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Abstract: Environment friendly policies and emission pricing schemes necessitate the integration of more and more renewable power into electricity grids. However, generation entry and transmission network development in a deregulated market depends on the cost and benefit of a project, where the system/market operator eventually decides the feasibility of investment. In this process, the priorities of market participants are overlooked in some cases. This paper investigates the preferences of market participants in evaluating renewable generation entry to the Australian National Electricity Market (NEM). The priorities of market participants have been investigated through a Multi-Attribute Decision Making (MADM) approach. The TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) algorithm is used to rank the preferences. Optimal Power Flow (OPF) and economic optimization of the Queensland network of the Australian NEM have been simulated in PSS/E and the MATLAB/MatPower software platform. Simulation studies confirm that in the current scenario, gas fired power plants near to the grid will lead in the generation portfolio due to their low lead time, lower investment and dispatchability. Remotely located wind and geothermal power would only be competitive with the existing LRET (Large scale Renewable Energy Target) payments along with very high carbon emission prices. [Copyright &y& Elsevier]

This study develops a long-term integrated planning approach to electricity and gas aiming at economically optimizing the 2030's investments of both networks while considering new policies towards future clean energy. A static stochastic cost minimization model is formulated, which takes into account the short-term uncertainties of renewable power, i.e. wind and utility-scale solar photovoltaic (PV) as well as the long-term uncertainties of load growth and gas price. The equivalent networks of both electricity and gas are driven to accurately capture their existing supplies and transmission networks. In addition, the integrated planning model allows determining the location of new power plants and gas supply facilities with their optimized capacities, as well as new transmission lines and pipelines. An extension of the proposed scheme is considered to accommodate higher penetrations of renewable energy and assess their impacts on both systems. The proposed model is applied to the state of Queensland in Australia, which is a prime example of a region actively integrating electricity and gas. [ABSTRACT FROM AUTHOR]

Grid-edge distributed energy resources (DERs) present both operational challenges and opportunities to distribution system operators (DSO). This paper presents a day-ahead scheduling strategy for DER-rich active distribution networks to leverage operational flexibilities of various DERs for effective network management. The scheduling strategy is realized based on a DSO-centric day-ahead market model that incorporates a multi-period and two-stage optimal power flow (OPF) model to determine scheduling and pricing for network and non-network DERs. The uncertainties in day-ahead operation stemming from local generation, load consumption, and market prices are robustly considered for hedging the intermittency and forecasting uncertainties. A novel bid price function is proposed for local distributed solar PV generation aiming at maximizing participation in network service. A new reactive power management and pricing scheme is also presented for optimal scheduling of voltage support devices within distribution network. The proposed framework is implemented on IEEE-33 bus balanced test system and operational planning strategy is analyzed for overall cost-benefits of the system at various uncertainty levels. A 7-10 percent saving in cost of procurement for DSO can be accrued at various uncertainty levels, and a 10 percent increase in revenue for the PV generation can be observed. • An optimal and sustainable operational planning for the DSO is proposed. • The proposed framework uses day-ahead model for operational planning of DERs. • The uncertainties in market prices, load, and PV generation are considered. • A new reactive power management strategy for fair pricing is proposed. • The proposed framework incentivizes older PV technologies with higher marginal prices. [ABSTRACT FROM AUTHOR]

This paper studies an interdisciplinary approach for improving building energy efficiency. In particular, the proposed approach integrates design innovation (DI) techniques, existing energy audit methods (EAM), and data-driven & engineering modeling techniques (DET) in the process of sustainable smart energy system design. From this perspective, DI methods are extended and modified to suit the content of sustainable smart energy system design and a DI 4D (Discover, Define, Develop and Deliver) framework is introduced to guide the design process. The motivation behind and the implementation procedure of each of the DI phases is explained separately, and the process of integrating DI methods, EAM and DET in developing a sustainable smart energy system is demonstrated. The proposed approach is deployed within the campus of a tertiary education institution to show its effectiveness in designing a smart sustainable energy system. • A design innovation (DI) approach is proposed for smart energy system design. • A comprehensive background of the proposed DI framework is provided. • How DI can be used to design smart energy system is demonstrated. • Experimental case studies are provided to show the benefit of the proposed scheme. [ABSTRACT FROM AUTHOR]