Journal of Energy Engineering

The installation and operation of distributed generators (DGs) has great potential for local utilities to improve distribution system reliability and lower their operating and expansion planning costs. To evaluate this potential, distribution system analyses must reflect its new operating environment with significant DG. Resulting tools can be utilized by both utilities and DG owners to improve their decision making algorithms. As such, this work investigates two different slack bus models for unbalanced distribution power flow and their impacts on subsequent cost analysis. The models include the traditional single slack bus model which assigns the substation as the slack bus and a distributed slack bus model which assigns slack to the substation and DGs according to network-based participation factors. Detailed expressions for cost analysis which directly depend on the distributed slack bus model are presented and discussed. Simulations illustrate that the different slack bus models have significant impacts on cost analysis. The difference in estimated annual profit for local utilities reached up to 265% using the different slack models.

Extension of electrical service to large rural populations in developing nations is a key requirement to realize human development goals set forth by international agencies. This paper presents the case for distributed generation in the form of microgrids, which should be the preferred path towards rural electrification in developing communities and a vital complement to expensive centralized grid expansion. The technical features of frequency and voltage control for distributed generation devices in a microgrid are discussed along with a presentation of their stability attributes. Computer simulation results and experimental results from a laboratory scale microgrid are also presented.

This paper addresses reactive power adequacy problems in distribution networks that include a significant number of distributed energy resources. The voltage profile of the distribution network is analyzed under increasing amounts of generation provided by the distributed energy resources. Both static and dynamic voltage disruption phenomena resulting from increasing distributed generation are described and the need for remedial actions identified. Different reactive power control schemes are then proposed to keep both an appropriate voltage profile and an appropriate voltage stability margin. Finally, an economic appraisal of remedial actions is carried out and the responsible parties identified. Results from a realistic case study are presented and discussed. Conclusions are duly drawn.

Application of individual distributed generators can cause as many problems as it may solve. A better way to realize the emerging potential of distributed generation is to take a system approach which views generation and associated loads as a subsystem or a “microgrid.” The sources can operate in parallel to the grid or can operate in island, providing utility power station services. The system will disconnect from the utility during large events (e.g., faults and voltage collapses), but may also intentionally disconnect when the quality of power from the grid falls below certain standards. Utilization of waste heat from the sources will increase total efficiency, making the project more financially attractive. University of Wisconsin laboratory verification of microgrid control concepts are included.

The cost-effectiveness of interconnected microgrid systems with combined heat and power is examined for 36 cases involving six microgrid applications in six different U.S. locations. In the baseline analysis, microgrids are found to be good investments in areas with relatively high “spark spreads” (electricity/natural gas price differentials). Customers with a higher value for electric reliability realize greater benefits. Results become more favorable over time if the rate of increase of electricity prices is at least 60% of the rate of increase of natural gas prices—a plausible scenario in states with substantial natural-gas fired capacity. Sensitivity analyses reveal that the choice of microgrid customer mix has a much greater impact on system economics than climate. Economies of scale are shown to be fairly modest for the systems considered here, but microgrids do show clear benefits over traditional single customer distributed generation. If performance goals of current U.S. Department of Energy research programs for IC engines and microturbines are met, rates of return for microgrid investments increase 10–20%.

Screening methodology for evaluation of interconnection of distributed generation (DG) to distribution feeder is presented. Applicable regulatory documents are used as guidelines for the approach. DG applications are screened into three categories: those that should be approved without further actions; those which are not acceptable under any circumstances; and those which require further study. Detailed interconnection studies are proposed for further investigation of the proposed interconnection. Additional considerations for siting and capacity allocation of DG are discussed. Application of a screening tool to a realistic feeder model is demonstrated.

Among distributed energy resources, wind power has recently showed great potential and it is being promoted in many countries. The wind power penetration increase and the trend of the wind farms to enter the market, makes necessary the development of new prediction tools. Prediction tools have been fully verified and used for demand forecast and, more recently, to predict the market prices. Among the different prediction methods proposed, the initial and more deeply verified were the statistical ones. In the present work, time series statistical methods are used to explore and assess the achievable improvement over a persistent model. Both autoregressive (AR) models that consider wind power time series and autoregressive with exogenous variable (ARX) models which include wind speed time series are used to carry out the prediction. An analysis of the appropriate parameters for the models is carried out and shows, for different wind farms, comparative results for persistent, AR, and ARX models with 6, 12, and $24\mathrm{h}$ forecast which can be useful for the day-ahead and hour-ahead electricity markets. The study also includes a comparative analysis of the different wind farms considered both independently and in an aggregated manner. The forecast improvement due to the use of ARX models and to the wind farm aggregation is fully assessed.

Electricity produced by distributed energy resources (DER) located close to end-use loads has the potential to meet consumer requirements more efficiently than the existing centralized grid. Installation of DER allows consumers to circumvent the costs associated with transmission congestion and other nonenergy costs of electricity delivery and potentially to take advantage of market opportunities to purchase energy when attractive. On-site, single-cycle thermal power generation is typically less efficient than central station generation, but by avoiding nonfuel costs of grid power and by utilizing combined heat and power applications, i.e., recovering heat from small-scale on-site thermal generation to displace fuel purchases, DER can become attractive to a strictly cost-minimizing consumer. In previous efforts, the decisions facing typical commercial consumers have been addressed using a mixed-integer linear program, the DER customer adoption model (DER-CAM). Given the site’s energy loads, utility tariff structure, and information (both technical and financial) on candidate DER technologies, DER-CAM minimizes the overall energy cost for a test year by selecting the units to install and determining their hourly operating schedules. In this paper, the capabilities of DER-CAM are enhanced by the inclusion of the option to store recovered low-grade heat. By being able to keep an inventory of heat for use in subsequent periods, sites are able to lower costs even further by reducing lucrative peak-shaving generation, while relying on storage to meet heat loads. This and other effects of storage are demonstrated by analysis of five typical commercial buildings in San Francisco, California, in the United States, and an estimate of the cost per unit capacity of heat storage is calculated.