• Energy Research

Abstract In humanitarian and refugees contexts, to give an adequate quality of life to people living in emergency conditions, energy supply is very important to face with the main problems concerning food cooking and food preservation. The traditional vapour compression refrigerators have relatively high efficiency, but they may have a critical impact on the electric supply system. For this reason, new solutions with thermoelectric refrigerators are emerging; in spite of lower efficiency, they may be more compatible with proper operation of the electrical grid. Furthermore, thermoelectric refrigerators can be used in any position, do not depend on a circulating refrigerant fluid, and are not sensitive to mechanical vibrations. These properties are useful for temporary installations that have to be moved from time to time – typical conditions for some humanitarian camps – and to avoid the use of toxic or flammable refrigerant. This paper addresses the electrical characteristics of a thermoelectric refrigerator connected to the power grid in a microgrid-like installation. A sustainable solution, in which the thermoelectric refrigerator is connected to a microgrid powered by a photovoltaic plant and equipped with an electric storage system, is designed and simulated.

Abstract This paper discusses specific models and analyses to select the best cogeneration planning solution in the presence of uncertainties on a long-term time scale, completing the approach formulated in the companion paper (Part I). The most convenient solutions are identified among a pre-defined set of planning alternatives according to decision theory-based criteria, upon definition of weighted scenarios and by using the exceeding probabilities of suitable economic indicators as decision variables. Application of the criteria to a real energy system with various technological alternatives operated under different control strategies is illustrated and discussed. The results obtained show that using the Net Present Cost indicator it is always possible to apply the decision theory concepts to select the best planning alternative. Other economic indicators like Discounted Payback Period and Internal Rate of Return exhibit possible application limits for cogeneration planning within the decision theory framework.

The definition of bidding zones is a relevant question for electricity markets. The bidding zones can be identified starting from information on the nodal prices and network topology, considering the operational conditions that may lead to congestion of the transmission lines. A well-designed bidding zone configuration is a key milestone for an efficient market design and a secure power system operation, being the basis for capacity allocation and congestion management processes, as acknowledged in the relevant European regulation. Alternative bidding zone configurations can be identified in a process assisted by the application of clustering methods, which use a predefined set of features, objectives and constraints to determine the partitioning of the network nodes into groups. These groups are then analysed and validated to become candidate bidding zones. The content of the manuscript can be summarized as follows: (1) A novel probabilistic multi-scenario methodology was adopted. The approach needs the analysis of features that are computed considering a set of scenarios defined from solutions in normal operation and in planned maintenance cases. The weights of the scenarios are indicated by TSOs on the basis of the expected frequency of occurrence; (2) The relevant features considered are the Locational Marginal Prices (LMPs) and the Power Transfer Distribution Factors (PTDFs); (3) An innovative computation procedure based on clustering algorithms was developed to group nodes of the transmission electrical network into bidding zones considering topological constraints. Several settings and clustering algorithms were tested in order to evaluate the robustness of the identified solutions.

Abstract Several power system problems require solutions in an uncertain environment. According to the relevant literature, expected utility theory (EUT) has been used extensively to solve such problems. However, the application of Prospect Theory (PT) has demonstrated that people deviate from the expected utility maximization because their effective behaviors reflect loss aversion and risk-seeking, reflection effects. The aim of this paper was to compare and critically analyze EUT and PT with the goal of outlining the different behaviors of a “real” decision maker (DM) and an “ideal” DM, with the real DM operating in the frame of PT and the ideal DM operating as EUT describes. The results of using the two different theories were compared by solving three power-system problems in uncertain scenarios.

This paper deals with the use of distributed energy storage systems in microgrids, and proposes a planning method which accounts for the uncertainties of load and distributed generation. Objectives of the planning method are the reduction of the energy costs, while providing the supply of ancillary services as a technical support to the network. The energy costs are evaluated considering a hourly varying pricing scheme and optimizing the storage systems charging/discharging stages. The technical support is devoted to the restraint of bus voltage amplitudes, and of network components' currents/powers within admissible ranges. The input data uncertainties are managed through three decision theory criteria (i.e., the minimization of expected costs; an approach based on the weighted regret felt by the design engineer; and a stability area criterion), which allow considering the multiple design alternatives and futures (i.e., possible values of uncertain input data) in an accurate and feasible way. The design alternatives refer to the size and location of the distributed storage systems, while each future is associated with a different level of load demand and power production of distributed generation over the whole planning period. The results of numerical applications are reported and discussed with reference to a Cigré test network.

In designing a distribution system, engineers have to choose optimal solutions under environmental uncertainty; in most cases, among the uncertainties the ones deriving from the presence of nonlinear loads must be included. Under these conditions, the Decision Theory appears to be a valuable tool for solving distribution design problems. This paper considers three approaches based on the Decision Theory for the economical sizing of medium voltage distribution electrical lines under uncertainty, paying particular attention to harmonics due to nonlinear load presence. In the last part of the paper the implementation and practical application of the sizing procedures are discussed and compared in some case studies.

Abstract The evolution of distribution automation technologies and the advances in distribution system optimisation studies are enabling the implementation of network configurations that are variable in time, with a limited number of configuration changes per day. The first part of this paper addresses the definition of pseudo-optimal intra-day distribution system configurations based on multi-scenario analysis handled with decision theory concepts. The resulting configurations are then used to formulate a demand response scheme for a given time period, aimed at procuring demand reductions to further decrease the distribution system losses. This scheme is driven by the calculation of the marginal loss coefficients and by the customers’ willingness to participate in the demand response action. A dedicated offer scheme to be introduced in a benefit-based mechanism for optimal demand procurement is formulated and discussed.