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One-level optimization methods have been proposed to optimize a single user’s load profile or a cluster of users in the smart grids. In this work, two two-level optimization methods are studied, one case considering technical requirements (case 1) and another considering economic criterion (case 2). In the upper level, the supplier optimizes the objective function. Meanwhile, at the lower level, users optimize their electrical costs. The proposed methods are based on Genetic Algorithm methods. In this sense, an indirect control is established in which users react to a price signal. Simulation results illustrate that both cases improve the demand profile and increase the retailer profit concerning an unscheduled case. However, when the supplier tries to maximize the profit, some users receive benefits to detriment of others, concluding that the technical approach is preferable to the economic one.

One-level optimization methods have been proposed to optimize the load profile of a single user or a cluster of users in the smart grids. In this work, two two-level optimization methods are studied, one considering technical requirements and other considering economic criteria. In the upper level, the supplier optimizes it objective function. Meanwhile, at the lower level, users optimize their electrical costs. The proposed methods are based on genetic algorithm methods. In this sense, an indirect control is established in which users react to a price signal. Simulations results illustrate that both cases improve the demand profile and increase the retailer profit. However, when the supplier tries to maximize the profit, some users receive benefits in detriment of others, concluding that the technical approach is preferable than the economical one.

Since distributed energy resources (DERs) can provide capacity in distribution system, distribution network reinforcement interacts with DER planning (DERP) for meeting load growth. This article proposes the coordination of distribution network reinforcement and DER planning in competitive market. The model is formulated as a multi-stage programming. In first stage, distribution companies (DISCOs) and DER aggregators (DERAs) make bidding plans for network reinforcements and DERP. In second stage, DSO checks the network security. If the check fails, DSO sends capacity signals to DISCOs and DERAs for more capacities. In third stage, the distributed market is cleared by DSO’s optimal operation problem and distribution locational marginal price (DLMP) is returned to DERAs as price signal. An iterative algorithm is proposed to solve the multi-stage model. The algorithm embodies the process of information interaction among DISCOs, DERAs, and DSO, where DISCOs and DERAs compete in capacity market under DSO’s supervision. Numerical results on IEEE 33-system and an actual 141-bus system demonstrate that the proposed model coordinates distribution network reinforcement and DERP in competitive market.

The complexity of the U.S. income tax system emerged in part from the differentiated fiscal treatment of specific investments and various sorts of business expenditures that, as Richard Wagner says, creates “a tax code so large that no one can read it and which creates nearly a unique tax liability for each taxpayer.” While tax scholarship documents the costs of complexity, current scholarship lacks a normative legal theory that could inspire an alternative to this practice of targeted credits and deduction rules. This paper builds on Epstein’s general Simple Rules framework to develop a radical simplification of income tax: the operationalization of a uniform expense rule, i.e., the application of a single deduction scheme across all expenses and investments. With regard to the trade-off between targeted rules and this general approach, this paper investigates the nature of a uniform expense rule and reveals its strengths with respect to political economy. First, a stable and universal expense rule would narrow the scope of politicians’ ability to concentrate benefits on special-interest groups and would limit rent-seeking. The abolition of deviating rules for investments would restrict the scope of tax optimization, meaning that individual and corporate tax liabilities would be more determined by the ability to pay them. The same policy would save companies and government millions of dollars that they currently spend on tax compliance and administration of the tax system, respectively. Last, a deduction rule that applies across all businesses and industries would be less price distortive and thus would enhance the quality of the price signal.

International audience; Electricity and water tariffs are undergoing significant changes due to smart metering, retail competition, and regulatory changes. Consumers now have to choose between different tariffs which are getting more and more complex. Theoretically, these new tariffs aim to use more cost-reflective pricing to incentivise consumers to adopt the right behaviours. However, empirical evidence from real pricing shows that consumers are confused by the complexity. Based on a lab experiment, this paper investigates how electricity and water consumers adopt more or less complicated tariffs and adapt their behaviours accordingly. We show that subjects prefer simple tariffs over complex ones. However, when they receive adequate information about tariffs and appropriate behaviours, they choose more complex tariffs. These results argue in favour of self-selection of tariff forms, in order to account for consumers’ different abilities to respond to the price signal. Lastly, we discuss the appropriateness of using a price mechanism to incentivise consumers.

