Heritage Values in the Rehabilitation of Gobbe-Sabz, Iran

Gobbe-Sabz (Green Cupola) is one of the most important and prominent build­ings in Kerman, Iran, dating back to the Qara-khitai dynasty (1222–1306 AD). It was a huge complex of buildings that was almost totally destroyed in an earthquake. Every building during its lifecycle from creation to deterioration acquires values that are important in making any decision about restoration. Brandi’s theory of restoration considers ruins as a work of art, claiming that they are the result of a unique, creative process. He asserts it is necessary to have a creative process for restoration to reclaim its significance in the human consciousness. Although there remains only a small part of Gobbe-Sabz, many remarkable heritage values have been added over time that could be helpful in the creative process for its conservation. The present situation of Gobbe-Sabz precludes rebuilding it as active and complete architecture, determining the process of rehabilitating its original condition. Moreover, some heritage values and meanings have been added to it across the years which are a collection of ideas and concepts that can be useful in deciding the conservation process. In this regard, this research proposes conservation strategies and a conceptual framework for the reha­bilitation of the historic ruins based on their current situation.Gobbe-Sabz (Cupola verde) è una delle costruzioni più importanti di Kerman, in Iran, risalente alla dinastia Qara-khitai (1222–1306 d.C.). Era costituito da un enorme complesso di edifici che fu quasi completamente distrutto da un terremoto. Ogni edifi­cio durante il suo ciclo di vita dalla ideazione al deterioramento acquisisce valori impor­tanti fondamentali per progettare il restauro. La teoria del restauro di Brandi considera le rovine come un’opera d’arte, sostenendo che esse sono il risultato di un processo unico e creativo. Afferma che è necessario un processo creativo per il restauro al fine di restituire il suo significato nella coscienza umana. Sebbene rimanga solo una picco­la parte di Gobbe-Sabz, nel tempo sono stati aggiunti molti valori culturali che potreb­bero essere utili nel processo creativo per la sua conservazione. L’attuale situazione di Gobbe-Sabz preclude la ricostruzione come architettura attiva e completa, deter­minando il processo di ripristino della sua condizione originale. Inoltre, alcuni valori e significati storici sono stati aggiunti nel corso degli anni. Questi forniscono una raccolta di idee e concetti che possono essere utili nel decidere il processo di conservazione. A tal proposito, questa ricerca propone strategie di conservazione e un quadro conc­ettuale per la valorizzazione delle rovine storiche in base alla loro situazione attuale

A Novel Hybrid Framework for Co-Optimization of Power and Natural Gas Networks Integrated With Emerging Technologies

In a power system with high penetration of renewable power sources, gas-fired units can be considered as a back-up option to improve the balance between generation and consumption in short-term scheduling. Therefore, closer coordination between power and natural gas systems is anticipated. This article presents a novel hybrid information gap decision theory (IGDT)-stochastic cooptimization problem for integrating electricity and natural gas networks to minimize total operation cost with the penetration of wind energy. The proposed model considers not only the uncertainties regarding electrical load demand and wind power output, but also the uncertainties of gas load demands for the residential consumers. The uncertainties of electric load and wind power are handled through a scenario-based approach, and residential gas load uncertainty is handled via IGDT approach with no need for the probability density function. The introduced hybrid model enables the system operator to consider the advantages of both approaches simultaneously. The impact of gas load uncertainty associated with the residential consumers is more significant on the power dispatch of gas-fired plants and power system operation cost since residential gas load demands are prior than gas load demands of gas-fired units. The proposed framework is a bilevel problem that can be reduced to a one-level problem. Also, it can be solved by the implementation of a simple concept without the need for Karush–Kuhn–Tucker conditions. Moreover, emerging flexible energy sources such as the power to gas technology and demand response program are considered in the proposed model for increasing the wind power dispatch, decreasing the total operation cost of the integrated network as well as reducing the effect of system uncertainties on the total operating cost. Numerical results indicate the applicability and effectiveness of the proposed model under different working conditions

