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Aims to show how interview data may be used to obtain an indication of the price elasticity of household electricity consumption. Examines how respondents think they will react to price changes.

The purpose of this study was to design a renovation plan for a university campus building (Department of Electrical and Computer Engineering) with the aim to achieve nearly zero energy performance, ensuring a low specific demand (lower than 44 kWh/m²) and a high level of on-site renewable generation (equivalent to more than 20 per cent of the energy demand).

The baseline demand was characterized based on energy audits, on smart metering data and on the existing building management system data, showing a recent reduction of the electricity demand owing to some implemented measures. The renovation plan was then designed with two main measures, the total replacement of the actual lighting by LEDs and the installation of a photovoltaic system (PV) with 78.8 kWp coupled with an energy storage system with 100 kWh of lithium-ion batteries.

The designed renovation achieved energy savings of 20 per cent, with 27.5 per cent of the consumed energy supplied by the PV system. This will ensure a reduction of the specific energy of the building to only 30 kWh/m², with 42.4 per cent savings on the net-energy demand.

The designed renovation proves that it is possible to achieve nearly zero energy goals with cost-effective solutions, presenting the lighting renovation and the solar PV generation system a payback of 2.3 and 6.9 years, respectively.

This study innovated by defining ambitious goals to achieve nearly zero energy levels and presenting a design based on a comprehensive lighting retrofit and PV generation, whereas other studies are mostly based on envelope refurbishment and behaviour changes.

The paper aims to examine the effects of exchange rate fluctuations on real output, the price level, and the real value of components of aggregate demand in Egypt and Turkey.

Building on a theoretical model that decomposes movements in the exchange rate into anticipated and unanticipated components, the empirical investigation traces the effects through demand and supply channels.

In Turkey, anticipated exchange rate appreciation has significant adverse effects, contracting the growth of real output and the demand for investment and exports, while raising price inflation. Random fluctuations in Turkey have asymmetric effects that highlight the importance of unanticipated depreciation in shrinking output growth and the growth of private consumption and investment, despite an increase in export growth. In Egypt, anticipated exchange rate appreciation decreases export growth. Given asymmetry, the net effect of unanticipated exchange rate fluctuations, in Egypt, decreases real output and consumption growth and increases export growth, on average, over time.

In light of the country‐specific evidence, future research should extend the investigation using panel estimation, incorporating various demand and supply shocks along with exchange rate fluctuations, to establish the relative importance of various shocks on macroeconomic performance across MENA countries.

While adhering to a flexible exchange rate policy to boost competitiveness, managing fundamentals to reduce excessive volatility impinging on the economic system over time should top the policy agenda.

Excessive volatility in the real effective exchange rate could be detrimental to real growth, over time, as the evidence for Turkey and Egypt illustrates.

Using quarterly data for a sample of 17 industrial countries, the purpose of this paper is to study asymmetry in the face of monetary shocks compared to government spending shocks.

The paper outlines demand and supply channels determining the asymmetric effects of monetary and fiscal policies. The time‐series model is presented and an analysis of the difference in the asymmetric effects of monetary and fiscal shocks within countries is presented. There then follows an investigation of the relevance of demand and supply conditions to the asymmetric effects of monetary and fiscal shocks. The implications of asymmetry are contrasted across countries.

Fluctuations in real output growth, price inflation, wage inflation, and real wage growth vary with respect to anticipated and unanticipated shifts to the money supply, government spending, and the energy price. The asymmetric flexibility of prices appears a major factor in differentiating the expansionary and contractionary effects of fiscal and monetary shocks. Higher price inflation, relative to deflation, exacerbates output contraction, relative to expansion, in the face of monetary shocks. In contrast, larger price deflation, relative to inflation, moderates output contraction, relative to expansion in the face of government spending shocks. The growth of output and the real wage decreases, on average, in the face of monetary variability in many countries. Moreover, the growth of real output and the real wage increases, on average, in the face of government spending variability in many countries. Asymmetry differentiates the effects of monetary and government spending shocks within and across countries. The degree and direction of asymmetry provide a new dimension to differentiate between monetary and fiscal tools in the design of stabilization policies.

The paper's evidence sheds light on the validity of theoretical models explaining asymmetry in the effects of demand‐side stabilization policies. Moreover, the evidence should alert policy makers to the need to relax structural and institutional constraints to maximize the benefits of stabilization policies and minimize the adverse effects on economic variables.

The purpose of this paper is to propose a novel demand response method for real‐time (RT) balancing markets, which relies on dynamic demand control (DDC) based on frequency linked RT prices.

A RT balancing market, where the RT price varies inversely with the system frequency, is described. In such a market, producers and consumers can get the RT price, simply by monitoring the frequency deviations themselves. Air conditioning load, the main contributor of summer peaks, is selected for DDC. A physically based model of air conditioner load is taken to simulate the load control. A smart load controller is proposed that changes the thermostat setting with deviations in grid frequency/RT price. Simple examples are simulated to show the load reductions achieved by DDC in a single air conditioner, a group of large number of air conditioners and a RT market consisting of four generation companies and four distribution companies.