Real-time pricing (RTP) is the pivotal component of demand response (DR) that promotes the power utilization of users in a cost-efficient way. This paper presents a reward fairness-based distributed RTP (RFbDRTP) framework for electric users to reduce the electricity consumption cost as well as experience the fairness from participating in DR. In RFbDRTP, a behavior welfare model (BWM) is developed to exploit the reward fairness strategy that returns the cost savings as a reward to the users in proportion to their load increase or decrease in DR. The model can motivate users to react to the price signal through adjusting their electricity consumption patterns, to in turn enable optimal distributed RTP for matching supply–demand. In this paper, users are assumed to interact with each other because of pricing based on the imbalance between load demand and electricity supply. We formulate the interactions among the users into a noncooperative game and give a sufficient condition to ensure the unique equilibrium in the game. After that, we develop a distributed algorithm and give a sufficient convergence condition of the algorithm. The simulation results show that the proposed RFbDRTP is effective in motivating users to participate in DR and matching demand with supply, and the distributed algorithm can converge to the equilibrium with a significant convergence rate.

Can prices convey information about the fundamental value of an asset? This paper considers this problem in relation to the dynamic properties of the fundamental (whether it is constant or time-varying) and the structure of information available to agents. Risk-averse traders receive two potential signals each period: one exogenous and private and the other, prices, endogenous and public. Prices aggregate private information but include aggregate noise. Information can accumulate over time both through endogenous and exogenous signals. With a constant fundamental, the precision of both private and public cumulative information increases over time but agents put progressively more weight on the endogenous signals, asymptotically disregarding private ones. If the fundamental is time-varying, the use of past private signals complicates the role of prices as a source of information, since it introduces endogenous serial correlation in the price signal and cross-correlation between it and innovations in the fundamental. A modified version of the Kalman filter can still be used to extract information from prices and results show that the precision of the endogenous signals converges to a constant, with both private and public information used at all times.

The purpose of the emission trading scheme (ETS), a cost-effective reduction, can be achieved through the active participation of liable firms. Although there was a steady increase in the transaction volume in the phase 1 (2015–2017) of Korea ETS, allowance used in flexible mechanism such as banking outweighed the amount of trading. By analyzing the trading behavior of liable firms in the Phase 1 of Korea ETS, we find out the determinants impeding the cost-effective reduction through active market participation. According to our empirical result, the liable firms who perceive ETS as a burden, trust government policy continuity and forecast that allowance price would go up tend to bank remaining allowance. On the other hand, the firms who were allocated larger allowance are more likely to trade. This result shows that heavy emitters having larger allowance could have realized economies of scale in transaction cost for MRV or seeking trading partners. Thus, market liquidity will be enhanced through government’s support to reduce transaction cost for small emitters, discover clear price signal, and provide policy signals that ETS can be another business opportunity.

Social interactions are widely understood to influence consumer decisions in many choice settings. This paper identifies causal peer effects in residential water conservation during the summer using variation from movers. We classify high-resolution remote sensing images to provide evidence that conversions of green landscaping to dry landscaping are a primary determinant of the reductions in water consumption. We also find suggestive evidence that without a price signal, peer effects are muted, indicating a possible complementarity between information and prices. These results inform water use policy in many areas of the world threatened by recurring drought conditions. (JEL D12, L95, Q25, Q54, Z13)

Carbon dioxide emissions from New Zealand’s transport sector have experienced rapid growth since 1990. In this paper, we investigate the scope for a targeted price signal to curb emissions growth a...

Demand-side management (DSM) involves a group of programs, initiatives, and technologies designed to encourage consumers to modify their level and pattern of electricity usage. This is performed following the methods such as financial incentives and behavioral change through education. While the objective of the DSM is to achieve a balance between energy production and demand, effective and efficient implementation of the program rests within effective use of emerging Internet-of-Things (IoT) concept for online interactions. Here, a novel DSM framework based on the diffusion and alternating direction method of multipliers (ADMM) strategies, repeated under a model predictive control (MPC) protocol, is proposed. On the demand side, the customers autonomously and by cooperation with their immediate neighbors estimate the baseline price in real time. Based on the estimated price signal, the customers schedule their energy consumption using the ADMM cost-sharing strategy to minimize their incommodity level. On the supply side, the utility company determines the price parameters based on the customer’s real-time behavior to make a profit and prevent infrastructure overload. The proposed mechanism is capable of tracking drifts in the optimal solution resulting from the changes in supply/demand sides. Moreover, it considers all classes of appliances by formulating the DSM problem as a mixed-integer programming (MIP) problem. Numerical examples are provided to show the effectiveness of the proposed framework.

