage required for the integration of renewables at 2050 was estimated to be 9.0GW. Batteries used in electric vehicles will be used for the electric storage at low cost. Finally the cost saving for the load shifting was estimated to be 1.64 × 1011 USD by a break-even point analysis. The cost saving is equivalent to the yearly saving of 3.64USD/household/year for forty five years. If the saving of 3.64USD/household/year is not enough for utilities to cover the cost increased due to the load shifting equipments, the utilities and customers have to share the extra cost.

A methodology for evaluating the energy, peak load and comfort effects of demand response control strategies for electric heating

Abstract: Today due to new developments in the field of smart appliances and communications, new strategies in the residential sector can be employed to maintain the balance between electricity supply and demand. However the physical effects and the methods to evaluate the impact of these actions in the electric market system are not totally understood. This article describes a methodology that makes possible the evaluation of Demand Response (DR) actions in thermal household appliances, from which the possible benefits can be determined for the consumer and for the electric grid. The demand response actions that serve as example are associated with electric home heating load shifting when responding to a day-ahead real-time-pricing. The randomized operation of a large number of electric heaters is simulated through a simple building thermal model. This enables calculation of the change in peak power during, preceding and after the demand response event, as well as the change in energy used. An important feature is that due to the introduction of a thermal model in our analysis, the energy recovery ("energy pay-back" - increase in consumption of energy after the control period application of a load shift) can be also determined by comparison with a reference case where there is no load control. The model also simulates changes in the magnitude and timing of peak load and during, before and after the load shift. This aspect will provide important information on how much load can be reduced with the introduction of a DR action, but also how much it can increase after the DR action (or before the DR action, if a pre-heating strategy is used). The simulations are then coupled with real-time-pricing tariffs which represent the actual electric power supply price. Subsequently economic benefits can be calculated at different times of the day and for different weather conditions, taking into account all the physical features described previously.

IEC 61850 based smart load-shifting through on-load tap changer control

Abstract: In this paper the feasibility of applying a Smart remedial action scheme (RAS) based on the coordinated control of on load tap changers is investigated Different from most of the existing RASs, the proposed method uses the measured voltage and current phasors to enhance the system security by balancing the power flow in the lines feeding a load The configuration of implementing the method with IEC 61850 standard is provided The simulations on a small test system demonstrate the validity of the scheme

Load Shifting and Power Gird Economic Operation

Abstract: Aiming at the characteristic of insufficient electricity at power using peak period and surplus electricity at power using valley period in power gird,this paper analyzed energy losses of transformers and lines,obtaining the calculation formula to carry out load shifting which could reduce energy losses of transformers and lines,as well as transformer's ideal avoiding peak load coefficient.Combined with the actual situations of power grid,this paper raised basic measures to carry out load shifting.

Large Scale Integration of Wind Energy by Financial Mechanisms for Support of Pumped Hydro Storage Installations

Abstract: Intermittent nature of the renewable energy sources (RES) like wind, solar and waves is one of the limitation factors for their higher penetration in the networks. This problem was firstly recognized in the autonomous networks as RES penetration in those systems easily reached technical limits. Now, similar problems are facing big power systems when RES penetration exceeds certain levels. Effective use of energy storage could solve the intermittency problem and it could increase RES penetration. Today the most widespread storage in power systems is the pumped or reversible hydro storage (PHS) which has many advantages and can provide multiple services in transmission, distribution and generation markets (e.g. support to RES integration, grid up-grade and ancillary services, load shifting etc.). Currently, all services in electricity market are not properly regulated and commercialised so there is big uncertainty how investments in energy storage will be recovered. Several EU documents support the development of measures that could provide confidence to those investing in storage so that they will be able to realise benefit from their investment. In this paper we propose development of Feed-in tariffs (FIT) for Pumped Hydro Storage as support to RES integration and we discuss the necessary market organization for their successful application. Proposed FIT for PHS is also tested in market environment trough developed mathematical models and by use of the historical market data. Proposers of FIT for PHS systems should take into account the local particularities of possible development of PHS and according to that, they should propose one or several levels of FIT. Supported level of FIT and limit on load factor of turbines in PHS, for particular energy system, should be optimized according to desirable level of excess production from RES or according the needs of security of energy supply provided by PHS.