The result of simulation on a single air conditioner shows that significant reduction in energy consumption can be achieved during severe frequency dips in a RT market. The results of simulation in an example of a RT market show that such load control not only results in better frequency control but also lowers the RT price of power.

The demand control mechanism suggested in this paper can be applied to Indian market setting but its applicability to other markets might be limited due to differing, reliability standards, market rules, and regulatory framework.

This paper finds that DDC by distribution companies based on RT price/frequency signal not only results in a significant benefit to these companies and consumers but also helps the system operator in frequency regulation. By making the demand‐side participate in frequency regulation, such control can potentially facilitate an increase in renewable energy portfolio.

The purpose of this paper is to explore how differently aggregated order data may affect inventories and service levels in a serial supply chain and compares the results against various levels of information sharing. By performing sensitivity analysis, critical parameters are identified and conjectures for explaining the divergent results on the value of information sharing in prior literature are given.

By using discrete event simulation, the paper analyses various approaches of differently aggregated order data compared to shared demand information.

The experiments show that suppliers cannot accurately estimate demand means and variances because of time‐depending order quantities and biasing effects of order inter‐arrival times. This may lead to inappropriate computations of reorder points and safety stocks. The aggregation of order data can improve the calculations resulting in lower inventories with almost identical service levels. The mean inventory can also be reduced by sharing information but may lead to considerably lower service levels.

As discovered in this paper, simplifications in the supply chain structure may have large effects on the experimental results. Therefore, the value of information sharing and order aggregation strategies should be analyzed in a more complex supply chain network.

Some ordering mechanisms have the effect of increasing the demand variance for upstream companies. This amplification may lead to inefficiencies throughout the entire supply chain. The paper proposes solutions to managers on how they can benefit from order data aggregation and information sharing. The per period variances may be reduced leading to smaller safety stocks and lower costs for the entire supply chain.

The paper shows that the performance of a supply chain may be improved by aggregating order data and compares the results with improvements derived from information sharing strategies.

The purpose of this paper is to analyze the role of industrial self-supply in the transition process from centralized energy generation based on fossil fuels and nuclear power to decentralized supply based on renewable energies in the Bavarian electricity system.

To quantify effects on system and price stability, a model of the Bavarian electricity grid is created and used to simulate electricity system behavior during a 1-year period for scenarios that are characterized by parameter variations in industrial self-supply, nuclear power capacity, renewable power generation and the capacity of electricity imports.

The simulations show that industrial self-supply can reduce instances of maximum grid utilization by 23 per cent and, based on the merit-order effect, decrease electricity market prices by 1.90 and 5.03 €/MWh in the scenarios with and without nuclear power, respectively; these values represent 5.7 and 15.0 per cent of average market prices from 2014.

The analysis shows that industrial self-supply can contribute to transforming the electricity system in a secure, sustainable and affordable manner. However, merit-order-based price effects have a limitation concerning the future applicability of results as quantified effects may not be permanent when the electricity system adapts.

This paper connects industrial self-supply and the merit-order effect within a nodal energy model. It provides insights into the relevant interdependencies and reciprocal effects by means of a simulation.

The purpose of this paper is to investigate both cooperative and competitive strategies of firms that may cause accidents. The firms may exchange information about the previous accidents associated with their products in order to reduce accident probabilities and the amount of damage. Thus, these firms may cooperate on this point. On the other hand, they compete on quantities after deciding whether accident information is to be disclosed. This situation is termed coopetition. In order to address the issue of disclosure of accident information, an economic model is developed and it derives two main conclusions. First, there is a unique equilibrium where firms choose to not disclose their accident information. Second, the equilibrium strategies of firms are Pareto inferior for them when the condition relating to marginal effort costs and potential demands is satisfied. Thus, whether the coopetitive situation that firms exchange their accident information cooperatively and choose their quantity levels competitively is desirable for firms depends on the magnitude of the cost reduction and demand reduction effects.

The serious economic difficulties that Peru is confronting, its rapid inflation, the failure of the IMF stabilisation programme, and the recent adoption of a new economic programme are all topics that are worth analysing.

Electricity utilization at electricity peak hour may differ from every single administration region, for example, mechanical region, business territory and residential zone. This paper introduces a demand-side load management (DSM) strategy, which is one of the utilization of smart grid (SG) that is fit for controlling loads inside the residential working so that the client fulfillment is augmented at least expense.

In this paper, a heuristic algorithms-based energy management controller is intended for a residential region in a SG. Here, Antlion Optimization technique is used for DSM techniques such as load shifting, peak clipping, and valley filling in the residential sectors for 24 h with the help of stochastic function to determine the detection of random distribution of the load.

This proposed algorithm offered the greatest fulfillment and least expense caused by the consumers when compared to the traditional cost by taking the individual consumer preferences for the loads and the ideal time scheduling for the load, which is obtained from the rebuilding trap.

Simulation results demonstrate that the comparison of the cost incurred by the users obtained by the DSM techniques is satisfiable.