Water demand management in Mediterranean regions

Water sustainability needs a balance between demand and availability: 1) Water demand management: demand may be managed by suppliers and regulations responsible persons, using measures like invoicing, consumptions measurement and users education in water conservation measures; 2) Augmentation of water supply: availibility may be augmented by infrastructural measures, waste water reuse, non-conventional resources and losses reduction. Water Demand Management is about achieving a reduction in the use of water resources, normally through increased efficiency of water application. The main objective of this paper is the application of these concepts to Mediterranean regions.

Water Demand Management in England and Wales: constructions of the domestic water-user

YesMeasures to manage demand include implicit and explicit messages about domestic water-users which have important potential impacts on their perceptions and practices. Drawing on recent literature, this paper identifies three different ¿dimensions¿ along which demand management measures¿ constructions of the water-user may vary: these relate to whether the water user is passive or active, whether they are motivated by individual or common needs, and whether they perceive water as a right or a commodity. Demand management measures currently used in England and Wales are then discussed and analysed. The paper concludes by highlighting the importance of communications associated with demand management, and in particular, notes the need to consider the cumulative impact of messages and their interactions with people¿s existing understandings

Residential demand management using individualised demand aware price policies

This paper presents a novel approach to Demand Side Management (DSM), using an “individualised” price policy, where each end user receives a separate electricity pricing scheme designed to incentivise demand management in order to optimally manage flexible demands. These pricing schemes have the objective of reducing the peaks in overall system demand in such a way that the average electricity price each individual user receives is non-discriminatory. It is shown in the paper that this approach has a number of advantages and benefits compared to traditional DSM approaches. The “demand aware price policy” approach outlined in this paper exploits the knowledge, or demand-awareness, obtained from advanced metering infrastructure. The presented analysis includes a detailed case study of an existing European distribution network where DSM trial data was available from the residential end-users

Optimized Household Demand Management with Local Solar PV Generation

Demand Side Management (DSM) strategies are of-ten associated with the objectives of smoothing the load curve and reducing peak load. Although the future of demand side manage-ment is technically dependent on remote and automatic control of residential loads, the end-users play a significant role by shifting the use of appliances to the off-peak hours when they are exposed to Day-ahead market price. This paper proposes an optimum so-lution to the problem of scheduling of household demand side management in the presence of PV generation under a set of tech-nical constraints such as dynamic electricity pricing and voltage deviation. The proposed solution is implemented based on the Clonal Selection Algorithm (CSA). This solution is evaluated through a set of scenarios and simulation results show that the proposed approach results in the reduction of electricity bills and the import of energy from the grid

Comments on a monetarist approach to demand management

Monetary policy ; Macroeconomics

The implementation of discrete demand management algorithms within energy systems modelling

Traditionally, demand side management (DSM) programs have been driven by utilities. With the prospect of growth in the utilization of building-integrated micro-generation, DSM offers opportunities for additional energy savings and CO2 emission reductions through better utilisation of local renewable energy resources. This paper examines the feasibility of using discreet demand management (DDM) to improve the supply/demand match. For many combinations of micro-generation and DDM controls, it is necessary to know the environmental conditions (i.e. temperatures and lighting levels) within the buildings being modelled. One method would be to embed all the renewable energy technologies and DDM algorithms within a detailed simulation program. An alternative method, investigated in this study, involves coupling two existing tools: a dynamic building simulation program (ESP-r) and a demand/supply matching program (MERIT) that incorporates DDM algorithms and renewable energy system technologies. These two programs interact at the time-step level and exchange calculated parameters (relating to loads, supply potentials and prevailing environmental conditions) to enable an evaluation of DDM techniques in terms of energy saving and occupant impact. This paper describes the technique and presents simulation results relating to a number of building cases

Modeling Storage and Demand Management in Electricity Distribution Grids

Storage devices and demand control may constitute beneficial tools to optimize electricity generation with a large share of intermittent resources through inter-temporal substitution of load. We quantify the related cost reductions in a simulation model of a simplified stylized medium-voltage grid (10kV) under uncertain demand and wind output. Benders Decomposition Method is applied to create a two-stage stochastic program. The model informs an optimal investment sizing decision as regards specific 'smart grid' applications such as storage facilities and meters enabling load control. Model results indicate that central storage facilities are a more promising option for generation cost reductions as compared to demand management. Grid extensions are not appropriate in any of our scenarios. A sensitivity analysis is applied with respect to the market penetration of uncoordinated Plug-In Electric Vehicles which are found to strongly encourage investment into load control equipment for `smart` charging and slightly improve the case for central storage devices.Storage, demand management, stochastic optimization, Benders Decomposition