Two-stage Robust-Stochastic Electricity Market Clearing Considering Mobile Energy Storage in Rail transportation

This paper proposes a two-stage robust-stochastic framework to evaluate the effect of the battery-based energy storage transport (BEST) system in a day-ahead market-clearing model. The model integrates the energy market-clearing process with a train routing problem, where a time-space network is used to describe the limitations of the rail transport network (RTN). Likewise, a price-sensitive shiftable (PSS) demand bidding approach is applied to increase the flexibility of the power grid operation and reduce carbon emissions in the system. The main objective of the proposed model is to determine the optimal hourly location, charge/discharge scheduling of the BEST system, power dispatch of thermal units, flexible loads scheduling as well as finding the locational marginal price (LMP) considering the daily carbon emission limit of thermal units. The proposed two-stage framework allows the market operator to differentiate between the risk level of all existing uncertainties and achieve a more flexible decision-making model. The operator can modify the conservatism degree of the market-clearing using a non-probabilistic method based on info-gap decision theory (IGDT), to reduce the effect of wind power fluctuations in real-time. In contrast, a risk-neutral-based stochastic technique is used to meet power demand uncertainty. The results of the proposed mixed-integer linear programming (MILP) problem, confirm the potential of BEST and PSS demand in decreasing the LMP, line congestion, carbon emission, and daily operation cost

Two-Stage Robust-Stochastic Electricity Market Clearing Considering Mobile Energy Storage in Rail Transportation

This paper proposes a two-stage robust-stochastic framework to evaluate the effect of the battery-based energy storage transport (BEST) system in a day-ahead market-clearing model. The model integrates the energy market-clearing process with a train routing problem, where a time-space network is used to describe the limitations of the rail transport network (RTN). Likewise, a price-sensitive shiftable (PSS) demand bidding approach is applied to increase the flexibility of the power grid operation and reduce carbon emissions in the system. The main objective of the proposed model is to determine the optimal hourly location, charge/discharge scheduling of the BEST system, power dispatch of thermal units, flexible loads scheduling as well as finding the locational marginal price (LMP) considering the daily carbon emission limit of thermal units. The proposed two-stage framework allows the market operator to differentiate between the risk level of all existing uncertainties and achieve a more flexible decision-making model. The operator can modify the conservatism degree of the market-clearing using a non-probabilistic method based on info-gap decision theory (IGDT), to reduce the effect of wind power fluctuations in realtime. In contrast, a risk-neutral-based stochastic technique is used to meet power demand uncertainty. The results of the proposed mixed-integer linear programming (MILP) problem, confirm the potential of BEST and PSS demand in decreasing the LMP, line congestion, carbon emission, and daily operation cost

A novel hybrid two-stage framework for flexible bidding strategy of reconfigurable micro-grid in day-ahead and real-time markets

Microgrids are going to be used in future intelligent grids as a promising technology to enable widespread utilization of renewable energy sources in a highly efficient and reliable manner. It is known that reconfiguration of micro-grids, using tie-line and sectionalizing switches, can provide more operational flexibility. Additionally, coordinated scheduling of flexible loads and energy storage systems can play an important role in the optimal scheduling of micro-grids; thus lowering the costs. This paper proposes an optimal bidding strategy for a micro-grid in day-ahead and real-time markets, based on AC power flow model, considering the hourly reconfiguration of the micro-grid. Fuel cell-based hydrogen energy storage and multiple shiftable loads are considered in the proposed method according to the load’s activity schedule. A reconfigurable micro-grid incorporates energy production and consumption of its local components to trade power in both day-ahead and real-time markets in order to maximize its profit as a private entity. The bidding problem faces issues due to the high level of uncertainties, consisting of wind power generation and electric load as well as variations of market prices. A hybrid two-stage bi-level optimization model is proposed to manage such uncertainties so that wind power, load demand, and day-ahead market prices are handled through scenario-based stochastic programming, and an information gap decision theory is applied to model the uncertainty of real-time market prices under two strategies, namely risk-seeker and risk-averse. The numerical simulation results confirm the effectiveness of the proposed model