Proposal of a New Procurement Strategy of Frequency Control Reserves in Power Systems: The Italian Case in the European Framework

Over the last few years, a strong penetration of Intermittent Renewable Energy Sources (IRES) has been in progress in the Italian power system. In this new framework, the dispatching activity must improve its efficiency to ensure adequacy and security of the national electricity system. European market integration initiatives are making this goal achievable, provided that the coherency of market price signals and reserve procurement at the European level are guaranteed. For this reason, the Italian Transmission System Operator (TSO), Terna, started to investigate the opportunity to align the Italian reserve-procurement approach to the one adopted in most European countries, procuring Replacement Reserve (RR) in dedicated auctions held in advance of the day-ahead market. The aim of this new methodology is to improve the coherency of price signals arising from the integrated European day-ahead market, anticipating potential scarcity conditions, thus helping to keep adequacy standards high. This paper describes the characteristics of a possible new reserve-procurement model based on the European benchmark. Comparative simulations are presented, estimating the impact of the new approach in terms of outcomes and costs of both the energy and ancillary services markets in Italy. The results of this study suggest activation of the reserve auction only in the cases in which the TSO expects a potential risk of simultaneous reserve scarcity across European countries.

A Capacity Market for the Transition towards Renewable-Based Electricity Generation with Enhanced Political Feasibility

There is a debate if electricity markets on the basis of energy-only markets ensure a sufficient generation capacity. Various capacity mechanisms are discussed to tackle this potential problem. Capacity auctions with reliability options are seen as one market-based solution. Assuming a perfect energy-only market, this mechanism leads to an equilibrium with an optimal capacity mix. This optimum is missed if there are distorted price signals at the electricity market. This is a serious problem since, despite substantial cost reductions, renewable-based electricity generation still depends on subsidies, which are not internalized at electricity markets. We develop a capacity market that internalizes subsidies for RES without direct intervention in the electricity market. The result is an endogenous discrimination of capacity prices, which enhances acceptance for a capacity market. Arising incentives direct the capacity mix to an equilibrium where discriminated prices converge to one uniform capacity price. The equilibrium is the optimal answer of fossil capacity to RES-based electricity generation.

Price Signal of Tilled Land in Rural China: An Empirically Oriented Transaction Costs Study Based on Contract Theory

Prices are effective signals of many market conditions, while underpricing of tilled land in rural China poses a dilemma to this common sense. Using n = 191 imputed contracts in rural China, this paper aims to investigate the role of ambiguous property rights in the context of agricultural reforms. Using rank statistics, several candidate variables in the transaction costs function fc(•) were identified, including BMI (Body Mass Index), Knowledge, Subtraction and Farming Experience. The results show clear evidence for underpricing to restrain competition under ambiguous property rights. More illuminatingly, non-parametric regression analysis specifies a well-founded transaction costs function: increasing Subtraction by one unit increases transaction costs by the equivalent of US$513.40, while a one-year increase of farming experience reduces transaction costs by US$116.20, ceteris paribus. It concludes that social costs behind underpricing are detrimental to China’s rural reform. This study contributes to economic theory, with important implications for policy makers. To encourage smooth transmission of price signals, it is important to consider farmer characteristics and develop professional farmers.

Behavioural Change in Green Transportation: Micro-Economics Perspectives and Optimization Strategies

The increasing demand for Electric Vehicle (EV) charging is putting pressure on the power grids and capacities of charging stations. This work focuses on how to use indirect control through price signals to level out the load curve in order to avoid the power consumption from exceeding these capacities. We propose mathematical programming models for the indirect control of EV charging that aim at finding an optimal set of price signals to be sent to the drivers based on price elasticities. The objective is to satisfy the demand for a given price structure, or minimize the curtailment of loads, when there is a shortage of capacity. The key contribution is the use of elasticity matrices through which it is possible to estimate the EV drivers’ reactions to the price signals. As real-world data on relating the elasticity values to the EV driver’s behaviour are currently non-existent, we concentrate on sensitivity analysis to test how different assumptions on elasticities affect the optimal price structure. In particular, we study how market segments of drivers with different elasticities may affect the ability of the operator to both handle a capacity problem and properly satisfy the charging needs.

Flexibility Control in Autonomous Demand Response by Optimal Power Tracking

In the regime of incentive-based autonomous demand response, time dependent prices are typically used to serve as signals from a system operator to consumers. However, this approach has been shown to be problematic from various perspectives. We clarify these shortcomings in a geometric way and thereby motivate the use of power signals instead of price signals. The main contribution of this paper consists of demonstrating in a standard setting that power tracking signals can control flexibilities more efficiently than real-time price signals. For comparison by simulation, German renewable energy production and German standard load profiles are used for daily production and demand profiles, respectively. As for flexibility, an energy storage system with realistic efficiencies is considered. Most critically, the new approach is able to induce consumptions on the demand side that real-time pricing is unable to induce. Moreover, the pricing approach is outperformed with regards to imbalance energy, peak consumption, storage variation, and storage losses without the need for additional communication or computation efforts. It is further shown that the advantages of the optimal power tracking approach compared to the pricing approach increase with the extent of the flexibility. The results indicate that autonomous flexibility control by optimal power tracking is able to integrate renewable energy production efficiently, has additional benefits, and the potential for enhancements. The latter include data uncertainties, systems of flexibilities, and economic implementation.

Fiscal Tools for Planning Objectives : Development Charges and Sending the Right Price Signals to Achieve Policy Objectives

Fiscal Tools for Planning Objectives : Development Charges and Sending the Right Price Signals to Achieve Policy Objectives

Fiscal Tools for Planning Objectives : Development Charges and Sending the Right Price Signals to Achieve Policy Objectives

Fiscal Tools for Planning Objectives : Development Charges and Sending the Right Price Signals to Achieve Policy Objectives

Identifying Challenges in Engaging Users to Increase Self-Consumption of Electricity in Microgrids

A microgrid’s self-consumption rate reflects its ability to retain its own energy and decrease its reliance on the synchronous grid. This paper investigates the empirical case of a microgrid equipped with photovoltaic (PV) panels and identifies challenges in engaging the microgrid’s users to increase their self-consumption. Accordingly, we explored both the physical and social dimensions of the microgrid. The former involved mapping the electricity consumption and production through an exploratory data analysis, and evaluating the associated price signals, while the latter involved the use of design interventions to explore users’ perceptions of the system. We highlight the problem of price signal impedance, the need for cost reflective pricing and the challenge in designing and extending internal price models in settings with various actors. We address the limitations of price signals, alongside alternative unidimensional signals, and emphasize the need for an integrated approach to a user engagement strategy as well as the challenges that this approach entails. Our results shed light on the complexity of energy communities such as microgrids, and why their implementation can introduce multidimensional challenges that demand cross-disciplinary approaches.