Bakgrund: Företag har idag press från intressenter i samhället att reducera sina koldioxidutsläpp. Internprissättning av koldioxid är ett verktyg för företag att internalisera sina externa koldioxidkostnader. Det signalerar information till intressenter om kostnaden för företags koldioxidutsläpp i syfte att reducera dessa. För att fler företag ska anta ett internt pris på koldioxid, och därmed bidra till en koldioxidsnål ekonomi, finns ett behov att bedriva forskning om det upplevda signaleringsvärdet som ett internt pris på koldioxid medför. Syfte: Denna studie syftar till att undersöka hur beslutsfattare upplever signaleringsvärdet av ett internt pris på koldioxid. Metod: Studien har antagit en kvalitativ forskningsstrategi med en tvärsnittsdesign. Med en utgångspunkt i pragmatismen har studien antagit en abduktiv ansats. Studien har utfört fem semistrukturerade intervjuer med beslutsfattare från olika multinationella företag. Avslutningsvis har en tematisk analys använts som analysmetod. Slutsats: Ett internt pris på koldioxid upplevs medföra fler positiva signaleringsvärden till interna än till externa intressenter, men beror på vald prismetod. Interna signaleringsvärden upplevs primärt vara ökad förståelse, ändrad attityd och ändrat beteende. Externa signaleringsvärden upplevs vara uppvisat klimatinitiativ, ansvarstagande och hållbart ledarskap, vilka kan leda till förbättrat rykte, ökad legitimitet och viss risk för greenwashing. En koldioxidavgift upplevs vara mest effektiv för att driva beteendeförändring inom företag då det förenar ekonomiska intressen med företagets koldioxidutsläpp i en större utsträckning än övriga prismetoder. Background: Companies today face pressure from stakeholders in society to reduce their carbon emissions. Internal carbon pricing is a tool for companies to internalize the external costs associated with their carbon emissions. It signals information to stakeholders about the cost of carbon emissions for carbon reduction. For more companies to implement an internal carbon price, and contribute to a low-carbon economy, there is relevance in conducting research about the perceived signaling value of an internal carbon price. Purpose: The purpose of this study is to investigate how managers perceive the signaling value of an internal carbon price. Methodology: This study has been done with a qualitative cross-sectional research design and a pragmatic perspective with an abductive approach. The empirical data has been collected through five semistructured interviews with managers from different multinational companies. The analysis has been done with thematic analysis. Conclusion: An internal carbon price contributes to more positive perceived signaling values internally than externally, but is dependent on chosen price method. Perceived internal signaling values are primarily understanding, changed attitude, and changed behavior. Perceived external signaling values are demonstrated climate initiative, responsibility, and sustainable leadership, which can result in improved reputation, increased legitimacy, and risk for greenwashing. A carbon fee is perceived as the most effective price method for changed behavior within companies as it unites economic interests with carbon reduction more than other price methods.

Conventionally, demand response functions by communicating to electricity users through price signals embedded in their tariffs. These signals are intended to encourage a change in behavior, which hinges on the ability of users to understand their tariff and link it to the appropriate curtailment actions. This study focuses on demand-based tariffs, evaluating user's understanding of these tariffs and the conceptual grasp of power (rate of energy consumption) that they implicitly require. It also explores whether users exposed to these tariffs for extended periods develop a better understanding of them. Using a survey, the following points are sequentially evaluated: (1) Respondents' abilities to intuitively distinguish between energy/power (2) Their understanding of the different effects of curtailment actions under four distinct tariffs (3) Whether those subject to demand-based pricing outperform those subject to energy-based pricing. Despite a weaker conceptual understanding of power compared to energy, there were no significant differences between respondents' understanding of energy and demand-based tariffs. Comparing those subject to energy and demand-based pricing reveals that a majority were unaware of their own tariff (and hence which group they fall into), but for the minority of users who correctly identified their own tariffs, those subject to demand-based pricing outperform their energy-based counterparts. When presented with clear and instructive tariffs, respondents are largely able to deduce the consequences of curtailment actions, despite a weak conceptual understanding of power. A deeper problem is that the price signal may be entirely disregarded by an apathetic majority, reaching only an inquisitive minority.