PLC based peak load control for chemical industries

Abstract: Chemical processes, employed for manufacturing basic chemicals are highly energy intensive. Due to escalating costs of fossil fuels and capacity addition, the electricity cost has been increasing for the last few decades. Electricity intensive industries find it very difficult to cope up with higher electricity charges particularly with time-of-use (TOU) tariffs implemented by the utilities with the objective of flattening the load curve. Load management programs focusing on reduced electricity use at the time of utility's peak demand, by strategic load shifting, is a viable option for industries to reduce their electricity cost. This paper presents an optimization model and formulation for load management of continuous process industries. The case study of a chemical industry is taken for conducting load management study. The formulation utilizes nonlinear programming technique for minimizing the electricity cost and reducing the peak demand, by rescheduling the loads, satisfying the industry constraints...

Load management effect on optimum sizing of stand-alone hybrid distributed generation

Abstract: This paper presents an optimum sizing assessment for stand-alone hybrid distributed energy system feeding a sub-village sized household community in the rural areas, affected by loading types based on demand side management principle. Simulations are carried out over the combination of hybrid power generation taking into account PV-battery, wind turbine, and diesel generator. Three loading management in which considered in this study are peak clipping, load shifting, and valley filling. Optimum hybrid generation sizing for each loading type is subject to minimum cost of energy. Besides, renewable generation fraction provided system optimum sizing is analyzed accordingly. The simulation result reveals that the least cost of energy is achieved by load shifting scheme with USD 0.39/kWh taking into account the combination of PV-battery, wind turbine, and diesel generator. In addition, the largest renewable energy fraction obtained from load shifting type as well, accounted for 73%.

A load truck and a method of offloading a load unit

Abstract: The invention concerns moving of load units laden on pallets or load sheets. The invention provides a load truck (10) (Figure 2) for moving load units (40). The truck (10) includes a load support structure (12) and a travelling member (28) for pushing a load unit (40) from the structure (12). It includes also a hydraulic cylinder assembly (32), acting between the member (28) and a member (26) fixed with respect to the structure (12), for displacing the member (28). The invention further provides a method (Figure 6) of offloading a load unit (40) from a load truck (10). It involves anchoring the truck (10) during at least a last stage of forward pushing of the load unit (40) from the truck (10) by means of a load shifting mechanism (25) of the load truck (10), thereby to restrain the load truck (10) against rearward displacement and push the load unit (40) against an object (48).

Optimization and integration of renewable energy sources on a community scale using Artificial Neural Networks and Genetic Algorithms

Abstract: The goal for this paper and my research is to reduce overall cost associated with electricity use at UC Merced. UC Merced presents itself as a unique opportunity for to model integration and optimization of renewable energy sources. It will be discussed exactly what makes UC Merced unique and how UC Merced has set a path towards higher energy efficiency on a community level. Furthermore, I will discuss difficulties involved with integrating renewable resources and then proceed to analyze techniques for further optimization as UC Merced continues its path towards zero net energy. One of these optimization techniques, genetic algorithms; I will discuss in some detail as it was the technique chose to verify the results of the optimization. The main goal of this study is to determine the effect of moving UC Merced‘s Central Plant load closer to or completely during daylight hours when there is inexpensive (solar) energy available or during the night time when energy pricing is minimum. While it seems logical to shift the cooling load, it has yet to be quantitatively shown that such load shifting would be more cost effective. Genetic algorithm (GA)-based Artificial Neural Network (ANN) models are used for demand and energy production forecasting and then GA based cost optimization is performed to find optimum time window for load shifting. We determined that loading shifting can be beneficial and the associated savings are presented for both summer and winter seasons.