Price Stability is a price condition since all parts which relate to marketing relationship reach the same information of price with CV 9% as the threshold value. Market integration is the rate of price movement in a different territory, where the same product will have the same price. Even though it is sold in a different place, the price signal and market information are evenly transmitted. The purpose of this research is to analyze the price stability of banana and to vertically analyze the market integration of banana commodities in Lampung. This research had been done in December 2019. The location election was done purposely. It was located in Lampung with the consideration that Lampung is a region of Indonesia's number one productivity crop of Banana. The used method of this research is a secondarydata analysis method. The data types and sources that are used in this research are secondary data such as the price list in producer and consumer‟s level of banana in Lampung. The collected secondary data had been time-series data for 10 years recently from 2009 to 2018 or as much as 120 monthly data. The data analysis used analysis variant and testing data by using Johansen‟s cointegration and VAR. Based from the research showing that the rate of stability for the banana supply in Lampung is stable. The vertical market integration analysis shows that the market at the farmer level is not a long-term relationship related to the consumer level, yet it still has a short-time relationship. KEY WORDS Price, market integration, banana, stability

A key feature of electricity generation in a distribution network is manifested by renewable generation with zero marginal cost. Existing market mechanisms are likely to fail in supporting such decentralized transactions while providing a reasonable price signal to compensate for the investment cost of renewable generators. Given this background, this paper first describes an average pricing market (APM) mechanism for pricing zero marginal cost renewable generation outputs in the distribution network. Then, a decentralized formulation of the APM mechanism is derived using the alternating direction method of multipliers (ADMM). Convergence of the decentralized mechanism can be guaranteed under some mild conditions for parameter setting. Finally, case studies are carried out to demonstrate the presented market mechanism. Simulation results show that the problem of always bidding a zero price by renewable generators in some existing markets can be avoided. The presented method also provides a solution for organizing decentralized electricity transactions in the distribution network and can converge to similar results with those obtained by the centralized one, with a relative error less than 5%.

This paper studies the coordination of heterogeneous thermostatically controlled loads (TCLs) to provide the real-time ancillary services. A market-based control framework is adopted for its advantages. The first advantage is that the demand curve-oriented approach makes it possible to form a unified control scheme for heterogeneous loads without identifying their different characteristics. The second one is that the broadcast price signal helps simplify the downlink control and reduce the implementation cost. Then, the separate demand curve construction strategies based on a virtual price for different types of TCLs are presented. The flexibility of each TCL is reflected through the curve, and its practical constraints, i.e., comfort requirements of users and operation constraints of devices, are satisfied explicitly. To ensure the control fairness and full utilization for the regulation ability of TCL cluster, a comfort-level-equality principle is applied in demand curve construction. Simulations are carried out to verify the effectiveness of the proposed method in providing frequency regulation services, for which a regulation capacity estimation method is developed. Finally, a series of case studies are conducted considering the practical situations, e.g., model errors, imperfect communication and sudden load change after the end of services.

The paper provides an analysis of Italian environmental taxes on electricity production and consumption in order to verify their consistency with the Polluters Pays Principle (PPP). The environmental external costs of air emissions generated by Italian thermal power plants are compared to environmental taxes paid by the same plants (fuel excise duties, SO2/NOx tax, ETS and levy on energy producers). As a basis for the comparison, the paper applies the methods for environmental external costs assessment recommended by the National Guidelines for the Evaluation of Investment Projects (2017). The PPP comparison highlights that the external costs related to thermal power plants emissions amount to about € 9,400 million (53.8 euro per MWh produced) whereas only € 350 million are actually paid through the above-mentioned environmental taxes (3.8% of the external costs generated). Indeed, the environmental taxes directly paid by all electricity customers in their bills (excise duty on electricity, system charges for subsidising renewable energy sources) are of the same order of magnitude of the external costs of power plants. However, seen from the PPP point of view, these two taxes have the drawback of environmental tax payment being made also by "green" customers, i.e. whose electricity is bought with the guarantee of being "produced from renewable energy sources". The authors argue that environmental taxes directly falling on electricity producers are consistent with the PPP and provide in principle a better price signal to electricity markets, rather than environmental taxes directly paid by customers. Shifting current environmental taxes from electricity consumption to production would support the implementation of two of the main targets of the National Energy Strategy (2017), such as the progressive phase-out of coal at 2025 and the 55% RES electric target at 2030, while increasing the coherence and fairness of taxes paid on electricity.